Who Is Winning The AI Model Wars?

Jyunmi hosted this pre holiday episode with Beth, Anne, and Andy, kicking off with a round robin on the most interesting AI stories from the past few days. The group moved through interactive fiction tools, Voice Mode updates in ChatGPT, OpenAI’s legal issues, algorithmic bias across social platforms, Google’s Notebook LM upgrades, and Perplexity’s surprising drop in mobile downloads. Karl joined midway, shifting the discussion toward model comparisons, real world user behavior, the gap between benchmarks and adoption, multi model workflows, and how people actually use AI at work. The episode ended with a long segment on AI reading scientific literature to discover new magnetic materials and the broader implications for science, industry, and fairness.Key Points DiscussedCharacter AI launches interactive story generation similar to yesterday’s Infinite Bard demoDisney plans to allow user generated content on Disney PlusChatGPT Voice Mode now works inside regular chats with 5.1OpenAI sued over a suicide case and responds by citing user policy restrictionsStudy shows LLMs trained on viral clickbait become persistently dumber and more narcissisticNotebook LM slide decks and infographics continue to improve with Nano BananaX’s algorithm changes and engagement drops raise concerns about visibility and biasPerplexity’s global downloads fall 80 percent after paid ads stopDebate over whether Perplexity has a unique moat or clear differentiatorGovernment unveils Project Genesis, a decade long AI driven science initiativeAWS commits up to 50B for US government supercomputing and AI infrastructureGemini 3, Claude Opus 4.5, and OpenAI 5.1 compared across reasoning, coding, and multimodal testsDiscussion on real adoption versus benchmark hype and why user habits matter moreMulti model workflows often outperform single model useAI reads 67,000 scientific papers to identify 25 promising new magnetic materialsBroader discussion on environmental impact, supply chains, discovery fairness, and scientific accessTimestamps and Topics00:00:00 👋 Opening, round robin setup00:01:03 📚 Character AI releases interactive fiction stories00:03:32 🎬 Future of AI customized films and Disney UGC plans00:04:31 🔊 ChatGPT Voice Mode now in normal chats00:06:25 ⚖️ OpenAI lawsuit response sparks criticism00:09:06 🧠 Study on clickbait trained LLMs degrading in quality00:11:10 📝 Notebook LM infographics and slide decks tested00:13:24 ⚙️ X algorithm changes and concern about creator visibility00:15:03 👥 LinkedIn gender bias issues and feed manipulation00:16:26 👋 Carl joins00:19:02 📰 Chrome based “Learn About” app from Google00:19:46 📉 Perplexity downloads drop 80 percent post ads00:21:31 ❓ Debate over Perplexity’s long term differentiation00:23:02 🔬 Project Genesis, a national AI science initiative00:27:27 ☁️ AWS 50B government AI infrastructure plan00:28:43 🤖 Gemini 3, Claude Opus 4.5, and OpenAI 5.1 model comparisons00:32:34 🧪 Benchmarks, reasoning scores, and coding performance00:38:08 📱 User adoption versus model quality00:40:35 🍏 AI model adoption compared to iPhone vs Android dynamics00:43:05 🔄 Multi model workflows as the emerging best practice00:48:38 🤝 When to use Claude, Gemini, and ChatGPT in combination00:50:26 📉 Gemini 3 significantly lowers token usage for transcripts00:52:52 🧲 AI reads decades of papers to discover new magnetic materials00:54:59 🔍 Why magnetic materials matter for EVs, energy, and supply chains00:56:39 🌱 Environmental, economic, and fairness implications01:02:34 🧠 Updating personal “brain models” and sustainability habits01:03:28 🏁 Closing and holiday send offThe Daily AI Show Co Hosts: Jyunmi, Beth, Anne, Andy, and Karl

Brian and Andy hosted this pre Thanksgiving episode and opened with platform issues, live chat glitches, and holiday energy in the air. They talked through the growing instability of their streaming setup and then shifted into the day’s news. The episode touched on the chip wars, new optical computing breakthroughs, OpenAI’s cameo trademark fight, the launch of OpenAI’s shopping assistant, Google’s Notebook LM upgrades, and Anthropic’s surprise release of Opus 4.5. The show ended with Brian demoing his Gemini powered “Infinite Bard” project and discussing why Gemini has become his default model for creative work.Key Points DiscussedMeta explores using Google TPUs, dropping