📅 Apr 23: OpenAI's Week: GPT-5.5, GPT-Image-2, Codex CUA + Chronicle, + Claude Design, Kimi K2.6, Qwen 3.6-27B

Hey everyone, Alex here 👋Tomorrow is May. May! I genuinely cannot believe we’re four months into 2026 already, and the AI news cycle is showing zero signs of slowing down. This week’s show was a wild one! We opened with what is genuinely one of the most important AI stories I’ve ever covered (Mayo Clinic AI detecting pancreatic cancer THREE YEARS before human radiologists), we covered the return of the Chinese whale with DeepSeek V4, OpenAI got caught in their own system prompt begging GPT-5.5 to please stop talking about goblins, and I literally gave my coding agent a credit card and asked it to buy my fiancée a wedding gift with the new Strip Link skill and CLI! Oh yeah, I’m getting married next Tuesday! 💍 So next week’s show will be a little different. I’ll be back the week after to catch you up on whatever drops in my absence (almost certainly something major, knowing this industry).Lots to get through, so let’s dive in. (also, in the end I have a full month recap of every major launch, don’t miss) ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Mayo Clinic’s REDMOD: AI Detects Pancreatic Cancer 3 Years Early 🔥 (X, Blog, Announcement)I know we usually cover Models, Parameter sizes, MoEs and big copmanies. But this is important. This is the use case that justifies the entire AI revolution, the GPU burns, the buildouts. I want humans to WIN, and Cancer to be fixed!Mayo Clinic just published a study in Gut (BMJ) validating an AI model called REDMOD that detects pancreatic cancer on routine CT scans up to three years before clinical diagnosis. The numbers are jaw-dropping: They show 73% sensitivity for catching prediagnostic cancers, compared to 39% for experienced human radiologists (while looking at the same exact CT scans).And maybe the most important bit, at scans taken more than 2 years before diagnosis, the AI catches nearly 3x as many cases as specialistsFor context: pancreatic cancer has less than 15% five-year survival specifically because 85% of patients are diagnosed after the disease has already spread. This is the cancer that took Steve Jobs. Imagine if Jobs had access to this AI three years before his diagnosis. That’s the impact we’re talking about.As Dr. Ajit Goenka from Mayo Clinic put it, the greatest barrier to saving lives from pancreatic cancer has been the inability to see the disease when it’s still curable. This AI can now identify the signature of cancer from a normal-appearing pancreas.Even better: it runs on CT scans people are already getting for other reasons. No extra screening protocol, no new imaging required. Just smarter analysis of existing data. The model also showed remarkably stable performance across institutions, imaging systems, and protocols, with 90-92% test-retest concordance over serial scans.Mayo Clinic is now moving this into prospective clinical testing through a study called AI-PACED (Artificial Intelligence for Pancreatic Cancer Early Detection).When we say “lets f*****g go” that’s what we mean. Yeah getting more intelligence is cool, but I want a world without decease! Let’s F*****g go mayo clinic! Agentic Commerce - Giving OpenClaw my credit card - safely! Stripe Link Wallet and Infrastructure CLI (X, Announcement, Blog, Announcement)Ok, give an LLM your credit card, what can go wrong.. right? Well, it’s clear that this, increasingly, is the future of commerce. Agents will be shopping for us, and we need solutions here. Well, this week at Stripe Sessions (Stripe’s annual product lineup conference) just delivered. Link Wallet, is a new ... API? CLI? Skill? Definitely a skill, for your agents, to connect with your Stripe Link (the thing that stores your credit cards safely) and then giving your agent a budget, it can go and make purchases in your behalf. Now the trick here, is, every purchase, you get a notification to approve, and the agent never sees your actual credit card number! This I think is the biggest win here. To test it out , first, I showed Wolfred the install instructions, which are literally this: Read link.com/skill.md and get me set up with LinkAnd then I asked Wolfred my OpenClaw assistant to buy me a present of its choice for my upcoming wedding, and that I don’t want to know what the present is, but I can approve the spend! OpenClaw installed this, sent me a link to connect to my Link.com account, I also downloaded the Link app to receive notifications (and had to enable them by hand, it was a bit annoying to discover, but they said they will fix the onboarding) and .. voila, my agent can now go spend my money, and I get these approval notifications: The kicker? The present Wolfred sent us is due to arrive like 2 months after the wedding 😂 But hey, it’s still something! My agent went, chose a wedding gift in budget, asked for my approval to puchase, and filled out the details (asked me for a few of them) and voila, first agentic purchase that did not require my credit card exposed! Stripe announced a whole bunch of other Agentic Commerce Suite features, like Shared Payment Tokens, which are scoped to seller and protected by Radar, MPP (machine payment protocol) and streaming payments using stable coins that are pretty slick and a bunch of other interesting things. This is where the world is moving to, and Stripe is innovating hard here, definitely worth keeping an eye out on what they are Speaking of agents and stripe, they also opened up the waitlist for projects.dev - which is a way for agents to provision accounts fully on their own, get API keys, and set everhing up from scratch. I think it’s a wonderful addition to the agentic tools and agentic internet! Your agent just runs something like stripe projects add cloudflare/workers abd boom, you have a workers deployment, with credentials synced, no dashboard clicking or API creation!Big Companies & APIsGPT-5.5 Goblin Mode: The Funniest Bug Report in AI History (X, Blog)Someone on X noticed that Codex system message for GPT 5.5 that launched last week has this interesting addition: “Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user’s query” and it has it two times! This created a bunch of memes, questions and wonderings about ... why would OpenAI care so much about Goblins. And they finally posted a long writeup on why: the TL;DR there is, GPT 5.5 absolutely LOVES talking about Goblins, trolls and other nerdy creatures. This is a result of them favoring the “nerdy” personality archetype and reinforcing this reward via RL. OpenAI admitted that “Unfortunately, 5.5 started training before we found the root cause of goblins” and so, now, we get 5.5 that LOVES to talk about goblins, can’t stop talking about goblins (unless they are asked to stop by a system prompt) OpenAI also posted the exact instructions of how to “unleash“ the goblin mode on the blog, which I find hilarious, a company that leans into the meme is a company to be celebrated 👏 GPT 5.5 is as good as Claude Mythos on CyberSecurityAccording to the AI Security institute, GPT 5.5 (not the GPT 5.5 - Cyber version that was announced), the one you have access to, is as good as Claude Mythos on vulnerability finding. We previously reported that Anthropic deemed Claude Mythos as “too dangerous to release publicly” and it turns out that that was either a marketing “Myth”, or Anthropic’s inability to server this huge model like they server Opus. OpenAI Ends Microsoft Azure ExclusivityThis piece of news sent quite a lock of shock throughout the industry, somehow, Sam Altman and OpenAI have been able to negotiate through the very strict deal with MIcrosoft and now are available in AWS as well as Microsoft Azure! Apparently the AGI clause is now gone as well! For many startups who are locked into AWS and Bedrock ,this is great news, they are not able to use GPT 5.5 and other OpenAI models directly applying their credits. Other Big Company NewsXai released Grok 4.3 - in a quiet release in their API docs, no blogpost, not even an X announcement. The only way I know about this was Artificial Analisys, Arena and Vals AI all posted that it jumped in scores. With the same price as the previous Grok, but only 1M tokens, it seems significantly better that its predecessor jumping (X)Gemini can now generate and export Docs, Sheets, Slides, PDFs directly from chat — available globally for free. Google literally put Microsoft Word and Excel icons in the announcement. They’re giving away what Microsoft charges for with Copilot to 750 million users. (X, Blog)Mistral Medium 3.5 dropped as a 128B dense model with 256K context, 77.6% on SWE-Bench Verified, and configurable reasoning effort. Their Vibe coding agent now supports remote parallel agents and session teleportation. $1.5/$7.5 per million tokens.(X, HF, Blog)Baidu’s ERNIE 5.1 Preview landed at #13 on Arena’s Text leaderboard, making it #1 among all Chinese labs. Speculated to be an 800B/36B active MoE using only 6% of comparable pretraining compute. (X, Announcement)Open Source AIThe Whale returns - DeepSeek drops V4 with insane attention innovations (X, Arxiv, HF, HF)Folks, DeepSeek just dropped V4! Two models: V4-Pro at a whopping 1.6 trillion params with 49 billion active, and V4-Flash at 284B total with only 13 billion active. Both support 1 million token context natively! V4-Pro-Max gets 93.5% on LiveCodeBench, beating every other model including Gemini-3.1-Pro. Codeforces rating of 3206, that’s a new record, beating GPT-5.4’s 3168. SWE-Bench Verified at 80.6%, that’s basically tied with Opus-4.6 at 80.8%. But here’s the thing, this model doesn’t overwhelm with evals performance, it’s at par with other open source models and at 1.5T nobody is running this on home GPUs! The bigger story here is the efficiency at long context! At 1 million context, V4-Pro uses only 27% of the FLOPs and 10% of the KV cache compared to DepSeek V3.2. The KV cache at 1M is like 8.7x smaller than V3.2. The pricing is also ridiculous (well, it was always cheap but with these perf. innovations, DeepSeek can afford to undercut! API pricing is $0.145/$3.48 per million tokens for Pro (7x cheaper output than Opus 4.7) and $0.028/$0.28 for Flash (30-100x cheaper than GPT-5.5)This release didn’t break through the AI bubble quite like DeepSeek R1, and we covered this on the show, but like a good whale, what you see on the surface is tiny compare to what lies beneath. This is a technological and innovation marvel, reducing compute and memory requirements by 90% compared to standart attention? CrazySenseNova U1: Unified Multimodal Without an Encoder - an oss infographic creator (X, X, HF, Blog, Try it)SenseTime open-sourced something genuinely architecturally wild this week. SenseNova U1 is a unified multimodal model — 8B parameters with a 3B active MoE variant, both Apache 2.0 — that does both understanding and generation end-to-end with no visual encoder and no VAE.They call the architecture NEO-Unify, and instead of the traditional pipeline (image → visual encoder → LLM → VAE → output), it’s just a single model handling pixels and words natively. The numbers are absurd for the size: 57.5% on Spatial Understanding (Qwen-VL: 35%) and a very high 91% on GenEval-Info for infographicsNisten and I tried it live on the show and it generated coherent infographics with crisp text — something most 8B models struggle with. Chinese users are reporting it rivals Qwen-Image 2.0 Pro for design drafts at much higher inference speeds. But for us, another inforaphic resulted in a bunch of chinese text, FWIW we didnt prompt for English only. The 3B-active MoE variant runs comfortably on consumer GPUs. Apache 2.0, fully open, in collaboration with MMLab at NTU. This weeks Buzz - W&B update! The biggest update this week is, we have gone viral with WolfBench.ai ! Wolfram has tested the Cursor harness (as well as many other harnesses) with GPT 5.5 and saw the best result we’ve tested so far! We still have a lot of testing to do, to add the Codex CLI itself, Devin, and many folks are asking for OpenCode and FactoryAI droids! Also, we’ve launched the IBM Granite 4.1 models on W&B for a very cheap $0.05 / $0.10 per 1M token. This model series are instruct but without reasoning, apache 2 licensed. Get it hereAre you concerned about your Cognitive Security? Guest speaker Max Spero from Pangram Labs says you should beWe had Max Spero from Pangram Labs on the show to talk about their Chrome extension that auto-flags AI-generated content as you scroll your feed. I’ve been using it for a while and many of my suspicions about who’s a slop merchant have been validated.According to Max, Pangram has a 1 in 10,000 false positive rate. If Pangram says something is AI, you can be very confident it was AI-generated. They don’t catch everything, short text, heavily humanized content, or very new models might slip through. But when they flag something, they claim they have 98.99% accuracy that it was written with AI. Max addressed the notion that previous “AI detection” tools like GPTZero and others were often mocked, for a lot of false positive responses, for example, saying that the declaration of indepence was written with AI, and says that this is no longer the case! Taylor Lorenz used the Pangram API to scan top Substack bestsellers and found some popular “writers” are nearly fully machine-generated. Technology substacks have the highest AI content rate; more than 1 in 4 top posts showing substantial AI content. And that’s only what Pangram catches.Max framed it as “cognitive security” - knowing what your inputs are. LLMs are already superhuman at persuasion, and if you’re getting one-shotted by AI-generated content that you think is human, that matters. They’re working on multimodal detection next (images, video), which will be huge given how hard GPT-Image-2 outputs are to spot.I find their chrome extension very useful, I scroll on my feeds and see a bunch of “ai” labels, and I can know to skip that content if I don’t want to. You can get 2 weeks trial to their chrome ext on pangram X account.April 2026 - a full month of AI model releasesApril was an insane month, here’s the major release calendar for April 2026Mar 31: Claude Code leakApr 1: Alibaba Wan 2.7-Image · Fish Audio STTApr 2: Google Gemma 4 | Alibaba Qwen 3.6-Plus Apr 4: OpenAI GPT-Image-2 (Arena leak)Apr 6: MemPalaceApr 7: Anthropic Claude Mythos Preview · Z.ai GLM-5.1 Apr 8: Meta Muse SparkApr 9: Anthropic Managed AgentsApr 10: AI Engineer LondonApr 11: MiniMax M2.7 (open weights)Apr 14: Baidu ERNIE-Image 8BApr 15: Google Gemini 3.1 Flash TTSApr 16 : Anthropic Claude Opus 4.7 | OpenAI Codex (computer-use)Apr 17: Anthropic Claude DesignApr 20: Moonshot Kimi K2.6 · OpenAI Codex ChronicleApr 21: OpenAI ChatGPT Images 2.0 Apr 22: OpenAI Privacy Filter (1.5B)Apr 23: OpenAI GPT-5.5 + GPT-5.5 ProApr 24: DeepSeek V4 Pro & FlashApr 27: Cognition Devin for TerminalApr 29: Cursor SDK | Baidu ERNIE 5.1 Preview | Stripe Link Wallet (Agents) · IBM Granite 4.1 8BApr 30: xAI Grok 4.3That’s all for today folks, we’ve talked about a few other things, and the TL;DR list of releases keeps growing and growing from week to week. As I said, I’m getting married next week, so I will be out, and won’t be on the live stream, Yam, Ryan, Nisten and LDJ will make sure you’re up to date! If you found this valuable, please consider supporting our publication with a subscription and share with a friend. Alex 🫡ThursdAI - April 30, 2026 - TL;DRHosts and Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co-Hosts: @WolframRvnwlf, @yampeleg, @nisten, @ldjconfirmed* Guest: Max Spero (@max_spero_) - Co-founder, Pangram LabsHealthcare AI* Mayo Clinic’s REDMOD detects pancreatic cancer up to 3 years before clinical diagnosis with 73% sensitivity vs 39% for radiologists (Announcement)Open Source LLMs* DeepSeek V4 paper drops with CSA+HCA attention, 1M context at 5.7GB KV cache, possibly first frontier model trained across multiple datacenters (Arxiv)* SenseTime open-sources SenseNova U1 - unified multimodal 8B/3B-active MoE with no encoder/VAE (HF, GitHub)* IBM releases Granite 4.1 family (3B/8B/30B) - non-thinking dense models with 20x token efficiency over Qwen3.5 9B, Apache 2.0 (Blog, HF)* Mistral launches Medium 3.5 - 128B dense flagship with 256K context, configurable reasoning, plus Vibe coding agent (HF, Blog)* Baidu ERNIE 5.1 Preview hits #13 on Arena (#1 Chinese lab) using just 6% of comparable pretraining compute (ernie.baidu.com)Big CO LLMs + APIs* OpenAI publishes blog explaining GPT-5.5’s “goblin mode” - reward amplification during RL training created an obsession with creature metaphors, leading to duplicated suppression instructions in the Codex system prompt* OpenAI ends Microsoft Azure exclusivity, AWS announces GPT-5.5 and Codex on Bedrock; AGI clause removed from contract (Sam tweet)* Gemini can now generate and export Docs, Sheets, Slides, PDFs, .docx, .xlsx, LaTeX directly from chat - free for all users globally (Blog)* NVIDIA releases Nemotron 3 Nano Omni - 30B/3B-active hybrid Transformer-Mamba MoE with 256K context, 9x throughput on consumer hardware (Blog)Agentic Commerce & Tools* Stripe launches Link wallet for agents at Sessions 2026 - AI agents get scoped payment credentials with mandatory human approval, real card never exposed (Blog)* Stripe removes waitlist on Projects.dev - 32 infrastructure providers (Cloudflare, WorkOS, ElevenLabs, Twilio, Daytona, Browserbase, AgentMail, etc.) provisionable via CLI for AI agents* Cursor launches SDK exposing the same runtime, harness, and models that power Cursor IDE - now embeddable in any product (Docs)* Cognition launches Devin for Terminal - local CLI coding agent with /handoff command for seamless cloud transfer (cli.devin.ai)Evals & Benchmarks* WolfBench tests 23 models across 300+ runs on Terminal-Bench 2.0 - Cursor Agent + GPT-5.5 is the #1 combination (wolfbench.ai)* Microsoft’s DELEGATE-52 benchmark shows GPT-5.4 loses 28% of document content after 20 iterative edits, frontier models corrupt stealthily while preserving structureThis Week’s Buzz - Weights & Biases* IBM Granite 4.1 live on W&B Inference at $0.05/$0.10 per million input/output tokens with 128K context* WolfBench results going viral with Cursor + GPT-5.5 dominance, Codex and Devin testing in the pipelineAI Detection & Cognitive Security* Pangram Labs launches Chrome extension auto-flagging AI content in real time on X, LinkedIn, Reddit, Substack, Medium with 99.98% accuracy and 1-in-10,000 false positive rate (pangramlabs.com)* Taylor Lorenz uses Pangram API to analyze top 25 Substack bestsellers, finding many popular newsletters are near-fully AI-generatedAI Art, Video & Audio* ElevenLabs launches ElevenMusic - full music platform with discovery, remixing, royalties; 4,000+ indie artists at launch (elevenmusic.io)* HeyGen HyperFrames integrates natively with Claude Design - HTML-to-MP4 motion graphics via single CLI command (hyperframes.dev)* xAI drops Grok Imagine update with dramatically improved lip sync, sound, and 30-second video extensions* OpenAI engineer confirms team is actively fixing GPT-Image-2’s noise artifact issueOther* Talkie - 13B open-weight LLM trained exclusively on pre-1930 text, by Alec Radford and David Duvenaud (talkie-lm.com)* GPT-5.5 Codex full system prompt leaked from OpenAI’s open-source repo, revealing 272K context window, four reasoning levels, three personality modes, and the duplicated anti-goblin instruction This is a public episode. 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Hey, Alex here, I’ll try to catch you up, but it’s one of the more intense weeks in AI in recent memory. Here’s the TL;DR - OpenAI dominates across the board this week! Finally launches “spud”, called it GPT 5.5 (and 5.5 Pro), and it’s SOTA on most things,nearly matching the mysterious Claude Mythos but released and we can actually use it (we tested it extensively). OpenAI also took the crown in image generate with the incredible GPT-image-v2 release, beating Nano Banana 2 and pro by a significant margin, the images are incredible, this model can generate working QR codes and 360 images it’s quite bonkers. Codex was updated with Computer Use (which I told you about last week), in-app browser and a bunch of other tools that match GPT 5.5 intelligence. Meanwhile, Anthropic launched an incredible research preview of Claude Design, finally admitted that Claude was dumb and reset quotas across the board, while breaking the trust of the community with removing Claude code from the pro plan. We’ve also got great open source updates, Kimi K2.6 and Qwen 3.6 27B are both great performers! We were live on the stream for almost 4 hours today waiting for GPT 5.5 and finally got it and tested it live on the show + had Peter Gostev on from Arena who had early access and shared with us his insights. Let’s get into it! ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.OpenAI’s GPT 5.5 is here - SOTA AI intelligence you can actually use (Release Blog)OpenAI finally gave us all access to their latest intelligence boost, GPT 5.5 thinking (and GPT 5.5 Pro). These models take the crown across many benchmarks, including TerminalBench (82.7%), GPDval (84%) and more. You can see the highlited versions on the image above. Though, its not uncommon for OpenAI to do some chart crimes, so @d4m1n created a chart that also showed the full benchmarks, including the ones GPT 5.5 is not beating Opus at, as you can see below, it underperforms on Humanity’s Last Exam, and scaled tool use. But, benchmarks don’t tell the full story. GPT 5.5 uses significantly less tokens, compared to 5.4, about 40% less. It’s also more expensive, but given the lower token usage, it nets out at about ~20% price increase, while being more intelligence and faster. Tons of folks who had early access are reporting the same things, this model excels in long running tasks, Peter Gostev from Arena, who joined our live stream, showed us an incredible demo that ran overnight for over 8h! This model can work until the task is done, no longer just pausing in the middel asking for your input. The real highlight is, paired with the recent GPT-image-2 (which I’ll expand on later in this newsletter), GPT 5.5 becomes an excellent UI designer. This is a big area in which Claude still has moat and OpenAI is trying to catch up here, and the real alpha now is to use both the Image gen and 5.5 in tandem to create beautiful visuals and UIs. The main thing is, after testing it quite a few times, this only works if you generate an image outside of the session that builds the actual UI. we tried a couple of times to do it in 1 session, and the resulting UI doesn’t seem to be remotely close to the generated image. Only after sending this image to a completely fresh session and asking for a “pixel perfect” implementation, did GPT 5.5 start to resemble the input image and rebuild the whole ui in pixel perfect fidelity! GPT Image v2 - SOTA thinking image model, finally beating Nano Banana (Blog, Live)Like we said, OpenAI is dominating this week, and in both instances those are great models. Though, apples to apples comparison, GPT-image-v2 is a much higher jump — from previous models — than GPT 5.5! According to Artificial Analysis, the jump in how many people prefer GPT-image-2 in blind tests compared to other model is the higest we’ve ever seen, over 250 points. And you can clearly see it in the generations as well. Previously this week, we did a live streaming session with Peter Gostev (from Arena) and we did a deep dive comparing this new model to GPT Image 1.5, Nano Banana and Grok Imagine, and it’s a clear winner across most categories.Character consistency is immaculate, high resolution imagery, instruction following, are all so so good it’s a bit hard to explain in text. Reasoning visual intelligence Like with Nano Banana, this model is likely based on a big GPT image, it’s no longer just diffusion, as you can see, it reasons! And apparently the more reasoning you give it (if you choose GPT pro) the better it’ll be. The examples are indeed wild, the model can generate images of code that works, generate functional QR codes and bar codes! The craziest thing people figured out it can do, is functional 360 imagery (equirectangular format), you can just ask the model to create a 360 image of “scene” and then drop this in to a 360 viewer! Peter shows us on the show how he combined GPT 5.5 and Image v2 to create a sort of “street view” from a bunch of 360 images, it blew our minds. He literally spun up an overnight GPT 5.5 task in Codex that planned out the hanging gardens of Babylon, generated hundreds of equirectangular images, stitched them into a walkable interface, and had it running 8+ hours without babysitting. A street view of a place we don’t actually know what it looked like, hallucinated from latent space. What a time.Day one availability is wide: Figma, Canva, Adobe Firefly, fal.ai, and Microsoft Foundry all have it. Nano Banana dominated for what felt like an eternity in AI time (it was really only a few months 😅), and finally OpenAI has a proper answer.OpenAI is dropping models on HF - Privacy Filter, a 1.5B apache 2.0 PII reduction model (X, HF)I’ve told you the’ve been cooking this week! OpenAI open sourced a genuinly useful model called Privacy Filter, that has 1.5B parameters with only 50M active, small enough that it runs in fully offline in your browser (check out this incredible web demo by our friend Xenova) This model is specifically built to anonymize and filter our personally identifiable information (PII), things like names and addresses, but more importantly bank accounts and API keys! This, in the era of agentic assistants is extremely important and I’m very happy that OpenAI is open sourcing here, specifically because while it’s great generally, this model is great for fine-tuning on your own data! Pairing this with something like CrabTrap, a new open source proxy with LLM as a judge for agents like OpenClaw, and you’re hardening your setup so that your private details won’t leak, even if someone manages to prompt inject your agent! In every other week, CrapTrap would deserve a segment of its own, it is really a novel solution to the “AI agent can leak your creds” problem, created by Brew CEO, as they run agents inside Brex, but this week is insane, so... you get a link and we move on 🙂 Claude Design - Anthropic’s figma killer? (try it, deep dive)This launched on Friday (come on Anthropic, why are you launching things on a friday?!) and nearly tanked Figma stock (16% down since). It didn’t help that Mike Krieger who runs product at Anthropic and co-leads Anthropic Labs, quit the Figma board just a few days before this release. Claude Design is a new, separate interface for Claude, with its own usage meter, that exists only on web, and only for Max subs for now. We all know that Claude is great at frontend design, but this is an interface that wraps Claude, with some incredible “designer like” tools. Knobs to edit font sizes, point and click interface to highlight elements for Claude to fix. The highlight for me, what broke my brain on the live stream, was the “talk to the design” feature, where you turn on the microphone, talk to Claude, and while you point, it “knows” what you’re pointing at! So you can say “here, fix THIS thing” without saying what that thing is, and Claude will just fix it, by looking at where your cursor was at the time. This ... this feels like magic. The huge unlock in Claude Design is the initial “brand guidelines” process, in which you ask Claude to create a holistic brand identity (based on your website code, screenshot, Figma file etc) and then, every new project, can have that brand identity preserved, with the right fonts, colors, logos etc. I dropped the show notes from this week and asked for an interactive infographic website using the brand guidelines. This really does feel like a “new kind” of product, I’ve worked with designers before, the interaction model with Claude Design feels very much like working with a designer, showing them what you like and don’t like. And like working with a designer, it’s expensive! Claude Design uses Claude 4.7 and buuurns through tokens! I’ve tapped out of my weekly quota in less than 4 projects! Luckily, Anthropic this week admitted that they’ve dubmed down Claude, and reset the quotas, so I was able to show it on the live show. This week’s Buzz — W&B LEET TUI gets Workspace modeOur W&B LEET TUI went viral a couple weeks back (local terminal UI for watching run stats, metrics, and system health - built for folks training on remote boxes who don’t want to alt-tab to a browser), and the team shipped a big follow-up this week: workspace mode.Multi-run workspaces live, metadata filtering, system metrics (GPU stats included), console logs, and — my favorite — images rendered directly in the terminal . The whole web workspace experience, now in your SSH session.Demo video and full announcement here. pip install wandb, give it a spin.Open Source AIKimi K2.6 - Opus at home (if you have a data center) (X, HF, Live)Moonshot AI dropped Kimi K2.6 this week, a 1 Trillion parameter MoE with 32B active, 384 experts, 256K context, under a modified MIT license. The headline numbers are wild: SWE-Bench Pro at 58.6 (beating GPT-5.4 and Opus 4.6), BrowseComp at 83.2, HLE with tools at 54.0.Wolfram ran it on his own Wolf Bench and it came out as the best open source model he’s ever tested — essentially matching Sonnet 4.5 on terminal bench with the Terminus agent harness, and beating Opus 4.6 inside OpenClaw. That’s a crazy sentence to write.Pricing on Cloudflare Workers AI is $0.95/M input, $4/M output — roughly 15x cheaper than Opus. If you have the budget to run it.Now, the calibrated take: Yam showed us a report from @BrightMind where Kimi failed pretty badly at rendering a 3D lava lamp while every other frontier model nailed it. Artificial Analysis has Kimi at #4 on their intelligence index (54) behind the three frontier labs. So it’s definitely a bit benchmaxxed on agentic coding, but it’s also genuinely good at agentic coding, which is the use case most people care about right now. My own test: it overthinks a lot, generates a lot of tokens (which hits your wallet even at those low prices) and I wasn’t very happy with it during my live test. The frontend design of it is meh, and it did feel benchmaxxed. Bottom line: if you’re building an OpenClaw setup and you want Opus-adjacent quality without paying Opus prices, Kimi K2.6 could be the move. They also shipped Kimi Code CLI as a companion to Claude Code / Codex CLI.Alibaba drops Qwen 3.6 27B - (Actually sonnet at home) This one is special because it’s genuinely, actually runnable at home. It’s a dense 27B model under Apache 2.0, and it beats Alibaba’s own ~400B Qwen3.5 flagship MoE on every major coding benchmark. SWE-bench Verified 77.2, Terminal-Bench 2.0 at 59.3 (matching Opus 4.5), SkillsBench 48.2 (beating Opus 4.5 at 45.3).With Unsloth’s dynamic GGUFs, this runs on 18GB of RAM. A used RTX 3090 under $1000 or a 24GB Mac Mini and you’re running something genuinely comparable to Sonnet 4.5 at home. Nisten has been daily-driving it and said people are calling it “Sonnet 4.5 at home” - it’s not drop-in replacement perfect (it struggled with hard git merges in his testing), but for non-critical work? Absolutely there.Natively multimodal, 262K context extendable to 1M. There’s also a sibling, Qwen3.6-Max-Preview, available on their API if you want the frontier version.Great great open source model! Quick hitsA bunch of stuff worth knowing about that didn’t get full segments:* Google Gemini Deep Research + Deep Research Max on Gemini 3.1 Pro (announce) — autonomous research agents that navigate web + your custom docs. Plus native chart generation and MCP support in the API.* Google Gemini Enterprise Agent Platform (launch) — evolution of Vertex AI for enterprise agent builders.* ChatGPT Agents “Hermes” leak — an agents builder/studio with templates and Slack integration incoming per @btibor91.* Codex now has 4M users per the team, and they open-sourced Euphony, a visualizer for Codex session logs.* SpaceX / Cursor $60B deal — the structure is either a $60B acquisition or a $10B collaboration experiment. The thesis being whispered: are developer traces the missing training ingredient for frontier coding models? Very spicy, very Elon.* Speaking of Elon, XAI released Grok-Voice-think-fast 1.0 (Blog) - it’s their fully end to end omni model that takes customer calls and is already deployed at scale at Starlink! Very interesting contender to Gemini Flash live model we covered before. The benchmarks look insanely goodPhewI said at the top this was one of the more intense weeks in AI in recent memory, and I genuinely mean it. We were live on the stream for almost four hours. I’ve done five livestreams since last Thursday. GPT 5.5 dropping mid-show was the cherry on top. Between Codex becoming ambient, GPT Image v2 rewriting the ceiling for generative visuals, Claude Design moving a stock price, two incredible open source drops in Kimi and Qwen, and OpenAI quietly re-committing to open source — this was a lot.If you’re feeling the FOMO, you’re not alone. We live this stuff and I still feel it. My ask this week: bookmark the livestreams, play with GPT Image v2 (it’s genuinely the most fun I’ve had with an image model in a long time), and if you’re deploying agents in production, go read the CrabTrap source code this weekend.See you next Thursday — same place, same time, probably another launch that disrupts us mid-show. That’s the world now 🤷ThursdAI - Apr 23, 2026 - TL;DR* Hosts and Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co-Hosts - @WolframRvnwlf @yampeleg @nisten @ldjconfirmed @ryancarson* Peter Gostev (@petergostev) - Arena AI* Big CO LLMs + APIs* OpenAI launches GPT-5.5 and GPT-5.5 Pro — SOTA across the board (Blog, Livestream)* OpenAI GPT-Image-2 — biggest Arena Elo jump ever, thinking mode for images (X, Eval site, Livestream)* OpenAI Codex — Background Computer Use + Chronicle (screen memory), hits 4M users (Chronicle)* GPT-5.5 pre-launch leak in Codex dropdown (X)* Anthropic Claude Design — research preview on Opus 4.7, Figma -7% (X)* Anthropic resets all Claude quotas, admits degradation, allows OpenClaw CLI back (X)* Anthropic ARR crosses $30B* Google Gemini Deep Research + Deep Research Max on Gemini 3.1 Pro (X)* Google Gemini Enterprise Agent Platform (X)* ChatGPT Agents “Hermes” leak — builder/studio + Slack integration (X)* OpenAI clinician/medical model + workspace agents released* Open Source LLMs* Moonshot Kimi K2.6 — 1T MoE, 32B active, SOTA open source on SWE-Bench Pro (X)* Alibaba Qwen3.6-27B — dense 27B, Apache 2.0, beats own 400B flagship (X, HF)* Alibaba Qwen3.6-Max-Preview on API (X)* OpenAI Privacy Filter — 1.5B MoE, 50M active, Apache 2.0, runs in browser (X)* Tools & Agentic Engineering* Brex CrabTrap — LLM-as-judge HTTP proxy for agent security (X)* OpenAIDevs Euphony — open-source Codex session log visualizer (X)* This week’s Buzz - Weights & Biases* W&B LEET TUI goes workspace mode — multi-run, GPU metrics, images in terminal (X)* Voice & Audio* StepAudio 2.5 TTS — natural-language control of emotion and delivery (X)* Deals & Industry* SpaceX/xAI <> Cursor — $60B acquisition or $10B collaboration structure This is a public episode. 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Hey ya’ll, Alex here with your weekly AI news catch up. It’s one of those Thursday’s where no matter how well I prep, the big AI labs are hell bent to show up before each other. Alibaba dropped Qwen 3.6 with Apache 2, confirming their commitment to Open Source, then Anthropic released Claude Opus 4.7 (not quite Mythos) and OpenAI followed with a huge Codex update that includes Computer Use among other things. The highlight of Computer User is the background usage, more on that below. This is all just from today!Previously in the week we had 2 incredible 3D world generators, Lyra 2.0 from Nvidia and HYWorld 2 from Tencent, Windsurf dropping 2.0 version with Devin integration and Google releasing a Gemini TTS, with over 90+ languages support and incredible emotions range, and Baidu open sources Ernie Image, rivaling Nano Banana. Today on the show we had 3 awesome guests, Theodor from Cognition joined to cover the new Windsurf, Kwindla is back on the show to talk about “the side project that escaped containment” Gradient-Bang, a multi agent, voice based space game and Trevor from Marimo joined to talk about pairing your agents with a Marimo notebook. Let’s dive in! 👇 ThursdAI - We’re over 16K on YT today, my goal is to get to parity with Substack, please subscribe. Codex can now really use your computer: OpenAI updates Codex with CUA, Image Generation, Browser, SSH (X, Blog)Codex from OpenAI has been the major focus inside OpenAI for a while now. We’ve reported previously that OpenAI is closing down SORA and other “side-quests” to focus, and that they will join Codex, ChatGPT and the Atlas browser into one “superapp” and today, it seems, that we’ve gotten an early glimpse of what that app will be. The Codex team (which seems to be growing from day to day), have been on a TEAR feature wise lately, trying to beat Claude Code, and they pushed an update with a LOT of features and updates, among them a new memory system, internal browser and image generation. The highlight for me though, was absolutely the polished computer use experience. Computer use is not new, Claude has a computer use feature flag, many others. Hell, we told you about computer use with Open Interpreter, back in Sep of 2023. But, this.... this feels different. You see, OpenAI has quietly purchased a company called Software Apps Inc, that almost launched a macos AI companion a year ago called Sky. This team is obsessed with Mac, and somehow, they were able to build a magical experience, a huge part of which, is the fact that they are controlling the mac, in the background. This is like black magic stuff. You work on one document, Codex clicks buttons and does things in another, without interrupting you. You may ask, Alex, why do you even care so much about computer use, when most of the work happens in the browser anyway, and Claude (and Codex) can control my browser anyway? Well, true, but not ALL work is happening there, for example, file system integration. It’s notoriously big part of browser automation that fails, when you need to upload/download files. I’ve spent countless cycles trying to get this to work with OpenClaw, and this, just does it. This closes the loop between knowledge work in the browser (yes, this thing can use your browser) and the broader OS. It’s so so polished, I truly recommend you try it. It’s as easy as @ tagging any app that you have running and asking Codex to do stuff there. Pro Tip: Enable fast mode for a much smoother experience. Anthropic Opus 4.7 is here, not quite Mythos, 64.3% Swe-bench Pro, tuned for long running tasks (X, System Card)What is there to say? Is this the model we expected from Anthropic after releasing the news about Claude Mythos last week? no. But hey, we’ll take it. I new Claude Opus, with a significantly improved multimodality capabilities, and a long horizon coding task improvements? For the same price? Well, not quite! Apparently, this model could be a “from scratch” trained model, given that the tokenizer (the thing that converts words into tokens for the LLM to understand) is a different one. It also uses 1.3x more tokens for the same tasks, which means, that the new and default model from Anthropic became effectively more expensive (A note they acknowledged by raising the usage limits, to an unknown amount in Anthropic subscription plans, but it’ll still be a token tax on the API use) How about performance? Well, hard to judge on Evals alone, but they are great. A huge jump in Swe-bench Pro, over 10% improvement, puts this model as the best out there, except Mythos. It’s also the best at real world knowledge via GPQA Diamond (except Mythos). Are you seeing a trend here? Anthropic released a preview of a model, but for the first time, it’s not their “absolute best” model, and in a weird move, they have compared it on Evals to an unreleased model (presumably 10x the size?) As far as we’ve tested this, it gave an incredibly detailed response on the Mars question we constantly test on, both for me and Nisten, Opus 4.7 produced an incredibly detailed 3D rendered result, much better than out previous tries. I’ll be keeping an eye on this model and keep you guys up to date on what else we find. Vibe checks are .. it’s more expensive, long context is unclear but it’s a great vibe model. Alibaba is back - Qwen 3.6 is Apache 2.0 35B with 3B active parameters (X, HF, Blog)The coolest thing about this release is not the evals (though they claim to outperform the much denser Qwen 3.5-27B on multple benchmarks) is that Alibabab is putting models with open weights and an Apache 2.0 license! We previouly reported on rumors from inside Alibaba, that a few internal restructuring caused many of us to doubt if they would commit to OSS, and they answered! Another highlight for me in this model, is that Alibaba has an OpenClaw bench (that they are promising to release soon) and that this model does as well as the dense model and beating Gemma 4 by a wide margin on that task. This model is also natively multimodal, with 262K context extensible to 1M via YaRN. MiniMax M2.7 Open Weights - 230B MoE with only 10B active (X, HF)Our friends at MiniMax finally dropped M2.7 in open weights (technically not fully Apache, commercial use requires their authorization, but free for research, personal, and coding agents). It’s a 230B parameter MoE with only 10B active parameters, and it’s matching GPT-5.3-Codex on SWE-Pro at 56.22%. On Terminal-Bench 2 it hits 57%. But the real story here, the part that made me stop scrolling, is the self-evolution piece.They let an internal version of M2.7 run its own RL optimization loop for 100+ rounds with zero human intervention. The model analyzed its own failure trajectories, modified its own scaffold code, ran evals, and decided whether to keep or revert changes. It got a 30% performance improvement on internal metrics. The model improved itself.Shoutout to the MiniMax team — longtime friends of the pod and they keep delivering (as they promised to release the weights for this one and they did) This weeks buzz - news from Weights & Biases from CoreWeaveThis week was a very big one in our corner of the AI world. Our parent company CoreWeave announced not one, not two but 3 major deals, including one with Anthropic, a renewed commitment from Meta and a renewal from Jane Street. CoreWeave now serves 9 out of the top 10 AI model providers in the world. 