Teaching Computers to Smell?! The AI That's Digitizing Scent

Behind every AI response, there's an invisible army of humans who trained it. In this episode, we talk with Casper Elliott from Invisible Technologies - the company that's trained 80% of the world's top AI models. We explore how models actually learn, why data quality matters more than quantity, what enterprises get wrong about AI deployment, and whether AI will really automate everyone's jobs. Casper shares insights from working with frontier labs, reveals the surprising skills that make great AI trainers (hint: League of Legends helps), and explains why the future needs more humans, not fewer.Subscribe to The Neuron newsletter: https://theneuron.aiLearn more about Invisible Technologies: https://invisibletech.ai

Computers can see and hear, but they've never been able to smell—until now. In this episode, we sit down with Alex Wiltschko, Founder & CEO of Osmo, to explore how his company is using AI to digitize scent. Alex walks us through how they "teleported" the smell of a fresh plum across their lab, created the world's first AI-designed fragrance molecules, and built Osmo Studio—a platform that lets anyone design custom fragrances in one week instead of two years. We discuss the read/map/write framework for digitizing smell, why scent is tied directly to memory and emotion, and how this technology could eventually detect diseases like cancer and Parkinson's earlier than any current diagnostic. Plus: what does the Museum of Pop Culture smell like, and can AI really create a fragrance from a Bon Iver song?Links: Osmo: https://www.osmo.aiScent Teleportation Update: https://www.osmo.ai/blog/update-scent-teleportation-we-did-itOsmo Studio: https://osmostudios.ai/ Subscribe to The Neuron newsletter: https://theneuron.aiCheck out the sponsor of this video, Flora: https://dub.florafauna.ai/neuronSubscribe to The Neuron newsletter: https://theneuron.aiHosted by: Corey Noles and Grant HarveyGuest: Alex Wiltschko (Founder & CEO, Osmo)Published by: Manique SantosEdited by: Kush Felisilda

Ever wondered who's actually teaching ChatGPT and Claude how to think? Meet Caspar Eliot from Invisible Technologies - the company behind 80% of the world's top AI model training. In this eye-opening conversation, we uncover the massive human workforce behind "artificial" intelligence, why your League of Legends skills might land you an AI job, and the shocking mistakes enterprises make when deploying AI.We discuss:• How AI models really learn (hint: it's not just scraping the internet)• Why data quality beats data quantity every time• The Charlotte Hornets' revolutionary AI scouting system• Whether robots will actually take your job (spoiler: probably not)• The $14.8 billion Scale AI valuation and what it means• Why Mark Andreessen thinks VCs won't be automatedPlus: Caspar reveals the #1 mistake companies make with AI deployment and why "AI-ifying" your current process is doomed to fail.Subscribe to The Neuron newsletter: https://theneuron.aiConnect with Caspar on LinkedIn: https://uk.linkedin.com/in/caspar-eliot-46b9a55aLearn more about Invisible Technologies: https://invisibletech.ai?utm_source=neuron&utm_medium=podcastPlease check out the sponsor of this video, Warp.dev: https://warp.devSo who is Invisible Technologies? In four words: they make AI work. Their platform cleans, labels, and structures company data so it’s ready for AI. It adapts models to each business and adds human expertise when needed — the same approach used to improve models for over 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.Their successes span industries from supply chain automation for Swiss Gear, to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets. And get this: Invisible has been profitable for over half a decade, was ranked #2 fastest-growing AI company in 2024, and recently raised $100M to advance its platform technology.Check them out at Invisible Technologies: https://invisibletech.ai?utm_source=neuron&utm_medium=podcast