Nvidia’s stock by about 4 percentResearchers show an optical computing breakthrough that rivals GPU performanceCameo wins a temporary restraining order blocking OpenAI from using the name CameoOpenAI launches a shopping assistant powered by a GPT 5 mini modelNotebook LM continues rapid improvement with Gemini 3, Nano Banana, and guided learningGemini excels in stability, fast prompting, large task reasoning, and tool buildingAnthropic releases Opus 4.5 with superhuman coding performance on SWE BenchOpus 4.5 introduces automatic context compression and major token efficiency gainsPricing shows Opus remains expensive but far more efficient than earlier versionsEnterprise users may heavily benefit from reduced token usage in agent workflowsBrian demos his Gemini “Infinite Bard” choose your own adventure engineGemini’s use of silent markdown context files enables branching story continuityTimestamps and Topics00:00:00 👋 Opening, holiday week, platform issues00:02:01 ⚙️ Meta explores using Google TPUs, Nvidia drops03:07:00 💡 Optical computing breakthrough using single laser tensor processing05:24:00 🔌 Chip efficiency and heat advantages of laser based systems06:43:00 ⚖️ Cameo wins temporary restraining order against OpenAI07:56:00 💬 Naming confusion across AI products09:11:00 🛍️ OpenAI launches interactive shopping assistant11:18:00 💻 Shopping UX walkthrough and first impressions12:19:00 📝 Notebook LM’s rapid upgrades and visual generation improvements14:01:00 🎧 Guided learning, audio overviews, and Notebook LM evolution16:02:00 🛒 Shopping assistant reasoning and laptop recommendations17:32:00 🧭 Shopping agents compared to Gen Spark and others18:53:00 🔍 Search consolidation, OpenAI’s OS ambitions20:04:00 🤖 Anthropic Opus 4.5 overview20:59:00 🧪 Superhuman coding performance on Anthropic’s hiring exam21:44:00 🧵 Context compression and unlimited conversation length22:59:00 📊 Benchmark comparison against Gemini 3 and Codex Max24:47:00 💰 Pricing for Opus, Sonnet, Haiku, and prompt caching26:05:00 ⚙️ Opus 4.5 token efficiency improvements27:27:00 🔄 Rate limits and concerns about Claude reliability32:58:00 🌐 Brian explains why Gemini has become his default model33:56:00 🎮 Demo of the Infinite Bard interactive storytelling gem35:26:00 📚 Using Gemini as a rapid prototyping engine37:21:00 🧩 Initial story branches and decision logic40:57:00 🗂️ Silent markdown files for inventory and story continuity44:51:00 🧠 Why Gemini excels at constrained creative generation47:18:00 📐 Prompt building with XML tags and gem architecture49:27:00 🧱 Using a prompt architect to build tools for tools50:14:00 📆 Upcoming holiday week schedule51:35:00 🏁 Closing and outroThe Daily AI Show Co Hosts: Brian Maucere and Andy Halliday

Beth opened episode 601 with Andy joining early and Karl arriving later. The show kicked off with browser based agents, Google’s Nano Banana expansion into Workspace, and a live demo of Slides using AI to beautify content. From there, the conversation shifted toward the limitations of Gemini generated infographics, the need for human oversight, the rise of agent powered browsers, and early signals about OpenAI’s new hardware team. The hosts explored cultural pushback against wearable AI, the gap between real world adoption and tech hype, and the long term impact of AI on management skills, jobs, and public trust.Key Points DiscussedPerplexity’s Comet agent comes to mobile with full web action supportGoogle rolls out Nano Banana AI in Docs, Slides, and Notebook LMGemini 3 image models still make factual mistakes in diagrams and labelsGoogle confirms layered image editing is on the roadmapManas launches a browser operator extension that turns Chrome into an AI agentOpenAI builds a hardware division and hires dozens of Apple engineersPublic resistance grows against AI wearables like the Friend pendantWestern media messaging reinforces AI as a threat, slowing adoptionSingapore’s AI rollout reveals a management and leadership gapHuman interpersonal skills emerge as a key competitive advantageRobotics accelerates as Google DeepMind hires Boston Dynamics’ former CTOVisionary hardware concepts likely push toward AI native devices with voice first designSora, agent tools, and multimodal models still struggle to break into mainstream awarenessTimestamps and Topics00:00:00 👋 Opening, Thanksgiving week, Andy joins01:01:00 🤖 Perplexity