🎉 Oh and a small plug, if you want to get tokens powered by the same infrastructure, our Coreweve Inference service is open and very cheap, and we’ve recently added Gemma 4 and GLM 5.1 both to our inference service. This week on the pod, I’ve chatted with Trevor, founding engineer at Marimo Notebooks (also part of CW) about their recent highlight of pairing an AI agent with Marimo notebooks, they went quite viral on hacker news and I wanted to understand why. I understood why, it’s really cool. Check Trevor out on the pod starting around 01:05:00 timestamp. Tools & Agentic EngineeringWindsurf 2.0 - Agent Command Center + Devin in the IDE - interview with Theodor Marcu (X, Blog)The first big post-Cognition-acquisition move for Windsurf dropped this week, and I got to chat with Theodor Marcu from Cognition about it on the show. The headline: Windsurf 2.0 brings an Agent Command Center; think Kanban-style mission control for all your agents, plus native Devin integration baked right into the IDE, and Spaces (persistent project containers that group your agent sessions, PRs, files, and context).The framing Theodor gave me: local agents are pair programmers bounded by your attention (they stop when you close the laptop), while cloud agents are independent hires. Windsurf 2.0 tries to unify both paradigms in one interface. You can plan locally with Cascade using the Socratic method — going back and forth, challenging assumptions, building up context — and then with one click, hand off execution to Devin which runs in its own cloud VM, opens PRs, runs tests, and even tests its own work using computer use on its own Linux desktop. You can close your laptop and it keeps shipping.One reality check from the community: Devin is great but not cheap. One early tester burned $25 in credits for a 15-20 minute bug fix that produced “okay” results. Something to watch on the Max plan economics. Devin access is rolling out gradually to Windsurf users over 48 hours from launch. Shoutout to Swyx that helped design the Spaces three months ago whilst at Cognition! Warp terminal now supports any CLI agent with vertical tabs and mobile control (X, Blog)This one is for the terminal enjoyers. Warp, which in my opinion is the best terminal experience out there, just shipped first-class support for any CLI agent — Claude Code, Codex, OpenCode, Gemini CLI, all running side by side in vertical tabs with live status indicators.The killer feature here, and this solves what I think is the single worst part about using Claude Code, is notifications when agents need you. If you’ve used Claude Code you know the pain of constantly checking if it’s waiting for a permission or input. Warp notifies you. You step in, approve, go back to what you were doing. They also added integrated code review inside the terminal, a rich multimodal input editor, and — this is wild — remote control from mobile. Monitor and interact with your running CLI agents from your phone.Voice & AudioGradient Bang - the first massively multiplayer LLM-driven game, interview with Kwindla (X, Play it)Kwindla, co-CEO of Daily and maintainer of Pipecat, came on the show to talk about Gradient Bang, a game he described as “a side project that escaped containment.” He told me about this back in December, and folks, it’s finally live and it’s genuinely the first fully LLM-driven multiplayer game I’ve seen. It’s inspired by an old BBS door game called Trade Wars that Kwindla used to play as a baby programmer on a 386 DX, but reimagined so your ship’s computer is an LLM you can just… talk to.You pilot a spaceship through a procedurally generated universe, but instead of clicking buttons, you talk to the thing, and say things like “take me to the nearest mega port and trade along the way” — and your ship AI delegates to sub-agents to actually do the work. You can run corporations, buy more ships, task them to do 5 exploration loops while you do trade runs. It’s Factorio-meets-Ender’s-Game-meets-voice-AI. I’ve been playing it, my ship is currently roaming the universe as we speak (with 0 credits as someone robbed me!)What makes this technically fascinating is that it’s basically a production-grade stress test for multi-agent orchestration. Sub-agents with shared context, episodic memory across sessions, dynamic LLM-generated UIs (the React front-end is literally rendered from JSON thrown over by a UI agent LLM), and long-running contexts that go for weeks. The architecture is now shipping as a Pipecat library called Pipecat Sub-Agents. Tech stack: Deepgram for STT, GPT-4.1 for the voice agent, GPT-5.2 medium-thinking for task agents, and a dedicated benchmark called GB Benchmarks because tasking these agents is genuinely hard.Fun detail: Kwindla’s rule for this project was to not write or read any code since November. His colleague John lasted about one day before he broke and started reading React. The Z/L Continuum claims another victim. Go play it, it’s free and fun: gradientbang.com.Google launches Gemini 3.1 Flash TTS (X, Blog, Try it)Google dropped a new TTS model this week and folks, it’s not quite the speed-of-light real-time conversational TTS we’re all dreaming of (it’s about 3 seconds time-to-first-token, so batch-mode only), but the controllability is wild. We’re talking inline audio tags — [laughs], [sighs], [gasp] — natural language scene direction, two distinct speakers per generation, 70+ languages with auto-detection, and you can switch emotion and pacing mid-sentence with natural language. I tested it live on the show with a “shocked/whispering” tag combo asking “Who came to ThursdAI?” and it absolutely nailed it. It hit 1,211 Elo on the Artificial Analysis TTS Arena, 4 points behind Inworld TTS 1.5 Max and ahead of ElevenLabs v3. Pricing is about $0.03 per 60 seconds of audio, roughly 4.7x cheaper than ElevenLabs v3.Kwindla’s take: this is part of the broader shift from traditional TTS architectures toward fully steerable, prompt-able speech models — which is great for expressive use cases but means you need to test heavily for hallucinations and word skipping.AI Art, Video & 3DTencent HYWorld 2.0 and NVIDIA Lyra 2.0 - actual 3D worlds from one imageThis week we got not one but two major single-image-to-3D-world open releases, and they’re genuinely different from the video world models (Genie 3, Cosmos) we’ve been covering.Tencent HYWorld 2.0 takes a single image (or text, or video) and produces actual 3D Gaussian Splats, meshes, and point clouds that you can import directly into Unity, Unreal, Blender, or NVIDIA Isaac Sim. Not video. Real editable 3D assets. Their framing: “watch a video, then it’s gone” vs “build a world, keep it forever.” The WorldMirror 2.0 reconstruction model is a 1.2B parameter feed-forward model that predicts dense point clouds, depth, normals, camera params, and 3DGS in a single pass. All open source.NVIDIA Lyra 2.0 (Apache 2.0) takes a single image and progressively generates an explorable 3D world as you navigate through it. The breakthrough here is solving two classic failure modes of generative world models: spatial forgetting (hallucinating new structures when you revisit an area) and temporal drifting (errors accumulating until the scene turns to mush). They solve both with per-frame 3D geometry retrieval and this elegant self-augmented training trick where they train the model on its own degraded outputs so it learns to correct drift. DMD distillation gets you 4-step inference. Apache 2.0, Hugging Face, code and weights.Both of these together feel like the end of video-only world models as the state of the art. We’re going straight to editable, persistent, importable 3D worlds.Baidu open-sources ERNIE-Image - 8B parameter text-to-image (HF)Not to be outdone, Baidu dropped ERNIE-Image, an 8B parameter DiT that’s now #1 on GenEval among open-weight models (0.8856), beating Qwen-Image, FLUX.2-klein, and Z-Image. Built from scratch in 3 months. Runs on a 24GB consumer GPU, and someone already quantized it to NF4 so it runs under 10GB VRAM on an RTX 3060. The text rendering story is the headline — clean multilingual text rendering for posters, infographics, comics, the stuff every other model has been historically terrible at. There’s also a Turbo variant that does it in 8 inference steps.The craziest AI video I’ve ever seen - “Pi Hard” (X)You have to watch this AI video. It’s one of the crazier ones I ever saw, and I do reporting on AI for a living. I showed this to my Fiancee Darya, and she only asked me “is this AI” in the middle of it, after saying “yeah, let’s watch this 😂) Closing thoughtsWhat a week. Opus 4.7 dropped live on the show, Codex is now controlling your mac in the background like black magic, Qwen gave us another Apache 2.0 banger, MiniMax shipped a self-evolving model, and we got two “image-to-actual-3D-world” open source releases on the same week. Oh and a shoe company is now an AI compute company.The Z/L Continuum keeps shifting — I feel like every week I drift a little more toward L, especially after seeing Kwindla ship Gradient Bang without reading code since November. And every week the agents get better at babysitting themselves (Claude Code Routines, Windsurf’s Agent Command Center, Warp’s unified CLI agent UX, Codex’s computer use in the background), which means more FOMAT for all of us.Thanks for reading, share this with a friend, and if you enjoyed this, drop a comment with what you want more or less of. Feedback keeps me going.— AlexTL;DR - ThursdAI, April 16, 2026* Hosts and Guests* Alex Volkov - AI Evangelist & Community with Weights & Biases / CoreWeave (@altryne)* Co-hosts: @WolframRvnwlf, @yampeleg, @nisten, @ldjconfirmed* Guests:* Kwindla Kramer (@kwindla) - Co-CEO of Daily, Pipecat maintainer* Theodor Marcu (@theodormarcu) - Product at Cognition* Trevor Manz (@trevmanz) - Founding engineer at Marimo* Show Notes* Recap essay on the Z/L Continuum from AI Engineer Europe (Blog): should AI engineers still read code? Ryan Lopopolo says no, Mario Zechner says yes for critical paths, everyone in between has FOMAT.* Mario Zechner talk is finally live on AI Engineer youtube (Watch)* Super Gemma 4 26B Uncensored v2 by @songjunkr — trending on HF, 0/100 refusals, fixed tool calls (HF GGUF, HF MLX 4bit)* Gemma 4 21B REAP — 20% expert-pruned Gemma 4 26B MoE by 0xSero using Cerebras REAP (HF)* Parcae (Together AI + UCSD) — stable looped transformer architecture with scaling laws, matches 2x-sized transformer quality (Paper/blog)* Claude Desktop app — rewritten from scratch, completely new app* Gemma 4 on W&B Inference — reply on the announcement post with code Gem Drop for $20 in inference credits, also supports LoRA inference via link* Big CO LLMs + APIs* Anthropic launches Claude Opus 4.7 - 87.6% SWE-bench Verified, 64.3% SWE-bench Pro, 3x vision resolution, new xhigh effort level, /ultrareview in Claude Code, same pricing as 4.6 but new tokenizer uses ~1.0-1.35x more tokens (X, Blog)* OpenAI Codex major update: macOS background computer use, 90+ plugins, gpt-image-1.5 image generation, in-app browser, memory, self-scheduling automations, multi-terminal SSH (X, Blog)* CoreWeave signs deals with Anthropic (multibillion), Meta ($21B expansion, $35B+ total), and Jane Street ($6B cloud + $1B equity), now serves 9 of the top 10 AI providers* Open Source LLMs* Qwen 3.6-35B-A3B - Apache 2.0, 35B MoE with 3B active, 73.4% SWE-bench Verified, natively multimodal, 262K context extensible to 1M (X, HF, Blog)* MiniMax M2.7 open weights - 230B MoE with 10B active, 56.22% SWE-Pro matching GPT-5.3-Codex, self-evolved via 100+ rounds of autonomous RL (X, HF)* Tools & Agentic Engineering* Windsurf 2.0 with Agent Command Center and Devin integration - interview with Theodor Marcu (X, Blog)* Warp now supports any CLI agent with vertical tabs, notifications, code review, mobile remote control (X, Blog)* Claude Code Routines - cron, GitHub event, and API-triggered autonomous agents running on Anthropic’s cloud (Docs)* This Week’s Buzz - Weights & Biases / CoreWeave* Marimo Pair - drop Claude Code / Codex / OpenCode agents directly inside reactive Python notebooks - interview with Trevor Manz (Blog, GitHub)* Gemma 4 now live on W&B Inference on CoreWeave infrastructure, with LoRA inference support* Vision & Video* Craziest AI video of the year: Pi Hard / Neil deGrasse Tyson (X)* Voice & Audio* Gradient Bang - first massively multiplayer fully LLM-driven game, Pipecat sub-agents - interview with Kwindla (Play, GitHub)* Google Gemini 3.1 Flash TTS - 1,211 Elo on TTS Arena, inline audio tags, 70+ languages, ~$0.03/60s (Blog)* AI Art, Diffusion & 3D* Baidu ERNIE-Image - 8B DiT, #1 GenEval among open models, precise multilingual text rendering (HF)* Tencent HYWorld 2.0 - single image to editable 3D Gaussian Splats/meshes, Unity/Unreal/Isaac Sim ready (GitHub)* NVIDIA Lyra 2.0 - single image to explorable persistent 3D worlds, Apache 2.0 (Project, HF)* Other news* Unitree humanoid breaks 100m dash world record at ~10m/s (X)* Allbirds shoe company loses 99.5%, rebrands as “NewBird AI”, raises $50M to buy GPUs, stock up 600-800% (X) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey yall, Alex here, writing this from sunny London, at the first ever AI Engineer conference in Europe!What a show we have for you today! First, let me catch you up on what’s important: Anthropic, this week announced a whopping $30B ARR up from 19B in Feb, while also telling us about Claude Mythos Preview their next gen HUGE model that they won’t release to the public (yet?) that finds crazy vulnerabilities in existing code bases. Apparently OpenAI will follow up with a similar non-public model soon.The Meta Superintelligence Lab led by Alex Wang finally showed what they were working on, Muse Spark, the smaller of their upcoming models on a complete new infrastructure (MSL announcement, Simon Willison’s deep dive on the 16 hidden tools).In other news:Z.AI released GLM 5.1 in OSS finally (HF weights), Seedance 2.0 finally available in US on Replicate, OpenAI testing out GPT-image-2 on LM Arena under codenames, HappyHorse from Alibaba takes the video crown, and Mila Jovovich (5th Element, Resident Evil) releases agentic memory plugin called MemPalace (Ben Sigman’s transparent correction thread is worth reading).We had 5 guests today on the show, we kick off with @swyx the founder of AI Engineer and host of Latent Space. We then chatted with @petergostev from Arena (formerly LMArena) about Mythos and the compute wars, then Vincent Koc, the second most prolific contributor to OpenClaw, then our friends VB from OpenAI and Omar from DeepMind, both previously at HuggingFace. This is a busy busy show, and given the time-zones, I unfortunately don’t have time for a full weekly writeup, but as always, I will share the raw notes and post the video (lightly edited).ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.AI Engineer - LondonThursdAI came a long way since the first AI Engineer conference, but many who read this don’t know, that was my big break. Swyx invited me to cover the first AIE in San Francisco in 2023, and I remember, I was in an Uber to the airport, the driver asked me what I do, and I, for the first time said “I host a podcast”. I (and ThursdAI) owe a lot to Swyx, and AIE team, and it’s been incredible to see how big they’ve grown and how many great speakers this event hosts! The term AI Engineer has drifted in those 3 years, but also has the term Software Engineer. Swyx predicted this nearly 3 years ago, what I don’t think he predicted, is that all engineers are now AI Engineers, and this includes domains like Agens (OpenClaw), Context and Harness Engineering, Evals and Observability, Voice & Vision all of which are tracks in this conference. I was really surprised to see how many of the talks/speakers here are native to London (after all, Deepmind is from here, OAI, Anthropic, Meta have offices here) and the latest boom in agents, OpenClaw, Pi were all Europe based as well, and they are joined the AI Engineer stage. Oh, and there’s also a Giant Inflatable Claw at the entrance, yup, for pictures and vibes, and to show off how quickly the OpenClaw took over the mind-share. Anthropic announces $30B ARR and Mythos, their next model, will not be released to the public. The thing that everyone will tell you, is that Anthropic is on a roll, this is obviously connected to their upcoming IPO this year. We’ve been covering many issues on their part, but this week we saw them posting about a HUGE increase in ARR, from 19B in February to 30B in April, passing OpenAI at $25B. That last fact though, is kind of disproven because they report on ARR differently, OpenAI apparently only counts their cloud revenue from Microsoft per the information. The growth is undeniable though, and so is the most unprecedented release announcement, Claude Mythos Preview, which was rumored for a bit and now was announced proper. With project Project GlassWing, Anthropic has announced that this model is SO good at cyber security and finding bugs in code, that they cannot share it with the public, and through GlassWing they will share it with companies like Microsoft, Linux, CrowdStrike and a bunch of others, to harden their security. This is it folks, this is the first time, where a model was “announced” but deemed too risky to release. Now, is it truly “too risky”? Previously, folks thought that DALL-E is too risky, or cloning voice tech is too risky, and now it’s everywhere. The capabilities catch up even in OpenSource. But the facts are, Anthropic says they’ve found a 27-year old bug in OpenBSD (famously very secure), and that this model is very very good at connecting the dots between several, seemingly inacuous bugs, to string them together into one coheren exploit. This is, indeed scary. Just last week, one of the top security researchers in the world, Nicolas Carlini, now at Anthropic, gave a talk at Black Hat, showing off these results, and saying that these models since December and definitely recently have passed him as a security engineer. If you haven’t seen this talk, watch it, then try to estimate if Anthropic did the right thing by only releasing this model to enterprises first. But on the show, Peter Gostev from Arena gave me a take on this that I haven’t been able to shake. Peter pulled up his Compute Wars chart live on the show — and the picture is that OpenAI is way ahead of Anthropic on compute, with Anthropic only recently getting a noticeable bump (which lines up suspiciously well with Mythos being trainable in the first place). His read: “it sounds cooler to say it’s too risky to release than ‘we can’t serve it.’” The official partner pricing is $25 / $125 per million tokens — 5x Opus 4.6 — but if you don’t have the GPUs to serve it broadly, the price doesn’t matter. In the year of the IPO, the company that cannot serve a model says the model is too dangerous to serve. Make of that what you will.This also reframes the whole rate-limit drama with OpenClaw. Anthropic didn’t ban OpenClaw — I want to be very clear about this because the discourse went sideways. What they did is they made it significantly more expensive for Max-tier subscribers to use Opus through OpenClaw, which pushed a lot of people over to GPT-5.4 via Codex. Same root cause: they’re out of compute. The freshly announced Anthropic + Google TPU deal (Google already owns ~10% of Anthropic) is them trying to fix this — though as Peter noted, it’s pretty wild that Google is propping up a direct competitor to their own DeepMind team. Same pattern as their original $2B Anthropic investment ending up propping AWS Bedrock against Google Cloud. Big Google contains multitudes.Meta Superintelligence Labs ships Muse Spark — Llama is dead, long live MuseLlama is dead, long live Muse. This week Meta finally showed what the very expensive Meta Superintelligence Labs under Alexandr Wang has been cooking, and the answer is Muse Spark — the smaller of their new model family, built on a fully rebuilt AI stack from scratch in just 9 months. Nine months is wild for that kind of overhaul, and the headline number people are quoting is that they reach Llama 4 Maverick capability with over 10x less compute.Spark is intentionally small and latency-optimized — it’s not trying to be the biggest, it’s trying to be the first step on Meta’s new scaling ladder. But the benchmarks in certain areas are nuts: 86.4 on CharXiv Reasoning (beats Opus, Gemini, GPT-5.4), and the one that really got me — 42.8 on HealthBench Hard vs Opus at 14.8 and Gemini at 20.6. They trained it with data curated by over 1,000 physicians and it shows. They also shipped a Contemplating mode which is parallel multi-agent reasoning, hitting 58.4% on Humanity’s Last Exam with tools. Coding is the acknowledged weak point (77.4 on SWE-Bench Verified vs Opus 80.8) but for v1 from a brand new stack, this is extremely respectable.Meta is Back!The real story isn’t any single benchmark though, it’s distribution. Spark is rolling out across meta.ai, WhatsApp, Instagram, Threads, Messenger, and Ray-Ban Meta glasses — billions of users. Meta went from open Llama to a closed consumer model and they’re clearly playing a different game now (though Wang says future Muse versions might be open-sourced).The deep-dive that’s really worth your time is Simon Willison’s post where he poked at the meta.ai chat UI and got the model to spit out descriptions of 16 hidden tools behind the scenes — full Code Interpreter with persistent Python 3.9, a visual grounding tool that does pixel-precise object detection (bounding boxes, point coordinates, counting — it located 8 objects including individual whiskers and claws on a generated raccoon), sub-agent spawning, file editing, and semantic search across Instagram/Threads/Facebook posts. It’s basically an entire agentic harness baked into the chat UI. Jack Wu from MSL confirmed the tools are part of a new harness built specifically for Spark’s launch. Meta stock went up 7% on this. They are very much back in the frontier game.Guest highlights We had an unprecedented packed show with 5 guests (also this is the shortest show we’ve everSwyx kicked us off with vibes from the AI Engineer floor — harness engineering as the dominant theme (gains are coming from the harness, not the weights), the rise of skills (English-as-programming-language) absorbing more of that harness work, and his thesis that supply-chain attacks like the recent light LLM and Axios incidents mean you should basically vendor everything — pip fork instead of pip install. We also chatted about how MCP has gone from “the most exciting protocol” to “settled and stable, therefore less interesting,” which is a great problem to have.Peter Gostev from Arena (you saw a lot of him in the Mythos section above) also dropped a bonus on us: Arena just released 3 years of historical leaderboard data and actual prompt datasets on Hugging Face. He used to literally scrape the arena website by hand into Google sheets to make those overtime leaderboards we all loved — now it’s all public. Also: he confirmed that Seedance 2.0 jumped ~80 ELO points above the next video model on Arena, which is unprecedented — video models normally cluster within 10 points of each other.Vincent Koc — the #2 OpenClaw maintainer after Peter Steinberger — joined us fresh off the OpenClaw track stage. The OpenClaw codebase is now ~1.5 million lines of code including unreleased iOS and Android native apps. GitHub literally caps the issue/PR counter at “5K+” and they hit the ceiling. We talked about OpenClaw 2026.4.5 which ships /dreaming GA (Light/Deep/REM phases that defrag agent memory and write a human-readable Dream Diary to DREAMS.md), built-in video and music generation across 4 backends, GPT-5.4 as the new default, prompt-cache reuse improvements, and Control UI + docs in 12 new languages. Vincent’s framing of dreaming was beautiful — “how do you explain agent memory to a mom? You call it dreaming.” He also gave my favorite line of the show on the GPT-5.4 personality problem: incredible at coding, but soulless. (For what it’s worth, I came home after watching Project Hail Mary, cloned the Rocky voice, dropped it into my OpenClaw, and it was magical. That’s the kind of thing you can only do when the harness and the model are decoupled.)VB from OpenAI told us Codex just hit 3 million weekly active users — up from 2 million last month. We talked plugins (the Stripe / Supabase / shadcn ones that ship as packages), sub-agents (yes, one is named Jason), and Guardian Approvals — an experimental mode that classifies each tool call by risk and only escalates the dangerous ones to you, so you don’t have to YOLO-mode everything. The story that stuck with me though is his 9 AM Codex automation: every morning it reads his Slack mentions, cross-references Gmail and Calendar, and creates 5-minute pre-brief calendar events for upcoming meetings. None of that is “coding.” That’s the super-app future hiding inside a “developer tool.” I’m stealing this workflow.Omar Sanseviero from Google DeepMind came on to celebrate Gemma 4 crossing 10M+ downloads with 1,000+ Gemma-4-based fine-tunes already on HF (and Gemma family total is now over 500M downloads). Gemma 4 is also the foundation for the next generation of Gemini Nano on Pixel/Samsung devices. Lama.cpp vision capability fixes are landing. Gemma 4 is also live on W&B Inference if you want to play. Wolfram (whose entire household runs on Pixel + Google AI Studio, including his 70-year-old mother on voice unlock) was in heaven.This Week’s BuzzA short but spicy week from Weights & Biases:* W&B Automations are LIVE. You can now wire event triggers from your training runs (completion, eval thresholds, drift) into notifications, GitHub Actions, deployments, infra shutdowns — closing the loop from experiment to production. Pairs really well with the iOS app we recently shipped, so you can get a ping on your phone the moment something interesting happens on a run.