From Adobe Max 2025 in Los Angeles, Corey and Grant sit down with Ely Greenfield, Adobe's Chief Technology Officer, to explore the philosophy behind Adobe's practical AI strategy. Discover why the crowd went wild over AI renaming layers, how Adobe thinks about "additive not subtractive" AI, and where creative tools are heading next. Ely shares Adobe's vision for making AI a creative partner that enhances rather than replaces human artistry, and explains why the best AI features are often the most boring ones.Topics covered include: the Photoshop AI Assistant, Harmonize for instant compositing, auto-masking in Premiere Pro, the Express conversational workflow, and Adobe's unique approach to balancing automation with creative control.Read our Adobe Max coverage:• Adobe Reinvents Creative Suite with AI• Day 2 Keynote Recap• NVIDIA's Beyond-GPUs StrategyThis episode was made possible by our sponsor, Clutch: https://clutch.co/resources/how-smbs-see-ai-crawlers?source=theneuron&utm_medium=referral&utm_campaign=newsletter_10-14-2025Related resources:• Adobe Max 2025 announcements: https://www.theneuron.ai/explainer-articles/adobe-goes-all-in-on-ai-max-2025-unleashes-creative-ai-arsenal-across-every-tool• Day 2 Keynote and Sneaks recap: https://www.theneuron.ai/explainer-articles/adobe-max-day-2-the-storyteller-is-still-king-but-ai-is-their-new-superpower• Check out Adobe Firefly: https://firefly.adobe.com/• Project Graph demo: https://www.youtube.com/live/wQza2t9Qs64?t=10409sMake sure to check out Clutch's new report on AI crawling for SMBS! https://clutch.co/resources/how-smbs-see-ai-crawlers?source=theneuron&utm_medium=referral&utm_campaign=newsletter_10-14-2025Subscribe to The Neuron newsletter for daily AI news: https://theneuron.aiOriginal article: https://www.theneuron.ai/explainer-articles/adobe-goes-all-in-on-ai-max-2025-unleashes-creative-ai-arsenal-across-every-tool

AI is changing what we need from our computers—but does that mean you need an "AI PC"? Corey and Grant sit down with Logan Lawler from Dell Technologies who leads Dell Pro Max AI solutions to decode what matters (and what doesn't) when buying or upgrading your next computer. From CPUs and GPUs to memory, NPUs, and traps to avoid, this episode is your practical roadmap for staying future-ready through the next five years of AI-powered work.Dell Pro Max Workstations: https://www.dell.com/en-us/plcp/lp/dell-pro-max-pcs LM Studio LIVE tutorial: https://www.youtube.com/watch?v=Ai3sBeBdA1Y Kiwix Wikipedia Download: https://en.wikipedia.org/wiki/Kiwix One Trainer: https://github.com/Nerogar/OneTrainerJawset Postshot: https://www.jawset.com/Subscribe to The Neuron newsletter: https://theneuron.aiCheck out the Reshaping Workflows Podcast: https://reshaping-workflows.simplecast.com/

AI is changing what we need from our computers—but does that mean you need an "AI PC"? Corey and Grant sit down with Logan Lawler from Dell Technologies who leads Dell Pro Max AI solutions to decode what matters (and what doesn't) when buying or upgrading your next computer. From CPUs and GPUs to memory, NPUs, and traps to avoid, this episode is your practical roadmap for staying future-ready through the next five years of AI-powered work.Dell Pro Max Workstations: https://www.dell.com/en-us/plcp/lp/dell-pro-max-pcs LM Studio LIVE tutorial: https://www.youtube.com/watch?v=Ai3sBeBdA1Y Kiwix Wikipedia Download: https://en.wikipedia.org/wiki/KiwixOne Trainer: https://github.com/Nerogar/OneTrainerJawset Postshot: https://www.jawset.com/Subscribe to The Neuron newsletter: https://theneuron.aiCheck out the Reshaping Workflows Podcast: https://reshaping-workflows.simplecast.com/

Learn how to use NVIDIA's Nemotron open-source AI models with VP Kari Briski. We cover what Nemotron is, minimum hardware specs, the difference between Nano/Super/Ultra tiers, when to choose local vs cloud AI, and practical deployment patterns for businesses. Perfect for anyone wanting to run powerful AI locally with full control and privacy.Resources mentioned:NVIDIA Nemotron Models: https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/Start prototyping for free: https://build.nvidia.com/explore/discoverSubscribe to The Neuron newsletter: https://theneuron.aiWatch more AI interviews: https://www.youtube.com/@TheNeuronAI

AI search is fundamentally changing how people find information online, but it's also creating a Wild West of spam, manipulation, and brand impersonation. SEO expert Mark Williams-Cook joins us to discuss why he calls AI a "leaky bucket," how expired domains are gaming LLMs, and what the death of the link graph means for the future of search. We'll explore practical strategies for making your site visible to AI, the risks brands face from AI phishing, and whether SEO is truly dead or just evolving. Perfect for anyone who owns a website or runs a business.Subscribe to The Neuron newsletter: https://theneuron.aiGuest: Mark Williams-Cook - Director at Candour, Founder of AlsoAskedFind Mark on LinkedIn: https://www.linkedin.com/in/markseo Search with Candour podcast: https://withcandour.co.uk/podcast 