Comet mobile agent overview02:21:00 📝 Nano Banana comes to Google Workspace03:12:00 🎨 Slides demo with AI generated infographics05:04:00 🚗 Andy reviews Nano Banana Pro car diagrams and labeling errors08:43:00 🧩 Discussion on image limitations and lack of editable text layers11:49:00 💬 Community notes, Google confirms layered images are coming14:07:00 🧭 Karl joins, new browser operator from Manas16:00:00 🛠️ OpenAI’s hardware division poaches Apple engineers17:40:00 📱 What an AI native device might look like21:08:00 🚇 Anti AI backlash, Friend pendant ads defaced in Chicago22:52:00 🌍 Western fear framing versus Asian AI optimism24:01:00 📉 Media narratives shape public adoption and trust27:03:00 🇸🇬 Singapore as a case study in AI driven workforce disruption29:15:00 👔 Management skills become a rare and valuable human advantage33:23:00 🤝 Interpersonal skills and face to face client work outcompete automation34:59:00 🔄 AI agents cannot replace real rapport and live collaboration38:59:00 🤖 DeepMind hires Boston Dynamics CTO to build robot capabilities41:12:00 🗣️ Future devices shaped around voice first AI45:15:00 ❓ Growing public “why would you build this” skepticism48:34:00 🧩 Designing use cases that actually solve problems52:28:00 📰 Upcoming stories this week: OpenAI internal memo, Meta updates

Most creative work in the future will still have clear owners. Novels will still have authors. Films will still credit directors. Inventions will still file patents. But beneath all of that, AI models will quietly borrow from sources no one ever meant to share. A breakthrough insight might rely on the phrasing of a stranger’s blog post. A melody might carry the echo of a musician who never earned a cent. A business idea might be guided by patterns learned from millions of people who never knew they were part of the training.We already see hints of this today. People enjoy the speed, precision, and intelligence of modern AI systems, even when it is obvious that the work was shaped by countless unseen contributors. Society has a long history of accepting benefits without looking too closely at what it costs others. The saying about not wanting to know how the sausage is made has never felt more relevant.AI pushes that dilemma forward. Should society confront the uncomfortable truth that some contributions will never be credited or compensated, even when they shaped something meaningful? Or will people decide that the benefits are too important and quietly ignore who got overlooked along the way?The conundrum:As AI creates value built on invisible contributions, do we force society to face every hidden debt even when it slows progress and complicates innovation, or do we accept the comfort of not knowing in exchange for tools that make life better, faster, and easier for everyone else?

Episode 600 opened with Beth hosting solo before Andy and then Carl joined. They reflected on the show’s long run and joked about the chaotic start due to technical issues and multiple versions of the studio running at once. Beth highlighted how Gemini 3’s image creation, especially “Nano Banana Pro,” is producing highly accurate layouts with readable text. The group discussed how far multimodal models have evolved and how different tools now specialize in different strengths. The rest of the episode covered AI agents, Codex Max, Gemini prompting, SEO disruption, group chats in ChatGPT, and how users are shifting their habits across platforms.Key Points DiscussedGemini 3’s “Nano Banana Pro” creates accurate layouts and readable textProblem solving around Talk Studio bugs during the live showGen Spark hits a $1.25B valuation and expands workplace agent automationTikTok adds controls for AI generated content and labels deepfake materialUsers increasingly search how to delete or deactivate social platformsAdobe buys SEMrush, triggering worries about the future of SEO toolsSEOs struggle because AI search results are personalized, inconsistent, and agent drivenCodex Max improves complex backend builds, Gemini excels at front end and multimodal workNew ChatGPT group chats allow shared sessions across teams and free usersPRDs become essential for scoping apps before coding with agentsAdvice on using Cursor, Codex, Gemini CLI, Cloud Code, and avoiding multi tool conflictsOpenAI launches free ChatGPT access for verified K 12 educatorsTimestamps and