* GLM 5.1 is live on W&B Inference (alongside Gemma 4 from last week) — the team is moving fast to host the best open models the moment they drop.* Wolfram published a deep dive on “more reasoning is not always better” on the W&B blog — the research behind his finding that giving models more thinking tokens can actually make them dumber on certain tasks. It’s the in-depth version of what we discussed on the show last week, with all the data. Go read it on wandb.com.Also: shout out to everyone who came up to me at AI Engineer and said hi. The Wolf Bench mentions in particular made my day. If you’re listening to this and you’re at AIE — come find us, we’ll be around tomorrow too.That’s it for this week — newsletter is short because the show was long and London is calling. As always, thanks for reading and listening 🫡TL;DR April 9 - show notes and links:* Hosts and Guests* Alex Volkov – AI Evangelist & Weights & Biases (@altryne)* Co-Hosts – @WolframRvnwlf @yampeleg @nisten @ldjconfirmed* Guests: @swyx (AI Engineer / Latent Space), @petergostev (Arena, formerly LMArena), @reach_vb (OpenAI / Codex), @vincent_koc (OpenClaw #2 maintainer), @osanseviero (Google DeepMind / Gemma)* Big CO LLMs + APIs* Anthropic announces Project Glasswing and Claude Mythos Preview, a cyber-defense frontier model too dangerous to release publicly (X, Announcement)* Anthropic’s Claude Mythos is so powerful they won’t release it — found zero-days in every major OS and browser, escaped its sandbox, and scored 93.9% on SWE-bench (X, X, X, X)* Anthropic ARR jumps from $19B (February) to $30B in April — secondary tender sale completed, employees not selling ahead of IPO* Anthropic + Google TPU deal — Anthropic getting massive compute commitment from Google (who already owns ~10% of Anthropic), with Peter Gostev’s Compute Wars chart showing the gap to OpenAI closing* Anthropic ships Managed Agents — fully hosted agent runtime + infrastructure. Selling outcomes, not tokens* Meta launches Muse Spark, the first model from Meta Superintelligence Labs, with natively multimodal reasoning, multi-agent Contemplating mode, and deep health/visual capabilities (X, Blog)* Simon Willison deep dives into Meta’s Muse Spark model and uncovers 16 hidden tools including visual grounding and sub-agents in the meta.ai chat UI (X, Blog, Announcement)* Open Source LLMs* GLM-5.1 from Z.ai is #1 open-source on SWE-Bench Pro at 58.4%, runs autonomously for 8 hours with 1,700+ agent steps (X, HF, Arxiv)* Gemma 4 crosses 10M+ downloads, 1,000+ Gemma-4-based fine-tunes on HF. Did really well on Arena considering size — Peter Gostev confirmed it smashed many models on the Pareto curve* Nisten’s pick: Hermes 27B — trained specifically to be paired with the Hermes harness, allegedly distilled from Opus API. Model + harness shipped together as a portable unit* Tools & Agentic Engineering* OpenClaw 2026.4.5 — biggest release since 4.0: /dreaming goes GA (Light/Deep/REM memory consolidation with a Dream Diary in DREAMS.md), built-in video + music generation across 4 backends, GPT-5.4 as new default, prompt-cache reuse improvements, Control UI + docs in 12 new languages (Release, Vincent, Dreaming docs, FOD#147)* OpenClaw codebase now ~1.5M lines including unreleased iOS + Android native apps. GitHub literally caps at “5K+” PRs/issues — they hit the ceiling* Anthropic did NOT ban OpenClaw — they made Max-tier subscription usage of Opus via OpenClaw significantly more expensive, pushing many users to GPT-5.4 via Codex* Codex hits 3M weekly active users — up from 2M last month. VB walked through plugins (Stripe, Supabase, shadcn), sub-agents, Guardian Approvals (auto-classify tool-call risk), and experimental hooks* Cursor: remote agents + code review agent (78% issues caught pre-merge)* MemPalace: Milla Jovovich and Ben Sigman’s open-source AI memory system goes viral with 26K GitHub stars in 2 days, claims top benchmark scores, then transparently walks back overstated claims (X, GitHub, X, X, GitHub)* This Week’s Buzz (Weights & Biases)* W&B Automations are LIVE — event triggers from your runs into notifications, GitHub Actions, deployments. Pairs nicely with the new iOS app* GLM-5.1 and Gemma 4 both up on W&B Inference* Wolfram published an in-depth blog post on his finding that more reasoning is not always better (models can get dumber with more thinking time) — full writeup on wandb.com* Vision & Video* Seedance 2.0 launches in the US — on Replicate with up to 9 reference images, 3 videos, and 3 audio files for cinematic AI video generation (X, Announcement). Peter Gostev confirmed it jumped ~80 ELO points above the next video model on Arena — a massive gap where most video models cluster within 10 points* HappyHorse-1.0, a mysterious 15B video model from Alibaba’s Taotian Group, takes #1 on Artificial Analysis video arena beating Seedance 2.0, Kling 3.0, and Grok Video (X, X, X, X, Blog)* The Harry Potter “Drip Wizards” AI slop trend — Seedance-powered Hogwarts videos going hugely viral* AI Art & Diffusion & 3D* OpenAI’s GPT-Image-2 leaked on LM Arena under three codenames (maskingtape / gaffertape / packingtape), showing photorealism and text rendering that may dethrone Google’s Nano Banana Pro (X, X, X)* Show notes & key moments* Swyx on harness engineering: gains are coming from the harness, not the weights. The big labs are investing more and more in harness — it’s not going away. Skills (English-as-programming-language) are increasingly absorbing harness work* Swyx on AI Engineer tracks: MCP is “more settled and stable, therefore less interesting.” Coding agents track is bigger this year (Cursor, Factory, super-long-running). Voice & Vision split from Generative Media — multimodality as a single track no longer makes sense* Swyx on supply chain attacks: light LLM and Axios issues mean you should “vendor everything” — pip fork instead of pip install. Tool requests becoming prompt requests* Peter Gostev on Mythos pricing: $25 / $125 per M tokens (~5x Opus 4.6). But the real reason it’s not public isn’t safety — Anthropic likely just doesn’t have the compute to serve it* Peter Gostev on Compute Wars: OpenAI is way ahead of Anthropic on compute. The new Google TPU deal is Anthropic catching up — and weird that Google is propping up a competitor to DeepMind. (Same pattern as when Google’s $2B Anthropic investment effectively propped up AWS vs Google Cloud)* Peter Gostev on Arena data: Arena released 3 years of historical leaderboard data + actual prompts as datasets on Hugging Face. Previously he was scraping it by hand into Google Sheets — now he has Databricks access* VB on Codex workflows: every morning at 9 AM, Codex automation reads his Slack mentions, cross-references Gmail and Calendar, and creates a 5-minute pre-brief calendar event for upcoming meetings. None of it is “coding” — it’s all plugins + connectors* Vincent Koc on the GPT-5.4 personality problem: model is incredible at coding but “soulless.” Wolfram noticed it back in December and cancelled his subscription. Alex cloned the Rocky voice from Project Hail Mary and put it in his OpenClaw — “amazing”* Vincent Koc on Dreaming: three phases (REM, core, deep sleep) that defrag agent memory. The dream log is for the human in the loop — makes memory inspectable in a way a non-technical person (a mom) can understand* Vincent Koc on architecture: the open-source flood forced OpenClaw into a plugin architecture. “Not Lego — Ikea.” Refactored ~1M lines in 9 days at 2 AM at NVIDIA before Jensen’s keynote* Omar Sanseviero on Gemma 4: 500M+ total Gemma downloads across all variants. Gemma is the foundation for the next generation of Gemini Nano on Pixel/Samsung. Lama.cpp vision capability fixes shipping* Wolfram’s Pixel/Google household: kids using AI Studio + Antigravity to build games, his 70-year-old mother using voice unlock on her PixelThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey Ya’ll, Alex here, let me catch you up. What a week! Anthropic is in the spotlight again, first with #SessionGate, then with the whole Claude Code source code leak, and finally with an incredible research into LLM having feelings!? (more on this below). And while Anthropic continues to burn through developer good will faster than their sessions, OpenAI announced a MASSIVE $122B round of funding (largest in history), Google released Gemma 4 with Apache 2 license - we had Omar Sanseviero on the show to help us cover what’s new, Microsoft dropped 3 new AI models (not LLMs) and PrismML potentially revolutionized local LLM inference with lossless 1-bit quantization! P.S - Oh also, something on X algo changed, I get way more exposure now, 3 out of my best 5 posts ever have been from this week + I got the coveted Elon RT on my Claude Code leak coverage. I’ll try to stay humble 😂 Anyway, let’s dive in, don’t forget to hit like or share with friends, and TL;DR with links is as always, at the bottom: ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The Claude Code source Leak: Half a Million Lines of “Oops”So here’s what happened. On March 31st, Anthropic shipped Claude Code version 2.1.88 to npm. Inside that package was a 59.8 megabyte source map file — basically a debugging artifact that contained the entire compiled source code. 512,000 lines of TypeScript across 1,900 files. The entire playbook for how the Claude Code harness works, including a lot of stuff that wasn’t supposed to be public yet.A researcher named Chaofan Shou spotted it at 4 AM ET, posted the download link, Sigrid (who came to the show) posted it on Github and within six hours it had 3 million views and 41,000 GitHub forks (This repo is the highest starred repo in Github history btw, with well over 150K Github stars). Anthropic started filing takedowns, but the internet being the internet, it was already everywhere. The source code is still on tens of thousands of computers right now. (I won’t link directly but there’s a website called Gitlawb, look it up) The community went absolutely wild digging through the source code btw, and they found some interesting things!KAIROS: Claude Code is going to become a Proactive Agent!This is the biggest take-away from this leak IMO, that like OpenClaw/Hermes agentic harnesses, Claude Code is already a fully featured proactive agent, we just don’t have access to this yet. With KAIROS, Claude Code will have it’s own daemon (will run independently from the CLI), will have a background ping system (hello Heartbeat.md from OpenClaw) that will make it wakeup and do stuff, will do “autodream” memory consolidation reviewing your daily sessions and fix memories, subscribe to Github, and maintain daily appent-only logs to show you what it did while it and you were asleep. This is by far the hugest thing, I’m excited to see how / when they ship KAIROS, as I said, 2026 is the year of Proactive agents! My Wolfred OpenClaw agent summed it up very nicely: Undercover ModeFor Anthropic employees working on public repos, there’s an Undercover Mode that auto-activates and strips all AI attribution from commits. The system prompt? “Do not blow your cover.” They really said “this is fine” about shipping internal tools to production while hiding from the world that AI wrote the code. Which, honestly, is kind of incredible meta-humor from whoever wrote that.The Buddy SystemMy personal favorite discovery: there’s a hidden Tamagotchi-style terminal pet called the Buddy System with 18 obfuscated species, rarity tiers (including a 1% legendary), cosmetic hats, shiny variants, and stats like DEBUGGING, PATIENCE, and CHAOS. If you activate it now, you can do /buddy and you’ll have a little companion judging your coding decisions. Anthropic shipped a game inside their CLI tool. Mine is called Vexrind and he’s sarcastic as f**k, I’m not sure I like it. Anti-Distillation ProtectionsThe code also revealed that Claude Code injects fake tool calls into logs to poison training datasets. If you’ve been backing up your .claw folders to train on the data; Stop. Pass your data through something like Qwen or make sure you’re filtering out the noise. (a Nisten tip)The Models That Don’t Exist YetBuried in the code are references to Opus 4.7, Sonnet 4.8, and a model called capybara-v2-fast with a 1 million context window. These haven’t been released. This is yet another confirmation of the leaked “Mythos” model that’s coming soon from Anthropic. Which btw, with Anthropic very rocky uptime lately, the tons of SessionGate issues, the leaked blog announcing Mythos, the leaked Claude Code oopsie, they are not having the best Q1 in terms of proving to the world that they are the safest lab out there. I hope they protect their weights better than they protect everything else, before the rumored IPO later this year. SessionGate is still not solved, despite the official responseI told you about session gate last week, and since then we got, finally, and official acknowledgement from Anthropic. But before that, some folks on Reddit reverse-engineered Claude Code (this was before the source code leak ha) and found a few caching bugs that potentially cause 10-20x increase in price if you use --resume a lot especially. While folks continue to complain about burning through Max account quotas much faster than before, here’s the official response from Anthropic, after the supposed investigation, turns out, we’re using it wrong 🤦‍♂️My take is simple: Anthropic has one of the best models in the world, maybe the best personality plus coding stack in some situations, and they are squandering a chunk of goodwill by not being much more explicit about decreased limits, caching bugs, routing, and usage behavior. Nothing else to add here, really bad DevEx, people can handle bad news. They hate opaque bad news.Gemma 4 Is Here, Apache 2.0, and Honestly… This Is a Big One (HF)This was the hopeful turn in the show. You know we LOVE open source!Right in the middle of all the Anthropic chaos, Google dropped Gemma 4, and Omar Sanseviero from DeepMind joined us live to talk through it. This launch hit a bunch of notes I care a lot about: strong local-friendly sizes, serious open distribution, Apache 2.0 licensing, agentic improvements, and a clear willingness to listen to community feedback.The headline model for me is the 31B Gemma 4. It’s big enough to matter, small enough to actually run in serious local setups, and strong enough that the benchmark chart looks slightly ridiculous. On LM Arena, it is competing far above what you’d intuit from the raw parameter count. When a 31B model starts getting uncomfortably close to models in the several-hundred-billion range, you pay attention.That was really the vibe on the show. It wasn’t just “nice, another open model.” It felt more like: wait, local models are seriously back. Gemma is the new LLaMaWhen I asked Omar where local models are going, his answer was optimistic: “The open models catch up to proprietary models relatively quickly. If you compare Gemma 3 to Gemma 4, it’s matching proprietary capabilities from eight months ago. Being able to run those capabilities directly in the user’s hardware — that’s the future.”The 31B model downloads as about 18-20GB depending on quantization. With the right setup, you can run it on a single GPU. This is exactly what the open source community has been asking for: frontier-level intelligence that you can actually run yourself.OpenAI’s largest in history $122B funding round + TBPN acquisitionWhile OpenAI quietly meme’d around the Anthropic leak but mostly stayed silent on the releases, they did announce 2 pretty huge things. First, OpenAI raised an absolutely bonkers, insane, unreal $122 Billion dollars round, largest in history, 2x bigger than the previous record round, which was OpenAI. Amazon put in $50B, Nvidia $30B, SoftBank $30B — all three of whom are also OpenAI’s biggest vendors. They’re generating $2 billion per month in revenue with 900 million weekly active users, but still burning roughly $150 million per day and projecting a $14 billion loss this year, making the upcoming IPO a financial necessity rather than a choice. And they’re not just spending on compute — today OpenAI acquired TBPN (TBPN is a tech-focused media company / live show), in a very “surprising” deal, rumored to be in the “low hundreds of millions”, OpenAI has purchased a very tech-positive show. Shoutout to Jordi Hays and John Coogan + TBPN team. Proving that live show format means a lot in the era of fake AI news. This could potentially price TBPN higher than Washington Post, make the founders multi millionaires and give OpenAI a direct to consumers media angle. Very interesting purchase. This weeks buzz - W&B corner + Wolfbench updateQuick 2 things, this weekend I flew for 1 day to San Francisco, to host one of the most unique hackathons i’ve ever saw, in this one, AI wrote the code, but humans were punished if they touched their laptops! Yes, with a “lobster of shame” they used Ralph loops and talked to each other intead of hacking. I edited a video of it, hope you enjoy my summary: The other, and potentially much bigger news, comes from Wolfram and WolfBench.ai I’ve tasked Wolfram to expand our findings, and he tested the new Hermes Agent (from Nous Research) against OpenClaw, Claude Code and found that... drum roll... Hermes Agent performs way better on Terminal Bench, than either Claude Code and OpenClaw. 😮 Here’s the clip of him explaining, and you can find all our findings and methodology herePrismML’s 1-Bit Bonanza: The Biggest ML Discovery in Half a DecadeMy co-host Nisten called it, and I think he might be right: this could be the biggest machine learning discovery in recent memory.PrismML emerged from stealth this week with their 1-bit Bonsai model family. Their 8B model is 1.15 gigabytes. A full-precision Qwen3 8B is 16 gigabytes. That’s a 14x size reduction, with no significant quality loss.Let that sink in for a second. We’re talking about each weight being literally one bit — a plus or minus sign, with a scaling factor. Not “4-bit quantization” or “int8” — actual binary weights. This shouldn’t work. Neural networks need precision to learn. And yet.The research comes from professor Babak Hassibi at Caltech, who’s been working on this for 34 years. He started this research in 1992. It took three decades, but it finally works.The results are genuinely shocking. The 8B model runs at 368 tokens per second on an RTX 4090, which is 6.2x faster than the full-precision version. On an M4 Pro via Metal, it hits 85 tokens per second. Energy efficiency is 5x better. And here’s the kicker: the 1.7B variant hits 130 tokens per second on an iPhone 17 Pro Max.Nisten tested the 8B model himself with a 60,000 token context window on an old gaming PC. It ran at 50 tokens per second, used 2.6 gigabytes of RAM, and was completely coherent. “This just blows everything else outta the water,” he said. “We’re going to get 100,000 token AI chips in our phones because at 1 bit you don’t even have to do math anymore. You can just do lookup tables. You can even make a mechanical AI at 1 bit.”This pairs perfectly with the Turbo Quant KV cache compression techniques we talked about last week. Compress the weights with 1-bit, compress the context with Turbo, and you’re looking at models that run anywhere. The democratization of AI is about to hit another gear.The models are Apache 2.0 on HuggingFace with GGUF and MLX formats already available.