Everyone's talking about the AI datacenter boom right now. Billion dollar deals here, hundred billion dollar deals there. Well, why do data centers matter? It turns out, AI inference (actually calling the AI and running it) is the hidden bottleneck slowing down every AI application you use (and new stuff yet to be released). In this episode, Kwasi Ankomah from SambaNova Systems explains why running AI models efficiently matters more than you think, how their revolutionary chip architecture delivers 700+ tokens per second, and why AI agents are about to make this problem 10x worse.💡 This episode is sponsored by Gladia's Solaria - the speech-to-text API built for real-world voice AI. With sub-270ms latency, 100+ languages supported, and 94% accuracy even in noisy environments, it's the backbone powering voice agents that actually work. Learn more at gladia.io/solaria🔗 Key Links:• SambaNova Cloud: https://cloud.sambanova.ai• Check out Solaria speech to text API: https://www.gladia.io/solaria• Subscribe to The Neuron newsletter: https://theneuron.ai🎯 What You'll Learn:• Why inference speed matters more than model size• How SambaNova runs massive models on 90% less power• Why AI agents use 10-20x more tokens• The best open source models right now• What to watch for in AI infrastructure➤ CHAPTERSTimecode - Chapter Title0:00 - Intro2:14 - What is AI Inference?3:19 - Why Inference is the Real Challenge9:18 - A message from our sponsor, Gladia Solaria10:16 - The 95% ROI Problem Discussion13:47 - SambaNova's Revolutionary Chip Architecture15:19 - Running DeepSeek's 670B Parameter Models18:11 - Developer Experience & Platform21:26 - AI Agents and the Token Explosion24:33 - Model Swapping and Cost Optimization31:30 - Energy Efficiency 10kW vs 100kW36:13 - Future of AI Models Bigger vs Smaller39:24 - Best Open Source Models Right Now46:01 - AI Infrastructure Next 12 Months47:09 - Agents as Infrastructure50:28 - Human-in-the-Loop and Trust52:55 - Closing and ResourcesArticle Written by: Grant HarveyHosted by: Corey Noles and Grant HarveyGuest: Kwasi AnkomahPublished by: Manique SantosEdited by: Adrian Vallinan

In this special hands-on episode, Corey Noles and Grant Harvey dive into OpenAI's Sora 2 - the AI video platform that's part TikTok, part meme generator, and 100% chaos. Watch as they navigate the new social media-style interface, create ridiculous videos featuring Sam Altman at a Berlin techno rave filled with clowns, and discover why Sam has become the "Tom from MySpace" of AI-generated content.The hosts explore Sora 2's key features including the viral "cameo" system that lets you loan your likeness to other creators, the remix functionality, and the surprisingly robust prompt editing capabilities. They demonstrate the platform's strengths (incredibly fast generation, social features, creative possibilities) and weaknesses (no timeline editor for scrubbing through footage, occasional voice mismatches, server delays during peak times).Key takeaways include practical prompting tips for better results, how to set up and optimize your cameo preferences, and why being descriptive in your prompts makes all the difference. Grant and Corey also discuss the broader implications: Is this OpenAI's answer to TikTok? How does this fit into the AI landscape where every major player now has a social platform? And most importantly - why is everyone making Sam Altman breakdance?Whether you're AI-curious or a seasoned prompt engineer, you'll learn how to navigate Sora 2's interface, avoid common pitfalls, and maybe even create your own viral AI video. Plus, find out why Corey's "realistic physique was not okay on Sora" and had to optimize his cameo settings with ChatGPT's help.➤ CHAPTERSTimecode - Chapter Title0:00 - Introduction: What is Sora 21:03 - Sam Altman is the Tom from MySpace of AI1:57 - Mobile App Tour & Social Features3:42 - Remix Feature: Editing Sam's Bedtime4:12 - The Secret to Better Prompting6:40 - Profile Features & Your Drafts8:44 - Understanding Cameos10:40 - How to Set Up Your Cameo13:00 - Optimizing Cameo Preferences with ChatGPT15:05 - Live Demo of Creating A Video18:25 - Using the Edit Feature20:09 - First Video Results23:32 - Fixing a Bad Video26:49 - Finding & Following People30:33 - Exploring Trending Videos32:50 - Why OpenAI Built a Social Platform35:34 - Training Data Implications38:00 - Voice Input and Pro Prompting Tips40:02 - The First AI-Native Social Media45:43 - Final ThoughtResources: - Sora 2 launch: https://openai.com/index/sora-2/- Download the app https://apps.apple.com/us/app/sora-by-openai/id6744034028- Sora app on the web: https://sora.chatgpt.com/exploreP.S: First comment gets an invite code. Grant has 4 atm :)