Topics00:00:00 🎉 Opening, episode 600, first solo start00:02:44 👋 Andy joins, discussion on Nano Banana Pro image accuracy00:04:50 🖼️ Gemini layout and multimodal strengths00:07:00 💻 Gemini Pro for image generation and model selection00:09:34 🤖 Gen Spark’s $275M round and workplace agent capabilities00:12:03 🛠️ How Gen Spark automates complex workplace tasks00:14:24 🧩 Agent platforms vs built in agents in big model ecosystems00:15:21 🧭 How users may lean on ChatGPT for end to end work00:16:58 🔀 Technical chaos navigating multiple Talk Studio instances00:19:40 🗞️ TikTok labeling AI content and user decline across platforms00:21:58 👥 New ChatGPT group chats demo and quirks00:28:36 📝 OpenAI gives teachers free ChatGPT with integrations00:32:32 🔍 SEO disruption as AI search becomes personalized and inconsistent00:34:26 📉 Adobe buys SEMrush, concerns about tool decline00:38:40 🤖 AI agents change how users perform search and comparison00:40:58 🎯 Codex Max vs Gemini 3 for coding, strengths differ by task00:45:49 🧪 Why building simple test apps matters before real projects00:50:16 🔧 Using Gemini for front end and Codex for complex backend logic00:52:41 🧠 Avoiding tool conflicts when coding across multiple IDEs00:56:03 🛠️ Cursor recommended as the unified working environment01:02:44 📂 Importance of GitHub when switching across platforms01:06:59 🏁 Closing, weekend content reminders

Brian and Andy hosted episode 599 and opened by looking back on how far the show has come. They talked about the Daily AI Show as a living archive that captures the state of AI day by day. They joked about submitting the series to the Library of Congress and reflected on the value of having a long running record of AI progress. The episode then moved into major news topics, new model upgrades, compute constraints, Gemini 3 prompting techniques, product strategy at OpenAI, and the growing divide between research priorities and consumer AI features.Key Points DiscussedNvidia posts a record $57B quarter, up 62 percent year over yearOpenAI launches GPT 5.1 Codex Max with context compaction and major coding gainsGemini 3 shows strong prompting upgrades, faster thinking mode, and smart memory handlingAmazon adds new AI recap features and enhanced NFL viewing modes to Prime VideoPerplexity revamps its AI shopping experience ahead of Black FridayFiji Simo becomes OpenAI’s new leader for applications and monetizationOngoing compute shortages create rate limits across major modelsMixing models becomes a theme, using Gemini, Codex, Claude, and Grok for different strengthsSuno and Audio make major funding and licensing moves in AI generated musicDebate over AI music hits as an AI generated country song reaches number oneTimestamps and Topics00:00:00 🔁 Reflection on 599 episodes, the show as an AI time capsule00:04:54 📈 Nvidia posts a record $57B quarter00:07:00 🧩 GPT 5.1 Codex Max and the compaction breakthrough00:09:50 ⚙️ Gemini 3 memory tricks, Python intermediates, and large task workflows00:12:10 🐢 Model slowdown at high token counts and manual compaction methods00:14:30 🙌 Carl joins, discussion on 600 episodes00:15:06 📺 Prime Video’s AI recaps and AI enhanced NFL broadcasts00:17:56 🛒 Perplexity’s holiday shopping updates00:20:33 🧿 Fiji Simo becomes CEO of Applications at OpenAI00:25:21 🧮 Compute constraints and why research gets priority00:27:37 🧠 Yann LeCun’s research first philosophy00:31:17 📚 Alpha Archive and the need for AI focused research repositories00:34:31 🧱 Andy and Carl on Energy Gravity and coding workflows00:36:50 🔧 Model specialization and mixing models for better outcomes00:45:06 🎶 Suno’s $250M raise and Audio’s new music licensing deals00:47:27 🎤 Creative backlash vs audience preference00:48:35 🎵 Brian plays AI generated music covers00:50:46 📣 Weekend reminders, Gem Architect, Slack community00:51:32 🏁 Closing and tomorrow’s 600th episodeThe Daily AI Show Co Hosts: Brian Maucere, Andy, and Karl

Jyunmi opened the show for episode 598 with Andy and Brian, setting up a news heavy Wednesday focused on Gemini 3 and how it changes prompting and agent design. Before diving into Gemini 3, they covered major moves from Nvidia, Microsoft, Anthropic, and Alibaba, plus new tools from Poe and Replit.Key Points DiscussedNvidia reports earnings and deepens its partnership with Microsoft and Anthropic, including new chip work tuned for Claude.Microsoft unveils a sales development agent and an agent command center to track official and shadow agents across 365.Alibaba launches the Qwen consumer chatbot to compete in China’s crowded assistant market and push deeper ecosystem integration.Poe adds group chat for up to 200 users with any model, and Replit ships a new design feature powered by Gemini 3.Google formally launches Gemini 3, wires it into search, the Gemini app, and introduces the anti gravity coding environment.Brian tests Gemini 3 and finds that it prefers a single large prompt over router style prompt chains.Gemini 3 introduces an objective based commander intent approach with a prime directive and clear success criteria.The team walks through new Gemini 3 prompting patterns, including phases instead of steps, deep reasoning loops, and source of truth rules.Negative constraints and quality gates become core tools to prevent sloppy outputs and premature phase changes.Brian builds a Gem Architect that helps users design strong Gemini 3 gems using this new prompting style.He then uses that architect to create a DOS page builder gem that turns show transcripts into SEO ready HTML deep dives.Andy explains the difference between the Gemini app and Google AI Studio, and how AI Studio is shifting toward full application projects.Brian shares how the community can access his Gem Architect prompt and gem inside The Daily AI Show hub.Timestamps & Topics00:00:00 💡 Intro, episode setup, and agenda00:01:05 💰 Nvidia earnings and Microsoft Nvidia Anthropic mega deal00:04:31 🧑‍💼 Microsoft sales development agent and agent command center00:09:20 🌏 Alibaba’s Qwen consumer chatbot and China price war00:12:29 🧑‍🤝‍🧑 Poe group chat and Replit design feature with Gemini 300:15:34 🤖 Gemini 3 launch, search integration, and anti gravity overview00:17:13 🧱 From router prompts to mega prompts in Gemini 300:22:09 🧭 Objective based commander intent prompting rules00:26:07 ✅ Negative constraints, quality gates, and phase based flows00:29:03 🏗️ Gem Architect builder for Gemini 300:31:30 📰 DOS page builder gem for Daily AI Show deep dives00:39:37 🧪 Anti gravity install, hardware notes, and first impressions00:41:36 🛠️ Finding the AI Studio playground and model options00:44:53 🧩 Gemini app versus AI Studio and when to use each00:54:36 🌐 Community hub, prompt sharing plans, and closingThe Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Jyunmi Hatcher, and Karl Yeh

Brian and Andy opened the show reacting to Gemini 3’s release, noting how quickly Google pushed it out after weeks of leaks. They framed the episode around three big storylines: Gemini 3 going live, the Prometheus project finally confirmed, and a wave of world model announcements across the industry.Key Points DiscussedGemini 3 officially launches with big jumps in reasoning, vision, and real time grounding.Google positions Gemini 3 as a direct competitor to GPT 5.1 and Claude 3.7.Early tests show major improvements in planning and tool use, but hallucinations still appear in edge cases.Jeff Bezos backs the Prometheus physical AI project, aiming to merge robotics, sensors, and world models.Elon Musk announces Grok 4.1, claiming large upgrades in memory and multi step reasoning.Nvidia reveals Apollo, a physics aligned world model intended for robotics and simulation.Debate over whether world models will replace Transformers or merge into hybrid systems.Anthropic updates Claude to improve tool calling and reduce slowdowns seen over the last week.New research shows world model agents may outperform LLM agents in long horizon tasks.Discussion on AI ecosystems pulling away from single model usage and toward fully integrated systems.Timestamps & Topics00:00:00 💡 Intro and Gemini 3 launch00:04:22 🤖 First reactions to Gemini 3 performance00:09:48 ⚙️ Tool use improvements and early benchmark noise00:13:40 🔍 Comparing Gemini 3 to GPT 5.1 and Claude00:17:22 🚀 Prometheus project confirmed with Bezos backing00:21:11 🤝 Robotics, sensors, and world model integration00:26:34 🔧 Grok 4.1 announcement and memory upgrades00:30:18 🧠 Nvidia Apollo and physics aligned world models00:35:42 🔬 World model agents vs LLM agents00:41:00 📉 Claude slowdown issues and Anthropic fixes00:47:29 🌐 Shift from single models to integrated ecosystems00:54:10 🏁 Wrap up and preview of midweek topicsThe Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

Brian and Beth opened the week talking about post-travel exhaustion, holiday timing, and the usual Monday scramble before diving into the fast-moving AI news cycle. They framed the episode around two big topics: Gemini 3 and GPT 5.1, both expected to shape the competitive landscape going into the end of the year.Key Points DiscussedGemini 3 hype grows as leaks point to a major leap over 2.5 Pro.Nate Jones claims Google may take the top spot for model quality for the first time.Benchmark saturation makes performance harder to judge, so real workflow testing now matters more.Concerns rise about switching costs as models continue to leapfrog each other.Discussion on Kimi, DeepSeek, and recycled media hype around “low cost” training claims.GPT 5.1 rollout improves instruction following and reduces jargon, but shifts may break existing custom GPT setups.Issues with user preferences, model selection, and memory overriding developer-built instructions.Prediction that custom GPTs and Gems may evolve into more structured, code-like agents built through vibe-coding style interfaces.Exploration of how ecosystems (Google, Microsoft, OpenAI) may soon matter more than the standalone model.Sakana AI becomes the most valuable private company in Japan.Reflection on how quickly the AI industry has changed public visibility for figures like Jensen Huang.Conversation on enterprise-grade update cycles and the future of agent maintenance.Apple expected to benefit from Gemini integration as Siri gets significantly stronger with minimal user friction.Timestamps & Topics00:00:00 💡 Monday kickoff and holiday timing00:03:07 🤖 Gemini 3 expectations and early leaks00:05:49 🔍 Google catching OpenAI for the first time00:08:02 🧪 Benchmark saturation and real-world testing00:10:16 🔄 Switching fatigue and user lock-in00:11:22 📉 Kimi, DeepSeek, and misleading training cost narratives00:15:15 ⚙️ GPT 5.1 updates and instruction-following improvements00:18:12 🧩 Problems with custom GPT triggers and file handling00:19:41 🔧 Skill-building workflows with Claude vs GPT 5.100:22:56 🔗 Tool clutter and connector issues in ChatGPT00:23:28 🧠 Google Gemini integrations and AI Studio00:24:57 🃏 Gemini 3 hype and online exaggerations00:27:22 🧬 Microsoft’s superintelligence lab and safety stance00:28:10 👤 Public persona shifts in the AI industry00:33:17 🚀 Sakana AI becomes Japan’s highest-valued private company00:37:25 🧠 Future of custom GPTs and vibe-coded agent systems00:43:04 🔐 Persistent memory challenges for developer-built tools00:52:40 🗂️ Agent-based onboarding and learning systems00:55:07 🌐 Full-ecosystem advantage for Google00:56:53 📱 Apple expected to benefit from Gemini-powered Siri01:00:02 🧩 The real competition is the ecosystem, not the model01:01:14 🏁 Wrap-up and after-show banterThe Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

Shared entertainment has always shaped how people connect. Families once gathered around a single television. College friends planned their week around a show everyone watched at the same time. Movie theatres turned an audience into a temporary community. Even when streaming arrived, the biggest stories still found ways to bring people together for premieres, finales, and cultural moments.AI will not replace that. Big films, concerts, and live events will still matter. But side by side with those experiences, AI will offer something new. It can generate long form movies or albums that match your taste perfectly. You do not wait for them. You do not compromise with anyone. They are delivered instantly, shaped around your favorite pacing, themes, and emotional patterns. It is entertainment that fits like a glove, and it will be hard not to reach for it.As people start to mix both worlds, an uncomfortable tension appears. Tailored stories scratch the immediate itch and feel more rewarding minute to minute. Shared stories ask more from you. They take longer. They do not always match your preferences, yet they create the moments larger than yourself.The conundrum:If AI gives us instant entertainment that feels perfect, will we still choose the slower, shared experiences that once helped us feel connected to something bigger, or will the pull of personal comfort slowly reshape what we show up for? And if our habits shift over time, what happens to the cultural moments that rely on many people choosing the same story at the same time?