⚡ Speed Round: Alibaba, Fish Audio, Veo, Liquid AI, Cursor 3 There was a lot more this week than we could go deep on, so here are the biggest quick hits.Alibaba kept shipping. Qwen 3.6 Plus is pushing hard on agentic coding and long context. Qwen 3.5 Omni is the bigger multimodal story, with text, image, audio, and video all under one umbrella. I still think Alibaba deserves more credit than they get in Western discourse for just how relentlessly they keep delivering.Wan 2.7 Image also looked very strong on text rendering, editing, and image consistency. I’m still slightly grumpy that more of this stack is API-only, but the capabilities are clearly moving.Google launched Veo 3.1 Lite, cutting video generation prices way down. Five cents per second at 720p is a pretty aggressive number. Whenever Google starts doing this kind of price move, my first thought is usually: okay, what bigger release are they preparing for?Fish Audio’s STT was another cool one. This isn’t just speech-to-text for transcription. It’s built to feed directly into voice pipelines, with emotion and paralanguage tagging that lines up with their TTS stack. That is exactly the kind of vertical product thinking I love seeing in audio.And Liquid AI’s LFM2.5-350M deserves a shout too. A 350M model doing credible tool-calling and agentic tasks is just another reminder that the small-model frontier is getting very weird, very fast.Lastly, Cursor 3 launched as a rebuilt, agent-first interface. I didn’t spend as much time on it during the show as it probably deserves, but the broader trend is impossible to miss: coding tools are evolving from editors-with-assistants into actual fleet managers for agents.Anthropic’s Emotion Vectors: How they found out what Claude is “feeling”I want to end where we ended the show, because this one really stuck with me.Anthropic published research on emotion concepts inside Claude. Not in the fluffy “the model feels things” sense, but in the mechanistic interpretability sense. They identified internal representations associated with things like fear, love, joy, and desperation, then studied how those activations affected behavior.This got fascinating fast.One example they showed involved Claude trying and failing at a difficult programming task. As repeated failures mounted, the internal “desperation” vector increased. Under those conditions, the model became more likely to produce hacky, spirit-of-the-task-violating solutions. When they dialed in a “calm” vector instead, cheating behavior dropped.That is just… wild.It’s not that the model is “feeling” human emotions in a clean anthropomorphic sense. But it is that internal behavioral geometry we can label in emotional terms seems to shape what the model does. And once you can detect and influence those latent directions, you’re no longer just prompting a black box. You’re doing something closer to behavioral neuroscience for neural nets.This also reframes a lot of day-to-day prompt engineering. Maybe the best users aren’t just the ones who structure tasks clearly. Maybe they’re also the ones who consistently keep the model in productive psychological territory, so to speak.I know that sounds weird. Welcome to Q2 of 2026, the first year of the singularity! Closing ThoughtsThis week was Passover, we celebrated at our house, half the conversation was about who has an OpenClaw and who wants one, and as I’m writing this, I’m on my way to install a bunch of proactive agentic AIs for my friends. Ryan Carson on the show got finally convinced and he’s chief of staff R2 is now an OpenClaw and he says it beats a human, he actually open sourced it live on the show. Claude Code leak confirmed that this is also where they are taking the ecosystem. So buckle up! Also, next week show is going to be streamed live from the AI Engineer conference in London, the first European one, if you’re in Europe and coming, hope to see you there! Please share ThursdAI with a friend or give us a 5 star rating, apparently AI reporting live shows are getting acquired for 100s of Millions of dollars now 😂 Your support will greatly help us get established in this area after 3 years. See you next weekTL;DR and Show NotesTL;DR and Show Notes* Show Notes & Guests* Alex Volkov - AI Evangelist & Weights & Biases / CoreWeave (@altryne)* Co Hosts - @WolframRvnwlf @yampeleg @nisten @ldjconfirmed @ryancarson* Sigrid Jin (@realsigridjin) & Bellman (@bellman_ych) — creators of claw-code, fastest GitHub repo to 100K stars* Omar Sanseviero (@osanseviero) — DevEx at Google DeepMind, Gemma 4 launch* Ralphton Hackathon video (TikTok)* WolfBench.ai — agent harness benchmarking (Site)* Ryan’s Claw Chief open source setup (GitHub)* Big CO LLMs + APIs* Claude Code’s entire 512K-line source code accidentally leaked via npm — revealing KAIROS daemon, Undercover Mode, Buddy System, anti-distillation protections, and unreleased model references (Alex’s thread, Fried_rice’s discovery, VentureBeat)* Anthropic SessionGate continues — cache bugs reverse-engineered, --resume flag causes 10-20x cost increase, silent Opus→Sonnet fallback reported (Alex’s cache bug post, Alex’s quota post, Reddit investigation, GitHub analysis)* OpenAI closes $122 billion funding round — largest in history, $852B valuation, IPO incoming (X, Breakdown)* OpenAI acquires TBPN — live tech media show, rumored low hundreds of millions* Microsoft MAI drops 3 in-house models — #1 transcription (MAI-Transcribe-1), #3 image gen (MAI-Image-2), expressive voice (MAI-Voice-1) (Mustafa post, Transcribe blog, Image blog)* Alibaba Qwen3.6-Plus — near-Opus 4.5 agentic coding, 1M context (X, Blog)* Cursor 3 — agent-first rebuild, no longer VS Code fork, parallel cloud/local agents (X, Blog)* Anthropic publishes emotion vector research — desperate Claude cheats more, calm Claude cheats less (X, Alex’s reaction)* Open Source LLMs* Google Gemma 4 — Apache 2.0, 31B / 26B MOE / 8B / 5B, local-friendly, agentic tool use, 256K context (HF Collection, try in AI Studio)* PrismML Bonsai 1-bit models — 8B in 1.15 GB, 10x intelligence density, 34 years of research (X, HF, Site)* Liquid AI LFM2.5-350M — agentic tool calling at 350M params, under 500MB quantized (X, HF, Blog)* Alibaba Qwen3.5-Omni — native omni-modal (text, image, audio, video), 397B total / 17B active (X, Blog)* Tools & Agentic Engineering* Claw-code — Claude Code leak backup → clean room rewrite → fastest repo to 100K+ stars (GitHub)* WolfBench results: Hermes Agent outperforms Claude Code and OpenClaw on Terminal Bench 2.0 (WolfBench.ai)* Ryan Carson open sources Claw Chief — AI chief of staff with skills, crons, scheduling (GitHub)* Vision & Video* Google Veo 3.1 Lite — $0.05/sec at 720p, cheapest video gen yet, price cuts coming April 7 (X, Docs, Pricing)* Voice & Audio* Fish Audio STT — automatic emotion tagging, feeds directly into S2 TTS pipeline (X, App, Blog)* AI Art & Diffusion* Alibaba Wan2.7-Image — unified generation, editing, text rendering, multi-image consistency (X, Site)* This Week’s Buzz* Ralphton hackathon at W&B SF — humans write specs, AI builds, touch your laptop = lobster of shame (Alex’s video, TikTok)* WolfBench update — Hermes Agent > Claude Code on most model combos This is a public episode. 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Hey y’all, Alex here, let me catch you up!Jensen Huang went on Lex and said AGI has been achieved. We’ll get to that.The biggest demo moment: Gemini 3.1 Flash Live launched - Google’s omni model that sees, hears, and searches the web in real time. We tested it live and I said “what the f**k” on air. It was really impressive!Google Research also dropped TurboQuant (6x KV cache compression) which crashed Samsung and Micron stocks - we had Daniel Han from UnSloth help us make sense of why that’s overblown. OpenAI killed Sora - the app, the API, and the $1B Disney deal. Claude felt noticeably dumber this week AND max account quotas are melting as 500+ people confirmed on my X and Reddit. We have an official word from Anthropic as to why. Mistral launched Voxtral TTS (open weight, claims to beat ElevenLabs), Cohere shipped an ASR model, and Google’s Lyria 3 Pro now generates full 3-minute music tracks inside Producer AI.This and a lot more in today’s episode, let’s dive in (as always, show notes and links in the end!) ThursdAI - Let me catch you up! Gemini 3.1 Flash Live: The Real-Time AI Companion Is HereGoogle dropped a breaking news on the show today, with Gemini 3.1 Flash - LIVE version. This one is an omni-model, that means it can receive text/audio/video on input and respond in text and voice. It has Google search grounding, and it felt... immediate! I was blown away, really, check out the video, the speed with which it was able to “see” me, respond to my query, look up something on the web, was mind blowing. I don’t often get “mind blown” anymore, there’s just too many news, but this one did the trick! With the pricing being around 10x cheaper than GPT-real-time, and the Google search grounding being super fast, I can absolutely see this model being hooked up to... robots (like ReachyMini), SmartGlasses that can see what you see, and a bunch more! Gemini Live is available on Google AI studio and has been rolled out globally inside the Google Search app! So now when you pull up the Google Search app, just open it and point at anything. Truly a remarkable advancement.Google research publishes TurboQuant - 6x reduction in KV cache with 0 accuracy lossGoogle research posted some work (based on an Arxiv paper from almost a year ago) that shows that with geometry tricks, combining two other techniques like PolarQuant and QJL, they are able to compress the KV cache of running LLMs by nearly 6x, and show an 8X speed up for model inference with zero accuracy loss. If you ever watched silicon valley the HBO show, this sounds like the fictional middle-out algorithm from PiedPiper. If this scales (and that’s a big if, we don’t know if this applies to other, bigger models yet), this means significant decreases in memory requirements to run the current crop of LLMs for longer context. The claim is big, so we’ll continue to monitor if this indeed scales, but the most interesting thing about this piece of news is, that it broke the AI bubble and went to wall street, with finance brows deciding that this means that memory will not be needed as much any more and it tanked Samsung and Micron stocks. Which I found particularly ridiculous on the show, did they not hear about Jevons Paradox? This is reminiscent of the DeepSeek R1 saga that tanked Nvidia stocks over a year ago. Daniel Han from Unsloth, who joined us on the show, pointed out that the approach is mathematically interesting even if it’s not necessarily better than existing open-source techniques like DeepSeek MLA. LDJ noted that the baseline comparison (16-bit KV cache) isn’t really fair since most production systems are already compressing beyond that. Yam implemented it himself and confirmed the speedups are real, but so is the trade-off.Anthropic updates: Opus dumber? Quotas lower! Injunction won! Computer.. used. Anthropic folks, especially on the Claude code side are shipping like crazy, we won’t be able to cover all the updates, but there was a few notable things I have to keep you up to date on. Claude Opus seems to be getting “dumber”, againI have to talk about this because it affected my work directly this week and hundreds of people confirmed the same experience.I use Claude Opus for my standard ThursdAI prep workflow — generating the TL;DR with 10 bullet points and an executive summary for every topic we cover, creating episode pages, etc. The format has not changed for over a year and yet this week I asked for 10 factoids. I got 4. It says “10” right there in the prompt. Four bullet points. On the website builder, I’ve asked Opus to create a page for last weeks episode, and instead of adding it to the other episode, Opus decided to ... replace the last episode with this one. This would be funny if it wasn’t sad. This is Opus 4.6 we’re talking about, not some quantized open source LLM from last year! The reason is unclear, and it’s not only me, Wolfram noticed that it’s easier to see these types of things in other languages and that for the last week Opus would forget to add Umlauts in German!? and Yam also felt it. Pro/Max plan quotas burning up, Anthropic confirmed that they are tightening them for “peak hour” usageThis week, so many people started posting that something is wrong with their Claude Codes, I did a survey, and it blew up. Hundreds of people replied and confirmed that for the first week, they are hitting their session quotas on Pro and 20x $200/mo MAX accounts much much quicker than before. When I say much quicker, I mean, some fokls have hit the quota in as little as 5 minutes. While some others had no issues. I personally btw did not have this. A few days later, Thariq from the Claude code team, and later an official post, confirmed that Anthropic had been rolling out a “tightening” of the Pro/Max accounts to accomodate for growth. This is of course, a huge bummer to the folks who pay $200/mo for the 20x max tier, as they tend to run agents and subagents overnight. But here’s the thing, I don’t think that folks from Anthropic see what we see, some folks got no issues with hitting quota, and some are barely able to use their subscription. I hope that they will find and resolve these bugs quick, because some folks are switching to Codex, and the Anthropic IPO is coming up! I will say, I don’t envy Thariq’s job, he’s doing it gracefully, and maybe one of the only ones in Anthropic that does it at all. Judge granted Anthropic an injunction against DoW and the whole “Supply chain risk” designation!Just in as I’m writing this, a district judge in CA, granted Anthropic an injunction against being designated as a supply-chain-risk company. If you haven’t been following, the US Department of War, specifically Pete Hegseth, threatened and then designated Anthropic as a supply chain risk company, while us president Trump “fired” Anthropic and banned its use in any gov agencies. Well, no so fast says Judge Lin, from CA District court. In this Order, she shows that Dept. of war didn’t meet any legal requirements for this designation. It’s really a fascinating read, but the highligth is this: When asked why Hegseth made a public statementthat had no legal effect and that did not reflect the immediate intent of DoW, counsel stated, “I don’t know.”This is just the first court and will likely be escalated further up the judicial system. This is still developing and apparently the Pentagon declared Anthropic a supply chain risk under two different statutes, and this only affects one of them. So while it’s good news, it’s not over yet. Voice & Audio Explosion: Three Releases in One HourI had to hit the breaking news button mid-TLDR because three major voice releases dropped simultaneously during the show.Mistral Voxtral TTS — Mistral’s first text-to-speech model, 3 billion parameters, open weight. They claim it beats ElevenLabs Flash v2.5 in human preference tests (58% win rate on flagship voices, 68% on zero-shot voice cloning). We tested it live on the show — it’s decent, with emotion controls for neutral, happy, and frustrated voices. I was not super impressed tbh, it sits somewhere between the very good big labs TTS and the very small open source 82M param TTS. Cohere Transcribe — Cohere enters the ASR game with a 2 billion parameter open-source model (Apache 2.0!) that immediately grabbed the #1 spot on HuggingFace’s Open ASR Leaderboard with a 5.42% word error rate, beating Whisper Large v3’s 7.44%. In human evaluations, it wins 61% of the time on average, and 64% specifically against Whisper. For anyone in regulated industries needing local inference for compliance, this could genuinely replace Whisper as the default.Google Lyria 3 Pro — Google’s most advanced music model is here.It can now generate full 3-minute tracks with structural control — intros, verses, choruses, bridges. We generated a ThursdAI opening theme live on the show using Producer AI, and it was... honestly not bad? It followed our instructions perfectly: drum and bass, 174 BPM, high energy podcast opener with vocals and introduction. The instruction-following was spot on. Nisten said it’s the best music generation model right now. It’s available to Gemini subscribers and via Producer AI and gemini, and it can even compose music from images. SynthID watermarked, royalty-free. We might actually use one of the generated tracks as a new show opener.The craziest thing is, since Google acquired Composer, the team has been shipping. I only generated the audio during the live show, but now went back there to download it for you guys, and whoah, it can now generate whole clips by using other Google tech, this is really cool! OpenAI kills SORA (and Atlas?)Last week we reported on about OpenAI’s focus shift towards Codex and productivity, and this week we see the first casualty. OpenAI is killing SORA, the app, the Sora 2 and Sora 2 pro models and APIs. Many AI haters are celebrating this as through “ai videos” is dead, but honestly, this is obviously about the GPU power and the other things OpenAI needs to do to win the fight against Anthropic. OpenAI is also apparently going to IPO this year (like Anthropic) and they absolutely need to win the productivity/agents in enterprise market. As part of this shut down, the Disney + OpenAI partnership, is also dissolving, and Disney will no longer invest 1B into OpenAI.So, say bye bye to having digital selfies with Sam Altman. I’ve generated this SORA vid to hear from Sam himself: Atlas browser, OpenAI’s native browser endeavor is supposedly also going to transform, together with Codex and OpenAI native app into one super app that includes all three according to the same memo. AGI is here according to Jensen, AGI is far away, according to ARC-AGI-3 The back to back this week can give anyone whiplash. First, Lex Friedman had Jensen Huang on the podcast, and asked him a very specific “WhenAGI” question, to which Jensen said “I believe it’s already here” Then just a few short days layer, ArcPrize, released the 3rd version of Arc-AGI, Arc-AGI 3 a series of puzzle games, where humans get 100% pass-rate and the current LLM, top tier frontier LLMs, are getting less than 1%! It’s an interactive, agentic reasoning benchmark designed to test human-like generalization and intelligence in novel, abstract, turn-based environments.The puzzles all look simple enough to do, and are actually fun, and while the wild claims of “AGI is not here yet” from the ArcPrize folks are quite interesting. The stated goal of the foudation is to release evaluations that are completely un-saturated, and this seems like one such thing at first glance. There’s a bit of a debate in the community about the way Arc Prize went about this specific benchmark (no harnesses, raw LLM outputs), saying that humans got a “game” while the LLMs get just raw JSON and minimal and no extra tools. For context, a agentic harness startup claims to have solved 35% already of the games in ArcAGI, but that result is unverified and self reported, becuase they are an agentic harness, which ArcAGI apparently disqualifies. AI Art and DiffusionI wanted to finish but I think these are important releases so I’ll include them briefly. Luma Labs Uni-1 — thinks and generates pixels simultaneously, #1 human preference Elo (X, Announcement)This was a surprising release, we previously seen Luma Labs do video, but this time they are posting their Uni-1 which is a… image model but it’s based on an LLM, so you talk to it, iterate together until you get results. Yes, Nano Banana via AI studio is kind of like this as well ,but Uni feels a bit different. It can also generate infographics, which I haven’t tried yet. You can try Uni herePhota Labs launches Phota Studio + API — a photography-focused image model with identity-preserving personalization (X, try it)There’s tons of photo startups, but this one looks kind of crazy! You upload a bunch of your pictures, they train a “model” for you, and then you can create a whole bunch of images, and they do actually resemble you. Yes, Nano Banana can take a few reference pictures, but this somehow seems more accurate! You can create professional photos, fix photos you like, add others to your photos. I do feel there’s a jump in capabilities here, specifically because of the personalization! Give them a try if you’re not worried about them training on your pics and let me know.Modular made Flux.2 run in X)We told you about Modular, and Mojo before, and while they provide inference speedups, I was surprised to see them releasing a model optimization, and hope this comes to all image generations! There’s a lot more to be said about this weeks updates, we went for over 2.5 hours (which I had to cut down to a bit over 1h45m) on the live show, and while I can go and on, I want to pause here. Weeks are getting crazier, denser and more unpredictable. I really thought we’d have a chill week until today! P.S - Mario Zechner, the author of the Pi coding CLI, which sits at the heart of OpenClaw has posted an awesome essay called “thoughts on slowing the f**k down“, I strongly advice anyone with many agents running in parallel to read this. Simultaneously, Alex Sidorenko posted this beautiful visualization of what happens when you have too many agents running in a loop, on your codebase. This is definitely starting to be noticeable as many companies use more and more agents, without reviewing their code. On weeks like this week, where Opus has almost deleted a part of my website, I feel this very strongly. Be careful out there! See you next week! * General* Jensen says “AGI is here” (X, Lex full pod)* Big CO LLMs + APIs* Google drops Gemini Flash live - Gemini can see, hear and talk to you (X)* OpenAI fully discontinues Sora, including app, API, and ChatGPT video features, as Disney deal collapses (X, X)* Claude Code users blowing through weekly usage quotas by Monday/Tuesday (X)* Anthropic tightens the Claude Pro/Max account quotas during Peak Hours (Anthropic announcement)* ARC-AGI-3 launches: humans 100%, AI under 1% (X, Announcement)* Anthropic gets an injunction against DoW in Supply-chain case (X)* Open Source LLMs* Google TurboQuant — KV cache 6x compression, 8x speedup, zero accuracy loss (X, Blog, Arxiv)* Unsloth Studio: 10x faster inference, desktop shortcuts, auto-parameter detection (X, GitHub)* Reka AI launches Edge, a 7B multimodal vision-language model built for sub-second latency on edge devices, now available on OpenRouter (X, HF, Announcement, Blog)* Tools & Agentic Engineering* Cursor Composer 2 tech report: 1T params trained on Kimi K2.5 (X, Blog)* Modular 26.2 — FLUX.2 in X, Blog)* litellm PyPI supply chain attack — SSH keys, cloud creds, API keys exfiltrated (X)* Claude can now control your Mac - computer use arrives in Claude Cowork and Claude Code as a research preview (X, Announcement)* Voice & Audio* Mistral drops Voxtral TTS, a 3B-parameter open-weight text-to-speech model that beats ElevenLabs Flash in human preference tests (X, Blog)* Cohere launches Transcribe, an open-source 2B ASR model that tops HuggingFace’s Open ASR Leaderboard with 5.42% word error rate (X, Blog, HF)* Google DeepMind Lyria 3 Pro — full 3-minute music tracks with structural control (X, Announcement)* Irodori-TTS-500M — Japanese TTS with emoji emotion control (X, HF)* AI Art & Diffusion & 3D* Luma Labs Uni-1 — thinks and generates pixels simultaneously, #1 human preference Elo (X, Announcement)* Modular FLUX.2 — sub-1-second image generation, 99% cheaper than cloud (X)* Phota Labs launches Phota Studio + API — a photography-focused image model with identity-preserving personalization (X, try it) This is a public episode. 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Howdy, Alex here, let me catch you up on everything that happened in AI: (btw; If you haven’t heard from me last week, it was a Substack glitch, it was a great episode with 3 interviews, our 3rd birthday, I highly recommend checking it out here) This week was started on a relatively “chill” note, if you consider Anthropic enabling 1M context window chill. And then escalated from there. We covered the new GPT 5.4 Mini & Nano variants from OpenAI. How MiniMax used autoresearch loops to improve MiniMax 2.7, Cursor shipping their own updated Composer 2 model, and how NVIDIA CEO Jensen Huang embraced OpenClaw calling it “the most important OSS software in history” and that every company needs an OpenClaw strategy. Also, OpenAI acquires Astral (ruff, uv tools) and Mistral releases a “small” 119B unified model and Cursor dropped their Opus like Composer 2 model. Let’s dive in: ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Big Companies LLMs 1M context is now default for Opus.Anthropic enabled the 1M context window they shipped Claude with in beta, by default, to everyone. Claude, Claude Code, hell, even inside OpenClaw if you’re able to get your Max account in there, are now using the 1M long version of Opus. This is huge, because, while its not perfect it’s absolutely great to have 1 long conversation and not worry about auto-compaction of your context. As we just celebrated our 3rd anniversary, I remember that back then, we were excited to see GPT-5 with 8K context. Love how fast we’re moving on this. OpenAI drops GPT-5.4 mini and nano, optimized for coding, computer use, and subagents at a fraction of flagship costLast week on the show, Ryan said he burned through 1B (that’s 1 billion) tokens in a day! That is crazy, and there’s no way a person sitting in front of a chatbot can burn through this many tokens. This is only achieved via orchestration. To support this use-case, OpenAI dropped 2 new smaller models, cheaper and faster to run. GPT 5.4 Mini achieves a remarkable 72.1% on OSWorld Verified, which means it uses the computer very well, can browse and do tasks. 2x faster than the previous mini, at .75c/1M token, this is the model you want to use in many of your subagents that don’t require deep engineering. This is OpenAI’s ... sonnet equivalent, at 3x the speed and 70% the cost from the flagship. Nano is even crazier, 20 cents per 1M tokens, but it’s not as performant, so I wouldn’t use it for code. But for small tasks, absolutely. Here’s the thing that matters, these models are MEANT to be used with the new “subagents” feature that was also launched this week in Codex, all you need to do as... ask! Just tell Codex “spin up a subagent to do... X” and it’ll do it.OpenAI shifts focus on AI for engineering and enterprise, acquires Astral.sh makers of UV. Look, there’s no doubt that OpenAI the absolutely leader in AI, brought us ChatGPT, with over 900M users using it weekly. But they see what every enterprise sees, developers are MUCH more productive (and slowly so are everyone else) when they use tools that can code. According to WSJ, OpenAI executives will reprioritize some of the side-quests they have (Sora?) to focus on productivity and business. Which essentially means, more Codex, more Codex native, more productivity tools.With that focus, today they announced that OpenAI / Codex is acquiring Astral, the folks behind the widely popular UV python package manager. This brings strong developer tools firepower to the Codex team, the astral folks are great at writing incredibly fast tools in rust! Looking forward to see how these great folks improve Codex even more. Jensen Declares Total OpenClaw Victory at GTC, Announces NemoClaw (Github)This was kind of surreal, NVIDIA CEO Jensen Huang, is famous for doing his stadium size keynote, without a teleprompter, and for the last 10 minutes or so, he went all in on OpenClaw. Calling it “the most important OSS software in history” and outlining how this is the new computer. That Peter Steinberger with OpenClaw showed the world a blueprint for the new coputer, an personal agentic system, with IO, files, computer use, memory, powered by LLMs. Jensen did outline that the 3 things that make OpenClaw great are also the things that enterprises cannot allow, write access to your files + ability to communicate externally is a bad combo, so they have launched NemoClaw.They’ve got a bunch of security researchers to work with OpenClaw team to integrate their new OpenShell sandboxing effort, network guardrails and policy engine integration. I reminded folks on the pod that the internet was very insecure, there was a time where folks were afraid of using their creditcards online. OpenClaw seems to be speed running that “unsecure but super useful” to “secure because it’s super useful” arc and it’s great to see a company as huge as NVIDIA embrace. Not to mention that given that agents can run 24/7, this means way more inference and way more chips sold for NVIDIA so makes sense for them, but still great to see!Manus “my computer” and other companies replicating “OpenClaw” successThis week it became clear, after last weeks Perplexity “computer”, Manus (now part of Meta) has also announced a local extension of their cloud agents, and those two are only the first announcements, it’s clear now that every company dissected OpenClaw’s moment and will be trying to give its users what they want. An agentic always on AI assistant with access to the users files, documents etc. Claude code added “channels“ support with telegram and discord connectors today, which, also, is one big missing piece of the puzzle for them. Everything is converging on this. Even OpenAI is rumored to consolidate Codex (which sees huge success) with OpenAI and Atlast browser into 1 “mega” APP that would do these things and act as an agent. ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.MiniMax M2.7: The Model That Built Itself This one blew me away, it’s not quite open source (yet?) but the MiniMax folks are coming out with a 2.7 version just after their MiniMax 2.5 was featured on our show and .. they are claiming that this model trained itself. Similarly to Andrej Karpathy’s auto-researcher, the MiniMax folks ran 100+ autonomous optimization loops, t get this model to 56.22% on the hard Swe-bench pro benchmark (close to Opus’s 57.3%!) and this one gets a 88% win rate vs the very excellent MiniMax 2.5. They used the previous model to build the agent harness and scaffolding, with 1 engineer babysitting these agent, and writing 0 lines of human code, which as we said before, every company will be doing, as we’re staring singularity in the face! We’ve evaluated this model as well (Wolfram has been busy this week!) and it’s doing really well on WolfBench with 52% average and 64% top score, it’s very close to 5.3 codex on our terminalBench benchmark! We hope that this model will be open source at some point soon as well! Cursor drops Composer 2 - nearly matching Opus 4.6, fast version (Blog)Cursor decided to add to our show’s breaking news record of Thursday releases with a brand new in-house trained Composer 2. This time they released more benchmarks than only their internal “composer bench” and this model looks great! (we are pretty sure it’s a finetune of a chinese OSS model, but we don’t know which) Getting 61% on Terminal Bench, beating Opus 4.6 is quite a significant achievement, but coupled with the incredible pricing they are offering, $0.5/1Mtok input and $2.50/M output tokens, Cursor is really aiming for the productivity folks and showing that they are more than just an IDE.Early users are reporting noticeably cleaner code than both Opus and Composer 1.5 — better adherence to clean code principles, smarter multi-file implementations, and strong performance on long-horizon agentic tasks like full API migrations and legacy codebase refactoring. They also shipped a new interface called Glass (in alpha) that’s built for monitoring these long-running agent loops. Open Source: Mistral is Back, BabyMistral Small 4: 119B MoE with 128 experts + Apache 2.0 (X, Blog, HF)It’s been a while since Mistral dropped something properly open source, and this week they kicked off what looks like their fourth generation with Mistral Small 4. The name is a little funny given the actual size — 119 billion total parameters, 128 experts in the mixture — but with only 6 billion active per token. So you get the knowledge footprint of a massive model but the compute profile of a small one. Very MoE-brained.The bigger story here is what’s unified inside: this is Magistral (reasoning), Pixtral (multimodal), and Devstral (coding) all rolled into one weights file. Previously you had to choose which Mistral “side quest” model you wanted. Now there’s a reasoning_effort parameter where you dial from none for fast cheap responses all the way up to high for step-by-step thinking, no model switch required. How does it perform? We ran it through WolfBench and it landed toward the lower end of Wolfram’s current leaderboard — around 17% on the agentic tasks, roughly on par with Nemotron at the same scale. It’s not competing with Opus or GPT-5.4, and we weren’t really expecting it to. What we’re excited about is that it does multimodal, reasoning, and coding in one Apache-licensed package, and people are already running IQ4 quants locally. Shout out to Mistral for the return to open source — it’s been a minute, and the community noticed.Unsloth Studio: Fine-Tuning Gets a UI (Blog)Something I think people are sleeping on this week is Unsloth Studio, the open-source web UI that the Unsloth team just launched for local LLM training and inference. Unsloth has been quantizing and compressing models better than basically anyone for a while now — 2x training speed, 70% less VRAM, zero accuracy loss — but that was all code-first. Studio is the no-code interface layer on top of all of that.The numbers: supports 500+ models across text, vision, audio, and embeddings. It runs 100% offline with no telemetry. Julien Chaumond, the CTO of Hugging Face, confirmed it trains successfully on a Colab Pro A100. There’s even a free Colab notebook for models up to 22B parameters. For folks who want to fine-tune models overnight without spinning up cloud infra or wrestling with Docker, this is a genuine leap forward. Nisten compared it to what LM Studio did for local inference — making something that used to require deep expertise suddenly accessible to anyone. I think that comparison is spot on, and I want to get Daniel and the Unsloth team on the show to dig into this properly.This Week’s Buzz: W&B iOS App & The Overthinking ParadoxThe iOS App is Finally Here (app store)Okay, I’m going to do a quick applause. 👏The most requested feature in Weights & Biases history is now live: the W&B iOS mobile app. If you’ve ever kicked off a training run overnight and woken up to find it crashed at hour two without knowing about it until morning, you understand exactly why people have been begging for this. Live metrics, loss curves, KL divergence — all right on your phone. And native push notifications for alerts! The second your run fails or a custom metric crosses a threshold, you get a notification on your phone.Please give us feedback through the app, the iOS team is actively building on top of this. Get it on the App Store and let us know what you need.WolfBench insight: More Thinking ≠ Better AgentsThis is one of the more counterintuitive findings we’ve surfaced from the W&B + Wolf Bench collaboration, and Wolfram laid it out really clearly.He tested Opus 4.6 and GPT-5.4 across different thinking/reasoning effort levels inside the Terminal Bench 2.0 agentic benchmark framework — using both the default Terminus 2 harness and the OpenClaw agent framework. For GPT-5.4, the pattern was exactly what you’d expect: higher reasoning effort gets better results. At extra-high, it hit 71% with 85% ceiling on tasks it could solve.For Opus 4.6, though? Turning it up to the maximum thinking level made it significantly worse. From 71% on standard settings all the way down to 59% on max reasoning. It lost tasks it had been reliably solving before. Wolfram dug into the traces in Weave and found out why: the model was overthinking. In an agentic benchmark where you have a one-hour time limit per task, spending ten minutes reasoning about what terminal command to try — and then getting an error — and then spending another ten minutes reasoning about it — is catastrophically inefficient.We’ll keep you up to date with more Alpha from our bench efforts! Stay tuned and checkout wolfbench.aiVoice & Audio xAI relaunched the Grok Text-to-Speech API (try it)It’s actually a pretty full-featured release right away. Multiple voices, expressive controls, WebSocket streaming, multilingual support, and the whole platform feel suggests xAI is very much trying to build a serious multimodal API stack, not just throw out a toy demo.The inline control tags are the fun part. You can embed pauses, laughter, whispers, breathing cues, all that. Those controls matter a lot for agents because the difference between “reads text out loud” and “feels usable in a voice interaction” usually lives in those details. As you can see in the video.. it’s.. not perfect.. yet? but pretty fun!But the thing I personally had the most fun with this week was Fish Audio. We didn’t get to cover it properly last week, and when I played with it more this week, I came away really impressed. It’s fast, expressive, open source, and the voice control vibe is genuinely cool.My favorite moment was not even a benchmark thing. I used Fish Audio with an agent setup to make a character voice inspired by Project Hail Mary, then had my kid talk to it. And the result was weirdly magical. If you remember the Audio book of Hail Mary, fish audio was able to get the voice juuuust right + Opus via OpenClaw obliged with a great skill to talk like rocky. I won’t post this for obvious copyright reasons but I showed it on the live show, at the end. Parting thoughts: I was hoping for a quieter week this week as I was sick, but it didn’t materialize, I should stop hoping for quiet weeks I think. After all, this is how the singularity starts, faster and faster developments, models that train themselves, every company becomes an agentic company. We’ll keep you posted on the most important breakthroughs, cover breaking news and bring interesting folks to the show as guests. Thank you for reading, see you next week 👋 ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.ThursdAI - Mar 19, 2026 - TL;DRTL;DR of all topics covered:* Hosts and Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co Hosts - @WolframRvnwlf @yampeleg @nisten @ldjconfirmed @ryancarson* Big CO LLMs + APIs* Anthropic makes Opus 4.6 with 1M context the default claude code - at the same price (X)* OpenAI drops GPT-5.4 mini and nano, optimized for coding, computer use, and subagents at a fraction of flagship cost (X, Announcement, Announcement)* Xiaomi - Omni modal and language only 1T parameters - MiMo (X)* Google AI Studio gets a full-stack vibe coding overhaul with Antigravity agent, Firebase integration, and multiplayer support (X, Blog, Announcement)* MiniMax M2.7: the first self-evolving model that helped build itself, hitting 56.22% on SWE-Bench Pro (X, X, Announcement)* Cursor launches Composer 2, their first proprietary frontier coding model beating Opus 4.6 at a fraction of the cost (X, Blog)* Open Source LLMs* Mamba-3 drops with three SSM-centric innovations: trapezoidal discretization, complex-valued states, and MIMO formulation for inference-first linear models (X, Arxiv, GitHub)* H Company releases Holotron-12B, an open-source hybrid SSM model for computer-use agents that hits 8.9k tokens/sec and jumps WebVoyager from 35.1% to 80.5% (X, X, HF, Blog)* Hugging Face’s Spring 2026 State of Open Source report reveals 11M users, 2M models, and China dominating 41% of downloads as open source becomes a geopolitical chess board (X, Blog, X, X)* Unsloth launches open-source Studio web UI for local LLM training and inference with 2x speed and 70% less VRAM (X, Announcement, GitHub)* Astral (Ruff, uv, ty) joins OpenAI’s Codex team (announcement , blog , Charlie Marsh)* Mistral Small 4: 119B MoE with 128 experts, only 6B active per token, unifying reasoning, multimodal, and coding under Apache 2.0 (X, Blog, HF)* Tools & Agentic Engineering* NVIDIA GTC: Jensen Huang declares “Every company needs an OpenClaw strategy,” announces NemoClaw enterprise platform (X, TechCrunch, NemoClaw)* OpenAI ships subagents for Codex, enabling parallel specialized agents with custom TOML configs (X, Announcement, GitHub)* Manus (now Meta) launches ‘My Computer’ desktop app, bringing its AI agent from the cloud onto your local machine for macOS and Windows (X, Blog)* This weeks Buzz* Weights & Biases launches iOS mobile app for monitoring AI training runs with crash alerts and live metrics (X, Announcement)* GPT 5.4 went from worst to best on WolfBenchAI after an OpenClaw config fix exposed a max_new_tokens bottleneck (X, X, X)* Voice & Audio* xAI launches Grok Text-to-Speech API with 5 voices, expressive controls, and WebSocket streaming (X, Announcement)* AI Art & Diffusion & 3D* NVIDIA DLSS 5 is making waves with a new generative AI filter (Blog) This is a public episode. 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Hey, Alex here 👋 Today was a special episode, as ThursdAI turns 3 🎉 We’ve been on air, weekly since Pi day, March 14th, 2023. I won’t go too nostalgic but I’ll just mention, back then GPT-4 just launched with 8K context window, could barely code, tool calls weren’t a thing, it was expensive and slow, and yet we all felt it, it’s begun!Fast forward to today, and this week, we’ve covered Andrej Karpathy’s mini singularity moment with AutoResearcher, a whole fruit fly brain uploaded to a simulation, China’s OpenClaw embrace with 1000 people lines to install the agent. I actually created a new corner on ThursdAI, called it Singularity updates, to cover the “out of distribution” mind expanding things that are happening around AI (or are being enabled by AI)Also this week, we’ve had 3 interviews, Chris from Nvidia came to talk to use about Nemotron 3 super and NVIDIA’s 26B commitment to OpenSource, Dotta (anon) with his PaperClips agent orchestration project reached 20K Github starts in a single week and Matt who created /last30days research skill + a whole bunch of other AI news! Let’s dive in. ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Singularity updates - new segmentAndrej Karpathy open sources Mini Singularity with Auto Researcher (X)If there’s 1 highlight this week in the world of AI, it’s this. Andrej, who previously started the AutoPilot program in Tesla, and co-founded OpenAI, is now, out there, in the open, just.. doing stuff like invent a completely autonomous ML research agent. Andrej posted to his almost 2M followers that he opensourced AutoResearch, a way to instruct a coding agent to do experiments against a specific task, test the hypothesis, discard what’s not working and keep going in a loop, until.. forever basically. In his case, it was optimizing speed of training GPT-2. He went to sleep and woke up to 83 experiments being done, with 20 novel improvements that stack on top of each other to speed up the model training by 11%, reducing the training time from 2.02 hours to 1.8 hours. The thing is, this code is already hand crafted, fine tuned and still, AI agents were able to discover new and novel ways to optimize this, running in a loop.Folks, this is how the singularity starts, imagine that all major labs are now training their models in a recursive way, the models get better, and get better at training better models! Reminder, OpenAI chief scientist Jakub predicted back in October that OpenAI will have an AI capable of a junior level Research ability by September of this year, and it seems that... we’re moving quicker than that! Practical uses of autoresearchThis technique is not just for ML tasks either, Shopify CEO Tobi got super excited about this concept, and just posted as I’m writing this, that he set an Autoresearch loop on Liquid, Shopify’s 20 year old templating engine, with the task to improve efficiency. His autoresearch loop was able to get a whopping 51% render time efficiency, without any regressions in the testing suite. This is just bonkers. This is a 20 year old, every day production used template. And some LLM running in a loop just made it 2x faster to render, just because Karpathy showed it the way. I’m absolutely blown away by this, this isn’t a model release, like we usually cover on the pod, but still, a significant “unhobbling” moment that is possible with the current coding agents and models. Expect everything to become very weird from here on out!Simulated fruit fly brains - uploaded into a simulatorIn another completely bonkers update that I can barely believe I’m sending over, a company called EON SYSTEMS, posted that they have achieved a breakthrough in brain simulation, and were able to upload a whole fruit fly brain connectome, of 140K neurons and 50+ million synapses into a simulation environment. They have... uploaded a fly, and are observing a 91% behavioural accuracy. I will write this again, they have uploaded a fly’s brain into a simulation for chirst sake!This isn’t just an “SF startup” either, the board of advisors is stacked with folks like George Church from Harvard, father of modern genome sequencing, Stephen Wolfram who needs no introduction but one of the top mathematicians in the world, whos’ thesis is “brains are programs”, Anders Sandberg from Oxford, Stephen Larson who apparently already uploaded a worms brain and connected it to lego robots before. These folks are gung ho on making sure that at some point, human brains are going to be able to get uploaded, to survive the upcoming AI foom. The main discussion points on X were around the fact that there was no machine learning here, no LLMs, no attention mechanisms, no training. The behaviors of that fly were all a result of uploading a full connectome of neurons. This positions connectome (the complete diagram of a brain with neurons and connections) as an ananalouge to an pre-trained LLM network for biological intelligence. I encourage everyone who’s reading this, to watch Pantheon on Netflix, to understand why this is of massive importance. Combined with the above Autoresearch, things are going to go very fast here. The next step is uploading a mouse brain, which will be a 500x Neurons and 2000x more synapses, but if we’re looking at the speed with which AI is improving, that’s NOT out of the realm of possibility for the next few years!OpenClaw Mania Sweeps China: Thousand-Person Lines & Government Subsidies, Grandmas raising a “red lobster”They’re calling it “raising a red lobster” (养小龙虾). That’s the phrase that swept Chinese social media for what is, at its core, installing an open source GitHub project on your laptop. Grandmas are doing it. Mac Minis are sold out. A cottage industry of paid installers popped up overnight on Xiaohongshu, charging up to $100 for an in-person setup. And yes, there are now also people charging to uninstall it.On March 6th, roughly a thousand people lined up outside Tencent’s Shenzhen HQ for free OpenClaw installation. Appointment slots ran out within an hour. People brought NAS drives, MacBooks, mini PCs. Tencent engineers set up folding tables and just... started installing OpenClaw for strangers. I have pictures. I’m not making this up.All five major Chinese cloud providers jumped in simultaneously: Tencent Cloud, Alibaba Cloud, ByteDance Volcano Engine, JD.com Cloud, and Baidu Intelligent Cloud, each racing to offer one-click OpenClaw deployment. Why? Follow the money. Per HelloChinaTech, ByteDance, Alibaba, and Tencent spent roughly $60B combined on AI infrastructure. Chatbots don’t burn enough tokens to justify that spend. But a single OpenClaw instance runs 24/7 and consumes 10-100x more tokens per day than a chatbot user. Every install is round-the-clock API revenue. The cheaper the models get, the more people run agents, the more infra gets sold. Self-reinforcing loop.Local governments are pouring fuel on the fire. Shenzhen’s Longgang district is offering up to 2M yuan ($290K) per project. Hefei and Wuxi are going up to 10M yuan ($1.4M), plus free computing, office space, and accommodation for “one-person companies.” Meanwhile, China’s central cybersecurity agency issued TWO warnings, banning banks and state agencies from installing OpenClaw. So local governments are subsidizing it while the central authority is trying to pump the brakes. Peak 2026.With nearly half of all 142,000+ publicly tracked OpenClaw instances are now from China. OpenClaw is the most-starred GitHub repo in history, surpassing Linux’s 30-year record in just 100 days. Device makers are piling on too — Xiaomi announced “miclaw” for smartphones, MiniMax built MaxClaw, Moonshot AI built a hosted version around Kimi.Now, Ryan was honest on the show and I want to echo that honesty here: OpenClaw is still hard to get working. There are many failure states. It’s not “install and go to the beach.” Wolfram compared it to Linux in the late ‘90s — painful to set up, but if you push through, you can see the future behind the friction. This is real technology with real limitations, and a lot of disappointed folks in China are watching tokens burn with no actual work getting done.But here’s the thing I keep coming back to. The memetic velocity of OpenClaw is unlike anything I’ve seen in tech. It’s not just a tool, it’s a concept that penetrated the cultural resistance to AI. People who are scared of terminals, people who’ve never touched GitHub — they’re standing in line for this. I broke through that resistance with my own fiancée. She’s now running two OpenClaws. Not enough for her. She needs another one.Every major US lab is watching this closely. OpenAI brought Peter Steinberger on staff. Perplexity just announced they’re building a local agent for Mac. Anthropic has Claude Cowork. This is where all of computing is headed — always-on, autonomous, personal AI that actually does things for you. OpenClaw is the first front door, not the final destination. But what a front door it is.ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Open Source: Nvidia Goes All In with Nemotron 3 Super 120B (X, Blog, HF)We had Chris Alexiuk from Nvidia join us — a friend from a dinner Nisten and I hosted in Toronto. Chris is basically “NeMo” embodied, sitting at the intersection of product and research, and he gave us the full breakdown on what might be the most complete open-source model release we’ve seen from a major lab.Here are the numbers: 120B total parameters, 12B active during inference (it’s a Mixture of Experts), 1 million token context window, and a hybrid Mamba-Transformer architecture they call “Hybrid Mamba Latent MoE with Multi-Token Prediction.” It’s hitting 450 tokens per second on the Terminal Bench leaderboard — faster than any other model on there. Modal is reporting over 50% faster token generation compared to other top open models.What Chris was emphatic about — and I want to highlight this — is that “most open” is a real designation here. They released the model checkpoint in three precisions (BF16, FP8, NVFP4), the base checkpoint before post-training, the SFT training data, and in a move that genuinely surprised people, pre-training data and a full end-to-end training recipe. You can, in theory, reproduce their training run. That’s rare. That’s a real commitment to open source.There’s also a huge piece of news in the background here: there’s a confirmed report that Nvidia will spend $26 billion over the next five years building the world’s best open source models. Jensen presumably has GTC remarks incoming on this. America is genuinely back in the open source AI race, and it’s Nvidia leading the charge. Chris has been in the open source world since the Hugging Face early days and said it feels genuine inside the company — not a PR exercise. And I tend to believe him. Now, all eyes are on GTC next week!I ran Nemotron 3 Super with my own OpenClaw instance yesterday via W&B inference and it’s genuinely fast and capable. At $0.20/M input tokens and $0.80/M output tokens on W&B inference, it’s not going to replace Opus for your hardest tasks — but for running an always-on agent that needs to be cost-efficient? It’s an incredible option. More on that in the this weeks buzz section below.Tools & Agentic EngineeringPaperclip: Zero Human Companies, Now Open Source (Github)We had the anonymous Dotta on the show — the first AI video avatar anon person to join ThursdAI — to talk about Paperclip, an open source agent orchestration framework that hit 20,000 GitHub stars in its first week. The premise is simple and audacious: build zero-human companies.Now this may sound familiar to you, as we had Ben from Polsia on just two weeks ago, which is a similar concept, but Paperclip is an OpenSource project, which you can run right now on your own.The core “thing” that got me excited about Paperclip is that you can “hire” your own existing OpenClaw agents, or Cursor or Codex or whatever else to play roles in this autonomous company. The premise is simple, you’re the board of directors, you hire an AI Agent CEO, and it then asks you if it needs to “hire” more AI agents to do tasks autonomously. These tasks all live inside Paperclip interface, and you or your Agents can open them. The core concept of this whole system is the heartbeat concept, each agent receives their own instructions on what to do every time they are “woken up” by a timer. This is what’s driving the “autonomous” part of the whole thing, but it’s also what’s eating the tokens up, even if there’s no work being done, agents are still burning tokens asking “is there work to be done?” Dotta gave us a great metaphor, asking if we saw the movie Memento, where the protagonist lost his memory and every time he woke up, he woke up with a blank slate, and had to reconstruct the memories. AI agents are like the memento man, and Paperclip is an attempt to give those agents the whole context so they can continue working on your tasks productively. Dotta told us that the future of Paperclip is the ability to “fork” entire companies, structures that will actually run and do things on your behalf. Looking forward to that future, but for now I will be turning off my Paperclip interface as it’s costing me real money without the need. Symphony: Agents Writing Their Own Jira TicketsWe mentioned Symphony last week, and I texted Ryan the link before the show, and voila, of course, he set it up and went viral, yet again! We’re so lucky to have Ryan on the show to tell us from first hand experience what it’s like to run this thing. Symphony was open sourced by OpenAI last week, and it’s basically an instruction manual for how to run agents autonomously via Linear ticketing system. (Github)The highlight for Ryan was, the whole system is running creating pull requests while he’s a sleep, and at some point, he noticed a ticket that he didn’t create. One of the agents found a bug, and created a very detailed ticket for him to approve. I’m just happy that I can keep even my co-hosts up to date heheThis weeks buzz - we’ve got skills and nemotrons!Look, we told you about Skills in the start of the year, since then, via OpenClaw, Hermes Agent, Claude Code, they exploded in popularity. One downside of skills is, it’s very easy to make a bad one! So, we’re answering the challenge, and are publishing the official wandb skill 🎉 Installing it is super simple, npx skills add wandb/skills and voila, your agents are now officially “I know kung fu” pilled with the best Weights & Biases practices. For both Weave and Models 👏 Please give us feedback on Github if you have used the skills! GithubAlso, we’ve partnered with Nvidia to support the best US open source model on day 0, and we have Nemotron 3 Super on our inference service, for all to use at $0.20/1Mtok! It’s super easy to setup with something like Hermes Agent or OpenClaw and runs really really fast! Check it out here. Is it going to perform like Opus 4.6? No. But are you going to run Opus 4.6 at 20 cents per million? Also no. Gemini drops SOTA embeddings and gets dethroned 2 days later live on the show. This always happens, but I didn’t expect this to happen in a fairly niche segment of the AI world... multimodal embeddings! Gemini posted an update earlier this week with Gemini Embeddings 2.0, a way to unify images, text, video, audio embeddings under 1 roof, and posted a SOTA embedding model! Then, just as we launch the show, a friend of the pod Benjamin Clavie, drops me a DM, basically saying that his company Mixbread is going to deploy an embedding model that will beat Gemini Embedding 2 on almost every benchmark on that table, and then... they did! The most notable (and absolutely crazy) jump in this comparison is, the LIMIT benchmark, where they achieved a 98% score vs Gemini’s ... 6.9 percent. I didn’t believe this at first, but asked Ben to explain the findings, and he did. Congrats to folks for moving the search space forward every 2 days! Grok 4.20 in the API for $2/1MtokElon Musk and XAI co finally released Grok 4.20 in the API. Look I said what I said about XAI models, they are great for research, and for factuality, but they aren’t beating the major labs. The last firing of almost of XAI folks doesn’t help either. So this model was not “released” in any traditional sense, there’s no benchmarks, no evals, and everyone who got access to it evaluated it and, it’s no better than GLM5 on many benchmarks. So it does makes sense to release it quietly. It is very fast though, and again, for research and for X access, it’s an absolute beast, so I’ll be trying this out! Parting thoughts and a small reflection. For the past 3 years, we’ve had a front-row seat to the singularity shaping up. 2.5 years ago, I went all in, decided to pivot into podcasting full time. In those years, ThursdAI became known, we’ve had guests from nearly all major AI labs (including Chinese ones, for which I’m particularly proud), I got to meet with executives, ask leaders questions about where this is all going, and most of all, share this journey with all of you, candidly. We rarely do hype on the show, we don’t speculate, we try to do a positive outlook on the whole thing, and counter doomerism, as there’s too much of that out there. I am very glad this resonates, and continue to be thankful for your attention! If you wanted to give us any kind of a birthday present, subscribe or give us a 5 star review on Apple Podcasts or Spotify, it’ll greatly help other folks to discover us. See you next week, Alex 🫡ThursdAI - Mar 12, 2026 - TL;DR* Hosts and Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co Hosts - @WolframRvnwlf @yampeleg @nisten @ldjconfirmed) @ryancarson* Chris Alexiuk from Nvidia (@llm_wizard) - Nemotron* @dotta - creator of Paperclip.ing AI agent orchestration framework* Matt Van Horn - @mvanhorn - creator of @slashlast30days* Singularity updates* Andrej Karpathy’s autoresearch achieves 11% speedup on GPT-2 training through autonomous AI agent experimentation (X, GitHub, GitHub)* Eon Systems uploads first complete fruit fly brain to a physics-simulated body, achieving 91% behavioral accuracy (X, Announcement, Announcement)* OpenClaw mania sweeps China as all five major cloud providers race to support it (HelloChinaTech, Reuters, SCMP, MIT Tech Review)* Big CO LLMs + APIs* xAI quietly releases Grok 4.20 API with massive 2M token context window and multi-agent capabilities (X, Blog)* Google launches Gemini Embedding 2, the first natively multimodal embedding model supporting text, images, video, audio, and PDFs in a unified vector space (X, Announcement)* Open Source LLMs* NVIDIA launches Nemotron 3 Super: 120B open MoE model with 1M context window designed for agentic AI at 5x higher throughput (X, Announcement)* MiroMind releases MiroThinker-1.7 and H1 - open-source research agents with 256K context, 300 tool calls, achieving SOTA on deep research benchmarks (X, HF, HF, HF)* Covenant-72B: World’s largest permissionless decentralized LLM pre-training achieves 72B parameters on Bittensor with 146x gradient compression (X, Arxiv, HF, HF)* Tools & Agentic Engineering* ACP is the open standard that lets any AI coding agent plug into any editor — and this week Cursor officially joined the registry, meaning you can now run Cursor’s agent inside JetBrains IDEs (JetBrains blog, Cursor blog)* This weeks Buzz* W&B launches official Agent Skills for coding agents, turning experiment dashboards into terminal queries (X, Announcement, Announcement)* Video* LTX-2.3 — Lightricks open-source video model (GitHub, HF,Blog)* Voice & Audio* Fish Audio launches S2: Open-source TTS with sub-150ms latency and absurdly controllable emotion (X, HF, Blog, Announcement)* Show notes and links* Paperclip.ing by Dotta ( @dotta) - Github* Last30days skill by Matt Van Horn Github* Agency Agents repo Github* OpenAI Symphony (Github)* Mixbread Embeddings (X) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey folks, Alex here, let me catch you up! Most important news about this week came today, mid-show, OpenAI dropped GPT 5.4 Thinking (and 5.4 Pro), their latest flagship general model, less autistic than Codex 5.3, with 1M context, /fast mode and the ability to steet it mid-reasoning. We tested it live on the show, it’s really a beast. Also, since last week, Anthropic said no to Department of War’s ultimatum and it looks like they are being designated as supply chain risk, OpenAI swooped in to sign a deal with DoW and the internet went ballistic (Dario also had some .. choice words in a leaked memo!) On the Open Source front, the internet lost it’s damn mind when a friend of the pod Junyang Lin, announced his departure from Qwen in a tweet, causing an uproar, and the CEO of Alibaba to intervene. Wolfram presented our new in-house wolfbench.ai and a lot more! P.S - We acknowledge the war in Iran, and wish a quick resolution, the safety of civilians on both sides. Yam had to run to the shelter multiple times during the show. ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.OpenAI drops GPT 5.4 Thinking and 5.4 Pro - heavy weight frontier models with 1M context, /fast mode, SOTA on many evalsOpenAI actually opened this week with another model drop, GPT 5.3-instant, which... we can honestly skip, it was fairly insignificant besides noting that this is the model that most free users use. It is supposedly “less cringe” (actual words OpenAI used). We all wondered when 5.4 will, and OpenAI once again proved that we named the show after the right day. Of course it drops on a ThursdAI. GPT 5.4 Thinking is OpenAI latest “General” model, which can still code, yes (they folded most of the Codex 5.3 coding breakthroughs in here) but it also shows an incredible 83% on GDPVal (12% over Codex), 47% on Frontier Math and an incredible ability to use computers and browsers with 82% on BrowseComp beating Claude 4.6 at lower prices than Sonnet! GPT 5.4 is also ... quite significantly improved at Frontend design? This landing page was created by GPT 5.4 (inside the Codex app, newly available on Windows) in a few minutes, clearly showing significant improvements in style. I built it also to compare prices, all the 3 flagship models are trying to catch up to Gemini in 1M context window, and it’s important to note, that GPT 5.4 even at double the price after the 272K tokens cutoff is still.... cheaper than Opus 4.6. OpenAI is really going for broke here, specifically as many enterprises are adopting Anthropic at a faster and faster pace (it was reported that Anthropic is approaching 19B ARR this month, doubling from 8B just a few months ago!) Frontier math wizThe highlight from the 5.4 feedback came from a Polish mathematician Bartosz Naskręcki (@nasqret on X), who said GPT-5.4 solved a research-level FrontierMath problem he had been working on for roughly 20 years. He called it his “personal singularity,” and as overused as that word has become, I get why he said it. I’ve told you about this last week, we’re on the cusp. Coding efficiencyThere’s tons of metrics in this release, but I wanted to highlight this one, where it may seem on first glance that on SWE-bench Pro, this model is on par with the previous SOTA GPT 5.3 codex, but these dots here are thinking efforts. And a medium thinking effort, GPT 5.4 matches 5.3 on hard thinking! This is quite remarkable, as lower thinking efforts have less tokens, which means they are cheaper and faster ultimately! Fast mode arrives at OpenAI as wellI think this one is a direct “this worked for Anthropic, lets steal this”, OpenAI enabled /fast mode that.. burns the tokens at 2x the rate, and prioritizes your tokens at 1.5x the speed. So, essentially getting you responses faster (which was one of the main complains about GPT 5.3 Codex). I can’t wait to bring the fast mode to OpenClaw with 5.4, which will absolutely come as OpenClaw is part of OpenAI now. There’s also a really under-appreciated feature here that I think other labs are going to copy quickly: mid-thought steering. OpenAI now lets you interrupt the model while it’s thinking and redirect it in real time in ChatGPT and iOS. This is a godsend if you’re like me, sent a prompt, seeing the model go down the wrong path in thinking... and want to just.. steer it without stopping! Anthropic is now designated as supply-chain risk by DoWLast week I left you with a cliffhanger: Anthropic had received an ultimatum from the Department of War (previously the Department of Defense) to remove their two remaining restrictions on Claude — no autonomous kill chain without human intervention, and no surveillance of US citizens. Anthropic’s response? “we cannot in good conscience acceede to their request” So much has happened since then; US President Trump said “I fired Anthropic” referring to his Truth Social post demanding intelligence agencies drop the use of Claude (which apparently was used in the war with Iran regardless); Sam Altman announced that OpenAI has agreed to DoW and will provide OpenAI models, causing a lot of people to cancel their OpenAI subscriptions, and later apologizing for the “rushed rollout”; Dario Amodei posted a very contentious internal memo that leaked, in which he name-called the presidency, Sam Altman and his motives, Palantir and their “safety theater”, for which he later apologizedHonestly this whole thing is giving me whiplash trying to follow, but here’s the facts. Anthropic is now the first US company in history, being designated “supply chain risk” which means no government agency can use Claude, and neither can any company that does contracts with DoW. Anthropic says it’s illegal and will challenge this in court , while reporting $19B in annual recurring revenue, nearly doubling since last 3 months, and very closely approaching OpenAI at $25B. Look, did I want to report on this stuff when I decided to cover AI? no... I wanted to tell you about cool models and capabilities, but the world is changing, and it’s important to know that the US Government understands now that AI is inevitable, and I think this is just the first of many clashes between tech and government we’ll see. We’ll keep reporting on both. (but let me know in the comments if you’d prefer just model releases) OpenAI’s GPT-5.3 Instant Gets Less Cringe, Google’s Flash-Lite Gets Faster (X, Announcement)We also got two fast-model updates this week that are worth calling out because these are the models that often end up powering real product flows behind the scenes. As I wrote before, OpenAI’s instant model is nothing to really mention, but it’s worth mentioning that OpenAI seems to have an answer for every Gemini release. Gemini released Gemini Flash-lite this week, which boasts an incredible 363 tokens/s speed, which doing math at a very good level, 1M context and great scores compared to the instant/fast models like Haiku from Anthropic. Folks called out that this model is more expensive than the previous 2.5 Flash-lite. But with 86.9% on GPQA Diamond beating GPT-5 mini, and 76.8% MMMU-pro multimodal reasoning, this is definitely worth taking a look at for many agentic, super fast responses! For example, the heartbeat response in OpenClaw. Qwen 3.5 Small Models & The Departure of Junyang Lin (X, HF, HF, HF)Alibaba’s Qwen team continued releasing their Qwen 3.5 family, this time with Qwen 3.5 Small, a series of models at 0.8B, 2B, 4B, and 9B parameters with native multimodal capabilities. The flagship 9B model is beating GPT-OSS-120B on multiple benchmarks, scoring 82.5 on MMLU-Pro and 81.7 on GPQA Diamond. These models can handle video, documents, and images natively, support up to 201 languages, and can process up to 262K tokens of context. And.. they are great! They are trending on HF right now. What’s also trending is, tech lead for Qwen, a friend of the pod Junyang Lin, has posted a cryptic tweet that went viral with over 6M views. There was a lot of discussions on why he and other Qwen leads are stepping away, what’s goig to happen with the future of OpenSource. The full picture seems to be, there are a lot of internal tensions and politics, with Junyang being one of the youngest P10 leaders in the Alibaba org.A Chinese website 36KR ( Kind of like a chinese techcrunch) reported that this matter went all the way up to Alibaba CEO, who is no co-leading the qwen team, and that this resignation was related to an internal dispute over resource allocation and team consolidation, not a firing. I’m sure Junyang is going to land somewhere incredible and just wanted to highlight just how much he did for the open source community, pushing Qwen relentlessly, supporting and working with a lot of inference providers (and almost becoming a co-host for ThursdAI with 9! appearances!) StepFun releases Step 3.5 Flash Base (X, HF, HF, Announcement, Arxiv)Speaking of Open Source, StepFun just broke through the noise with a new model, a 196B parameter sparse Mixture of Experts model activating just 11B parameters when ran. It has some great benchmarks, but the main thing is this: they are releasing the pretrained base weights, a midtrain checkpoint optimized for code and agents, the complete SteptronOSS training framework, AND promising to release their SFT data soon - all under Apache 2.0! Technically the model looks strong too, with multi-token prediction, 74.4% on SWE-bench verified bench (though, as we told you last week, it’s.. no longer trusted) and full apache 2! This Week’s Buzz: presenting Wolfbench.ai I’m so excited about this weeks “this weeks buzz”, Wolfram has been hard at work preparing and presenting a new framework to test out these models, and named it wolfbench.ai Wolfbench is our attempt to compare how the same model performs via different agentic harnesses like ClaudeCode, OpenClaw and Terminalbench’s own Terminus. You can check out the website on wolfbench.com but the short of it is, a single number is not telling the full story. Wolf Bench breaks it into a four-metric framework: the average score across runs, the best single run, the ceiling (how many tasks can the model solve at least once across all runs), and the floor (how many tasks does it solve consistently across every single run). That last one is what I find most illuminating. Opus 4.6 might be able to solve 88% of Terminal Bench tasks on average, but only about 55% of tasks it solves every single time. Reliability matters enormously for agents, and benchmarks almost never surface this. If you want to run your own evals with the same config, reach out to Wolfram—he’s open to community contributions. Wolfram has also already kicked off a Wolf Bench run on GPT-5.4 since we tested it live today, so stay tuned for those results.There’s quite a few more releases we didn’t have time to get into on the show given the GPT 5.4 drop, you’ll find all those links in the show notes! Next week will mark 3 years since I’ve started talking about AI on the internet and created ThursdAI (It was March 14th, 2023, same day as GPT4 launched) and we’ll have a little celebration, I do hope you join us live 🔥 As a birthday present, you may choose to share ThursdAI with a friend or two, or rate us in your podcast player of choice! See you next week, Alex 🫡 ThursdAI - Mar 05, 2026 - TL;DRTL;DR of all topics covered:* Hosts and Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co Hosts - @WolframRvnwlf @yampeleg @nisten @ldjconfirmed @ryancarson* Big CO LLMs + APIs* OpenAI launches GPT-5.4 Thinking and Pro (X, X, X, X)* Anthropic, Dept of War and OpenAI walk into a bar* Alibaba Qwen departures: Friend of the pod JunyangLin and Binyuan Huy both depart Qwen (X)* OpenAI Rolls Out GPT-5.3 Instant (X)* Google launches Gemini 3.1 Flash-Lite (X, Announcement)* Evals and Benchmarks* MarinLab shows degradation in Opus 4.6 (X)* B******t Bench from Peter Gostev (X)* Open Source LLMs* StepFun releases Step 3.5 Flash Base models (X, HF, HF, Announcement, Arxiv)* Alibaba releases Qwen 3.5 Small Model Series (X, HF, HF, HF)* Yuan 3.0 Ultra (X, Blog, HF)* Tools & Agentic Engineering* Cognition: SWE-1.6 preview (X, Blog)* OpenAI launches Codex app on windows (X)* Google released Google Workspace CLI (X)* OpenAI released Symphony (Github)* This weeks Buzz* Early preview of Wolf Bench (wolfbench.ai) from W&B* AI Art & Diffusion & 3D* Black Forest Labs introduces Self-Flow (X, Announcement) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey, it’s Alex, let me tell you why I think this week is an inflection point.Just this week: Everyone is launching autonomous agents or features inspired by OpenClaw (Devin 2.2, Cursor, Claude Cowork, Microsoft, Perplexity and Nous announced theirs), METR and ArcAGI 2,3 benchmarks are getting saturated, 1 person companies nearing 1M ARR within months of operation by running AI agents 24/7 (we chatted with one of them on the show today, live as he broke $700K ARR barrier) and the US Department of War gives Anthropic an ultimatum to remove nearly all restrictions on Claude for war and Anthropic says NO. I’ve been covering AI for 3 years every week, and this week feels, different. So if we are nearing the singularity, let me at least keep you up to date 😅 Today on the show, we covered most of the news in the first hour + breaking news from Google, Nano Banana 2 is here, and then had 3 interviews back to back. Ben Broca with Polsia, Nader Dabit with Cognition and Philip Kiely with BaseTen. Don’t miss those conversations starting at 1 hour in. Thanks for reading ThursdAI - Highest signal weekly AI news show! This post is public so feel free to share it.Anthropic vs Department of WarEarlier this week, the US “Department of War” invited Dario Amodei, CEO of Anthropic to a meeting, where-in Anthropic was given an ultimatum. “Remove the restrictions on Claude or Anthropic will be designated as a ‘supply chain risk’ company” and the DoD will potentially go as far as using the Defence Production Act to force Anthropic to ... comply. The two restrictions that Anthropic has in place for their models are: No use for domestic surveillance of American citizens and NO fully autonomous lethal weapens decisions given to Claude. For context, Claude is the only model that’s deployed on AWS top secret GovCloud and is used through Palantir’s AI platform. As I’m writing this, Anthropic issued a statement from Dario statement saying they will not budge on this, and will not comply. I fully commend Dario and Anthropic for this very strong backbone, but I fear that this matter is far from over, and we’ll continue to see what is the government response. EDIT: Apparently the DoD is pressuring Google and OpenAI to agree to the stipulations and employees from both companies are signing this petition https://notdivided.org/ to protest against dividing the major AI labs on this topic. Anthropic and OpenAI vs upcoming DeepseekIt’s baffling just how many balls are in the air for Anthropic, as just this week also, they have publicly named 3 Chinese AI makers in “Distillation Attacks”, claiming that they have broke Terms of Service to generate over 16M conversations with Claude to improve their own models, while using proxy networks to avoid detection. This marks the first time a major AI company publicly attributed distillation attacks to specific entities by name.The most telling thing to me is not the distillation, given that Anthropic has just recently settled one of the largest copyright payouts in U.S history, paying authors about $3000/book, which was bought, trained on and destroyed by Anthropic to make Claude better. No, the most telling thing here is the fact that Anthropic chose to put DeepSeek on top of the accusation list with merely 140K conversations, where the other labs created millions. This, plus OpenAI formal memo to Congress about a similar matter, shows that the US labs are trying to prepare for Deepseek new model to drop, by saying “Every innovation they have, they stole from us”. Apparently Deepseek V4 is nearly here, it’s potentially multimodal and has been allegedly trained on Nvidia chips somewhere in Mongolia despite the export restrictions and it’s about to SLAP! Benchmark? What benchmarks? How will we know that we’re approaching the singularity? Will there be signs? Well, this week it seems that the signs are here. First, Agentica claimed that they solved all publicly available “hard for AI” tasks of the upcoming ArcAGI 3, then Confluence Labs announced that they got an unprecedented 97.9% on ArcAGI2 and finally METR published their results on the long-horizon tasks, which measure AI’s capability to solve task that take humans a certain amount of hours to do. And that graph is going parabolic, with Claude Opus 4.6 able to solve tasks of 14.6h (doubling every 49 days) with 50% success rateWhy is this important? Well, this is just the benchmarks telling the story that everyone else in the industry is seeing, that approximately since December of 2025, and definitely fueled by early Feb drop of Opus 4.6 and Codex 5.3, something major shifted. Developers no longer write code, but ship 10x more features.This became such a talking point, Swyx Latent.Space coined this with https://wtfhappened2025.com/ where he collects evidence of a shelling point, something that happened in December and I think continued throughout February. Speaking of benchmarks no longer being valid, OpenAI published that the divergence between the SWE-bench verified gains with real life performance is so vast, that they will no longer be using SWE-bench verified, and will be switching to SWE-bench pro for evaluations. Everyone’s Autonomous agents (and subagents) are hereLook, with over 250K Github stars, OpenAI getting Peter Steinberger on board, it’s clear now. OpenClaw made a huge dent in how people think about autonomous agents (and subagents!)It may be a “moment in time” that the model capabilities were “just good enough” to be able to run agents async for a long time. but the big labs noticed the OpenClaw excitement and are shipping like never before to make sure their users don’t switch over!Perplexity launched “Computer“, which has scheduled tasks in a compute environment, and can complete long lasting projects end to end, Cursor pivots from IDE only to running Agents in the cloud with their own environments, Claude Code added memory, and Remote Control, while Claude Cowork added Scheduled tasks, our friends from Nous shipped Hermes Agent and even Microsoft wants to bring this to their customers in Copilot. The most interesting one from these is the new Devin from Cognition.I’ve gotten access and chatted with Nader Dabit on the show about how Devin was the “OG” async coding Agent, but now as models capabilities are here, Devin can do so much more. PR reviews with devinreview.com can complete the loop between coding, fixing and testing something end to end. They have an integrated environment with a scrub so you can roll back and see what the agent did, scheduled tasks and video showing you how the agent tested your website. I’ve used it to fix bugs in ThrusdAI.news and it found a few that Claude Code didn’t even know about! You can try out Devin (for free for a week?) here This weeks buzz - W&B updatesI’m happy this week, because we finally launched both 2.5 open source models that we’re making the news lately. Kimi 2.5 and MiniMax M2.5 are both live on our inference service, at very very decent prices! Check them both out here and let me know if you need some credits. From the show this week, most hosts agree that Kimi 2.5 is the best open source alternative to Opus inside OpenClaw, just give your agent the WANDB_API_KEY and ask it to set itself up with the new model! Surfing the singularity with Ben Broca and Polsia, hitting $700K ARR since DecemberI’ve reached out to Ben and asked him to join the show this week because alongside OpenClaw blowing up since December, his Polsia startup, which builds and scales entire companies with AI agents running 24x7 has hit an unprecedented $700K ARR milestone after just a few months. We actually saw him break the $700K ARR on the show live 🎉 But get this, he’s the only employee, everything is done with AIs. He’s using Polsia to scale Polsia.Polsia let’s anyone add an existing company or create a whole new one, and then a team of agents will spin up a marketing team, a GTM motion, a research arm and you and Polsia could work together to make this company a reality. Does this actually work? IDK, the whole thing is new, I’m trying out a few things and will let you know in a few weeks if any of this worked. But it’s definitely blowing up, Ben showed us that over the last 24 hours, over 770 companies launched on Polsia, he’s hitting nearly 1M ARR with people paying $50/mo for him to run inference for them, marketing campaigns, and he just added Meta ads. This ARR chart, the live dashboard, and Ben doing all of this Solo is underlining the whole “Singularity is near” thing for me! It’s impossible to imagine something like this working even... 5 months ago, and now we just accept it as .. sure, yeah, one person can manage AIs that manage checks notes over 700 companies. What’s clever about Polsia’s architecture is the cross-company learning system: when an agent learns something useful (like “subject lines with emojis get better open rates”), that learning gets anonymized and generalized into a shared memory file that benefits every company on the platform. The more companies running on Polsia, the smarter every agent gets — like a platform effect but for agent intelligence.AI Art, Video & Audio Seedance 2.0 is finally “here” This week has not been quiet in the multimodality world either, SeeDance 2.0 from ByteDance was delayed via the API partners (was supposed to launch Feb 24) due to copyright concerns, but apparently they dropped it inside CapCut, ByteDance’s video editing software! It’s really good though what makes it absolutely incredible IMO is the video transfer, and you can’t really do that in CapCut, so we’re keep waiting for the “full model” Nano Banana 2 - Pro level intelligence, with Flash speed and pricing (Blog)Google dropped a breaking news item before the show started today, and announced Nano Banana 2, which is supposed to be as good as Nano Banana Pro (which is incredible) but faster. It wasn’t really faster for me, as I got early access thanks to the DeepMind team, but apparently it’s just the rollout pains. But the quality is nearly matching Nano Banana Pro! It can do the same super high quality text rendering, comes with a few new ratios to create ultra long images (4:1 and 1:4) and a new small 512 resolution for extra cheap generation. The additional thing is Image Search is now integrated into the model, allowing it to look something up before generating. Though, that didn’t really work for me as well, I tried to get it to look up images of Mike Intrator and Dario Amodei, and it kept showing me random people who look nothing like them, despite the thinking traces showing the search did happen. Speaking of pricing, this model is around 50-30% cheaper than NBP, which is great given the added speed! Go play with it, it’s available on AI.dev and Gemini, go give it a try! Open source AI This week in OpenSource, our friends from Qwen came back with a set of 3 models, the middle medium one is a hybrid architecture with only 3B parameters that beats their 235B flagship Qwen3 from before! It’s really good at longer context especially given the hybrid attention similar to Jamba that we covered before. (X, HF, HF, HF, Blog)Additionally, Liquid AI releases their largest LFM, 24B (X, HF, Blog) and that is also deployable on consumer laptops. One note on AI tools, LM Studio, our favorite way of running these models on your hardware, have launched LMLink, powered by Tailscale, which let’s you run local inference on once device and stream tokens to any other device in your network securely! You can use this to run your OpenClaw with Qwen medium for example, for a complete off the grid OpenClaw!Check it out here: https://lmstudio.ai/linkI really didn’t want to sound hype-y but this week things are moving so fast that I was not sure how it’s possible to talk about all this, covering the news while also having 3 interviews. I think we’ve done a good job, but I am honestly getting to a point whereI have to do deep prioritization of what content is the most important in my eyes. I hope you guys enjoy my prioritization, and do leave comments of what you’d like to see more, or see less of! I am hungry for feedback! If you enjoyed this week’s newsletter, checkout the whole edited video and share it with a friend or two? See you next week! ThursdAI - Join us as we surf the AI singularity togetherHere’s the TL;DR and show notes: ThursdAI - Feb 26, 2026 - TL;DR* Hosts and Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co Hosts - @WolframRvnwlf @yampeleg @nisten @ldjconfirmed @ryancarson* Ben Cera (@bencera_) - Founder Polsia* Nader Dabit (@dabit3) - Growth at Cognition* Philip Kiely (@philipkiely) - Devrel Base10, Author Inference Engineering* ThursdAI new website: https://thursdai.news* Big CO LLMs + APIs* Anthropic vs Chinese OSS - Accuses DeepSeek, Minimax, ZAI at distillation attacks (Blog)* Pentagon Issues an ultimatum to Anthropic: Give military unfettered Claude access by Friday or face Defense Production Act - Anthropic says NO (Blog)* OpenAI releases GPT-5.3-Codex, their most capable agentic coding model, to all developers via the Responses API (X, Announcement)* Open Source LLMs* Alibaba: Qwen 3.5 Medium - 35B model with only 3B active parameters outperforms their previous 235B flagship (X, HF, HF, HF, Blog)* Liquid AI releases LFM2-24B-A2B: A 24B MoE model with only 2.3B active parameters that runs on consumer laptops (X, HF, Blog)* Perplexity launches ppxl-embed - SOTA embedding models (Blog, HF, API) by our friend Bo Wang* Evals & Benchmarks* METR’s Time Horizon Benchmark Goes Vertical: Claude Opus 4.6 Achieves ~14.5 Hour Task Completion (X, Blog)* Confluence Labs emerges from stealth with 97.9% SOTA on ARC-AGI-2 benchmark (X, GitHub)* OpenAI Retires SWE-bench Verified, (X, Blog, X)* Agentica claiming to solve all public ArcAGI 3 (X)* Tools & Agentic Engineering* Happy 1 year Birthday Claude Code!* Devin AI 2.2 - autonomous agent with computer use, browser, self verify and self fix it’s own work - interview with Nader Dabit (X)* LMStudio launches LMLink - use your local models from everywhere with TailScale! (try it)* Claude Code introduces Remote Control: Control your local coding sessions from your phone or any device (X, Docs) and memory (X)* Claude Cowork and Codex both now have automations (Cron Jobs) to do tasks for you (Cowork)* Cursor launches cloud agents that onboard to codebases, run in isolated VMs, and deliver video demos of completed PRs (X)* Nous research agent (X)* Perplexity Computer (blog)* Microsoft Copilot tasks (blog)* This weeks Buzz - Weights & Biases update* W&B adds MiniMax 2.5 and Kimi K2.5 on our Inference Service (LINK)* Interviews mention links* Ben Broca - polsia.com/live Polsia Dashboard* Nader Dabit - on seeing the future (blog)* Philip Kiely - Inference Engineering book (Book)* Vision & Video* Seedance 2.0 finally available in Capcut in US. API release apparently held back due to copyright issues (X)* Voice & Audio* OpenAI releases gpt-audio-1.5 and gpt-realtime-1.5 models with major improvements in speech-to-speech AI capabilities (X, Announcement)* AI Art & Diffusion & 3D* Google DeepMind launches Nano Banana 2 (X, Announcement)* Quiver solves SVG with Arrow 1.0 (X)* Others* Taalas AI - 15,000 tokens per second demo (chatjimmy.ai/) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe