AI in Design and Creative Work
AI tools for design, writing, video, music, games, content production, creative teams, and human-AI creative workflows.
Figma’s CEO Says AI Makes Average Work Easier to Ignore
Figma co-founder and chief executive Dylan Field argues in a Hard Fork interview that AI is not killing design so much as making average work cheaper and more abundant. Field’s case is that writers, designers and software makers will be judged less on their ability to produce a first draft or prototype than on whether they can give it a distinctive voice, point of view and level of craft. He expects design work to broaden rather than disappear, even as AI labs push further into application software.
AI’s Creative Promise Is Moving People From Consumption to Authorship
In a closing reflection at Shared Futures: The AI Forum, Patrick J. McGovern Foundation president Vilas Dhar argued that AI’s creative significance should be judged less by what machines can produce than by whether they help people recover agency as makers. Drawing on performances from the forum and a childhood memory of communal singing in India, Dhar framed the risk as passivity: a culture in which creativity is professionalized, distributed and consumed rather than shared. His cautious optimism was that AI could widen participation if it gives people without technical skills new ways to write, sing, build and imagine.
Flows Agent Turns Creative Briefs Into Editable AI Production Pipelines
ElevenLabs presents Flows Agent as a conversational assistant for building and revising node-based creative workflows inside ElevenCreative Flows. The company’s case is that a user can describe an ad or other asset in natural language, have the agent assemble the models, prompts, nodes, and connections, then keep the resulting pipeline visible for edits, approvals, and reuse. The demo emphasizes cost controls for credit-heavy generation, node-level revisions through chat, and templates that turn a completed flow into a repeatable production system.
AI Distrust Makes Human Agency the Central Cultural Question
Opening Shared Futures: The AI Forum, Vivian Schiller of Aspen Digital and Vilas Dhar of the Patrick J. McGovern Foundation argued that public distrust of AI is not an obstacle to the conversation but its starting point. Schiller framed AI as a contested tool that can either feel imposed on people or be used by artists and makers with agency; Dhar said the deeper issue is not the technology itself, but how people turn fear of replacement into meaning, art, and shared experience.
Snap’s Specs Face a Public-Market Test After Years of AR Spending
On Diet TBPN, John Coogan and Jordi Hays used Snap’s new Specs as the clearest case for a broader skepticism: technically strong demos do not answer whether a company can create demand, an ecosystem, or a rational return on capital. They argued that Snap’s AR work might look fundable as a startup but is harder to defend inside a public company whose stock has fallen sharply and whose core ads business could be run more profitably. The same standard shaped their read on Taste Labs, AI export-control fights, and SpaceX’s valuation: the hard question is whether impressive capability can be converted into durable business control.
ElevenMusic Lets Creators Publish Tracks to Explore and Earn After 11,000 Streams
ElevenLabs presents ElevenMusic as an AI music platform where discovery, remixing, publishing, and earning are meant to operate as one loop. The source argues that creators can turn a lyric, melody, mood, or existing track into publishable music, place it on the Explore page for others to stream or remix, and use audience response to guide further work. It also makes the monetisation path conditional: creators must subscribe to Pro, meet an 11,000-stream threshold, and satisfy the platform’s royalty terms before earning from listens.
Dubbing v2 Preserves Speaker Performance Across 90-Plus Languages
ElevenLabs presents Dubbing v2 as an AI dubbing model designed to transfer a speaker’s performance across more than 90 languages, not just translate the words. The company argues that by conditioning on the original audio rather than a transcript, the system can preserve voice, tone, emphasis, emotion and timing while adapting phrasing for natural delivery in the target language. The walkthrough positions the tool as an automated localization workflow for creators, marketers and studios, with speaker similarity as the main setting users adjust between voice resemblance and native-language naturalness.
Codex Turns Campaign Briefs Into Editable Marketing Assets
OpenAI’s demo presents the Creative Production plugin for Codex as a campaign-production workflow for marketing teams, rather than a standalone image generator. Using a fictional Maison Feve chocolate launch, the company shows Codex turning a brief into mood-board directions, revised visual treatments, display-ad variants and an editable Canva handoff. The argument is that marketers can use Codex to carry campaign context through concepting, asset generation and final production edits in one working thread.
ElevenMusic Turns Music Discovery Into AI Remixing and Prompted Creation
ElevenLabs presents ElevenMusic as a music platform that begins with discovery and turns listening into creation. The onboarding shows users moving between Explore, where they can browse and remix tracks from more than 4,000 independent and emerging artists, and Studio, where they can upload material or generate new tracks from prompts. Its central argument is practical: the main user skill is not production technique but writing a specific musical brief that gives the model enough genre, mood, instrumentation, vocal, and energy cues to produce a closer result.
ElevenLabs Adds Studio and Flows Agents to Automate Creative Production
Luke Harries used ElevenLabs’ Warsaw summit to argue that AI creative production is moving beyond prompt-based asset generation toward agent-directed workflows. Presenting ElevenCreative, he introduced Studio Agent and Flows Agent as layers above models and editing tools, intended to help teams ideate, script, prompt, edit, localize, and reuse campaigns. His case was that marketers’ role shifts from executing each production step to directing and approving systems that can produce hero assets, performance variations, and localized creative continuously.
Sanders’ 50% AI Stock Plan Turns Training Data Into a Political Fight
Jason Calacanis argued that Anthropic’s call for an AI slowdown and Bernie Sanders’ proposal for public ownership of major AI companies show AI politics moving toward jobs, ownership and redistribution. He dismissed Sanders’ 50% stock-tax plan as unworkable but said its premise could resonate with voters who believe AI companies built enormous value from public and creative inputs while threatening employment. Yoland Yan’s ComfyUI demo supplied the production-layer version of the same control question, presenting generative AI as a workflow where exposed parameters and reproducibility matter more than prompt-box convenience.
Tool-Call Repairs Let DeepSeek v4 Beat Opus 4.7 in Internal Evals
Ahmad Awais, founder of CommandCode.ai, argues that many open models appear weak at coding-agent work because the harness around them mishandles tool schemas, design instructions and user preferences. Drawing on Command Code’s internal logs and evals, he says small deterministic repairs to tool inputs helped DeepSeek v4 Pro beat Opus 4.7 in six of ten internal comparisons. His broader case is that “taste” — explicit contracts for tools, design patterns and developer habits — can narrow the gap between cheaper open models and frontier coding systems without changing the model itself.
ComfyUI Bets on Open-Source Control for AI Video Workflows
Despite its Anthropic-titled hook, the source’s developed argument is about product interfaces that give users more control over complex systems. ComfyUI co-founder Yoland Yan argues that serious AI video creators need open, node-based workflows rather than simplified freemium tools; INTVL founder Louis Phillips makes the case for turning tracked routes into contested fitness territory; and the fact-checker bounty highlights live verification as a control layer for streamed claims.
Codex Product Design Plugin Turns Rough Prompts Into Shareable Prototypes
OpenAI presents its Product Design plugin for Codex as a workflow for turning an early product prompt into a reviewable prototype, using a proposed ChatGPT calendar feature as the example. The source argues that the plugin’s value is not in replacing product judgment but in forcing constraints, generating alternative directions, and then converting a selected direction into interactive software, Figma context, and a shareable Sites deployment.
NVIDIA RTX Spark Recasts Windows PCs as Local AI Agent Machines
NVIDIA chief executive Jensen Huang used his GTC Taipei keynote to present RTX Spark as the basis for a new class of Windows PCs built around personal AI agents. His argument was that the PC needs an abstraction layer comparable to the one that made the original Windows ecosystem work: existing applications, CUDA workloads and games still run, but large language models and agent runtimes become part of the operating environment.
Microsoft Bets Enterprise Agents Will Run Through the Cloud
John Coogan reads Microsoft Build 2026 as a sign that Microsoft is trying to make the cloud, not the phone, the center of enterprise AI agents. On Diet TBPN, he argues that Project Solara, Scout, OpenClaw support and Microsoft’s own models point to a platform strategy built around Azure, Microsoft 365 data, security boundaries and cost-efficient deployment rather than frontier-model supremacy. The open question, he says, is whether agent hardware and workflows can win adoption outside environments where companies can mandate them.
Useful AI Systems Are Emerging Inside Controlled Enterprise Workflows
TBPN’s latest discussion framed the commercial AI moment less as a race to looser autonomy than as a shift toward bounded systems. Across Microsoft’s Build announcements, Suno’s funding, creator films, stablecoins, crypto markets, cybersecurity, and workflow software, the central argument was that AI becomes useful when it is embedded in infrastructure that can price, route, audit, secure, or constrain it. John Coogan and guests applied that lens most directly to Microsoft’s agent strategy, where Azure and Microsoft 365, not a new phone, become the controlled operating environment for enterprise agents.
Public-Market Capital Is Becoming an AI Infrastructure Advantage
TBPN’s John Coogan and Jordi Hays use Alphabet’s reported $80bn equity raise, Berkshire Hathaway’s investment and a run of founder interviews to argue that AI is pushing capital markets and operating infrastructure back to the center of technology strategy. Their case is that the advantage is moving to companies that can finance enormous compute buildouts, unify fragmented data, own service businesses where AI can be deployed, and build the physical systems — from data centers to space logistics — that make AI useful.
RTX Spark Agent Moves Architectural Designs From Brief to Photoreal Render
NVIDIA’s RTX Spark demonstration argues that an architectural AI agent is most useful as a workflow operator, not as a standalone design tool. Running locally on RTX Spark and connected to tools including Rhino, Blender, ComfyUI, OpenShell and Claude Sonnet, the agent turns a residential brief into massing options, editable layouts, validated geometry and photoreal renders. NVIDIA frames the speedup as orchestration across existing applications, with the designer still approving directions, resolving tradeoffs and controlling materials and shots.
YouTube Is Becoming Hollywood’s Talent Market and IP Proving Ground
TBPN’s John Coogan and Jordi Hays argue that YouTube is moving from Hollywood competitor to Hollywood’s talent market, where creator-led films prove creative judgment, production ability and audience response before studio capital arrives. The episode extends that pattern to AI policy, software and prediction markets: established institutions are trying to absorb signals formed outside their usual channels, from internet-proven filmmakers and frontier AI labs to traders and startups testing demand before regulators, studios or public markets have settled their response.
NVIDIA Positions RTX Spark as a 128 GB Local AI Workstation
NVIDIA’s Computex preview positioned RTX Spark as a compact Windows platform for local AI, creative production and RTX gaming, built around a new superchip pairing a Blackwell RTX GPU with a Grace CPU. Jacob Freeman and other NVIDIA presenters argued that its 128 GB of unified memory and RTX acceleration allow slim laptops and small desktops to run larger local agents, handle heavy creative scenes and support modern ray-traced games with DLSS 4.5.
A Two-Hour AI Prototype Let Museum Visitors Talk to Statues
Joe Reeve of ElevenLabs argues that his “talk to a statue” prototype mattered less as a museum product than as evidence of what can now be assembled quickly from existing AI APIs. Built in Cursor in about two hours, the app identifies a photographed statue, generates historical context and a plausible voice, spins up an ElevenLabs agent, and starts a conversation in roughly 30 seconds. Reeve says the harder remaining questions are institutional rather than purely technical: who authors the object’s story, what voice it should have, and how multimodal voice interfaces should work.
Pope Leo XIV’s AI Encyclical Ties Safety Rules to Human Dignity
A panel convened by Aspen Digital treated Pope Leo XIV’s first encyclical, Magnificent Humanity, as an authoritative Catholic intervention in AI governance rather than a narrowly theological text. Kim Daniels, Vilas Dhar, and Josh Good argued that the document judges AI by its effects on human dignity, especially for workers, students, creative professionals, and vulnerable communities, while pointing to safety regulation, retraining, and education as practical tests. The unresolved problem, Daniels said, is whether the Church can move that teaching from Rome into parishes, civic institutions, classrooms, and technology work.
ElevenLabs Music v2 Adds Section Editing and Mid-Track Genre Shifts
ElevenLabs’ launch walkthrough for Music v2 presents the model as a more controllable generative music system, not only a higher-quality one. Alec Wilcock says the new version improves vocals, instrumentation, arrangement, multilingual output and dense vocal delivery, while adding section-by-section composition, targeted inpainting and the ability for one song to move between genres without losing coherence. The company also says the model is trained on licensed data and that generated tracks are cleared for commercial use.
ElevenLabs Says Dubbing v2 Preserves Performance Across 90 Languages
ElevenLabs is introducing Dubbing v2 alpha as an AI dubbing model built around preserving the original speaker’s performance, not just translating a transcript. The company says the system conditions directly on source audio so tone, pacing, emphasis and emotional delivery can carry across more than 90 languages, with sync-aware translation adapting phrasing to fit the timing of the original. ElevenLabs is positioning the launch for creators, marketers and studios that want automated localization without building a separate dubbing pipeline.
ElevenLabs Adds Licensed Stan Lee AI Voice to Creator Tools
ElevenLabs is introducing an approved AI replica of Stan Lee’s voice through a partnership with Stan Lee Universe, positioning the late comic-book creator as a licensed feature inside its voice and creator tools. The company says users can request to license Lee’s voice for projects, hear it in Eleven Reader, generate Stan Lee cameos, and use Stan-inspired music, while repeatedly framing the launch around official authorization, rights ownership, and Lee’s mythology of stories being carried forward.
ElevenLabs Launches Music v2 for Licensed Commercial AI Song Generation
ElevenLabs is presenting Music v2 as a licensed-data AI music model built to generate vocal-led tracks from detailed natural-language prompts, not just loops or backing beds. The launch materials argue that the model can produce finished-sounding, one-shot outputs across styles and languages, while adding workflow features such as targeted inpainting, section-by-section composition, and deployment through ElevenMusic, ElevenCreative, and a forthcoming ElevenAPI.
Useful AI Agents Need Smaller Contexts and Simpler Representations
Angus McLean, an AI Director at OLIVER, argues that useful agents are not the most autonomous ones but the best constrained. Drawing on OLIVER’s production use of AI across thousands of daily creative assets, he says builders should resist both model and developer tendencies toward verbosity and over-engineering: use curated documentation instead of open web access, ask how little context a task needs, choose simple representations such as HTML when they work, and avoid automating jobs they cannot do themselves.
Google’s GenAI Stack Turns Multimodal Prompts Into Application Pipelines
Google DeepMind’s Paige Bailey and Guillaume Vernade argue that Google’s generative AI stack is being organized as an application pipeline rather than a set of isolated models. In a three-hour workshop, Bailey showed AI Studio turning multimodal Gemini prompts into inspectable API calls and generated apps with auth and Firestore, while Vernade used Gemini, Nano Banana, Veo and Lyria to illustrate, animate and score The Wind in the Willows. Their case is that builders can now orchestrate prompt, code, media generation and deployment in one workflow, even as the demos exposed seams that still require engineering discipline.
ChatGPT Adds In-PowerPoint Drafting and Editing for Business Decks
OpenAI presents ChatGPT for PowerPoint as an embedded drafting and editing layer for business presentations, now available in beta to all customers. The source argues that the tool is meant to turn scattered company material — notes, account context, market research, prior deck fragments and analysis files — into a structured executive deck inside PowerPoint, with the user reviewing the storyline before generation and refining slide content afterward. Its claim is less that ChatGPT can make slides from a prompt than that it can keep the source material, outline, draft and edits in one workflow.
AI Demand Broadens Beyond Hyperscalers Into Software, Devices and Space
Ivan Feinseth, chief investment officer at Tigress Financial, argued on Bloomberg Technology that the AI investment case is already broader than the hyperscale capex cycle and the next wave of AI IPOs. He pointed to Microsoft’s Azure and Copilot revenue, Adobe’s underrecognized AI content tools, Garmin’s health-and-wellness devices and SpaceX’s long-duration space story, while cautioning that AI-native IPOs may draw strong initial demand but will still have to prove themselves as public companies.
AI’s Bottlenecks Shift From Model Demos to Compute, Rights, and Institutions
AI, in TBPN’s latest discussion, is no longer treated mainly as a product demo but as a question of infrastructure, financing and institutional adoption. The strongest evidence came from SpaceX’s AI-heavy IPO framing, Anthropic’s reported move toward operating profit, and OpenAI’s claimed Erdős breakthrough, which the speakers used to challenge the “AI is a scam” critique. The unresolved issue is not whether the technology matters, but how quickly compute capacity, rights regimes, regulation and existing institutions can absorb it.
Gemini Omni Flash Replaces Veo as Google’s Default Video Model
ElevenLabs’ breakdown of Google’s I/O 2026 launch presents Gemini Omni as a major reset of Google’s AI video stack, with Omni Flash already replacing Veo as the default video model in the Gemini app. The source argues that the significance is not just better text-to-video generation, but a shift toward multimodal, conversational video creation: users can combine text, images, audio, video, and reference photos, then revise clips through successive instructions while preserving characters and scenes.
Google’s AI Assets Are Becoming a Product Coherence Problem
John Coogan and Jordi Hays read Google’s I/O as evidence that the company’s AI advantage is becoming a product-navigation problem: it has data, distribution, models and hardware partnerships, but its demos and product names left questions about coherence and pace. Across the source, that same pressure appears in more operational forms, as AI pushes companies to turn technical capability into usable workflows, secure software dependencies and faster product systems. Tae Kim’s Nvidia argument and the expected SpaceX IPO make the capital-market version of the question explicit: whether investors will keep paying for scarce infrastructure, extreme scale and growth curves that may take years to prove out.
AI’s Value Is Shifting From Model Demos to Distribution and Measurement
Google’s problem at I/O, Jordi Hays argued, was no longer proving that its AI models are impressive, but making Gemini useful rather than redundant across products investors now increasingly view as part of a full-stack AI business. The TBPN discussion extended that framing across the rest of the show: AI’s value, the hosts and guests argued, depends less on model spectacle than on distribution, workflow integration, economics and adoption by institutions. That distinction ran from Google’s risk of crowding users with Gemini entry points to SendCutSend’s physical capacity constraints, Commure’s push to automate healthcare administration, and METR’s effort to turn frontier-model risk into something auditable.
ElevenLabs Adds Albert Einstein’s Voice to Its Licensed AI Marketplace
ElevenLabs is offering a licensed AI version of Albert Einstein’s voice through its Iconic Marketplace, positioning it for narration, education, documentaries, and immersive storytelling. The company argues that Einstein’s voice can be used as both a cultural artifact and a creative tool, while saying the marketplace is curated and that each voice is approved and managed with the relevant rights holder.
Gemini Becomes the Prompt Engineer for Google’s Gen Media Stack
Google DeepMind developer advocate Guillaume Vernade demonstrates a gen-media workflow built around Gemini as the orchestrator rather than as a one-shot generator. Using The Wind in the Willows, he shows Gemini reading the full book, producing structured prompts and scripts, and handing them to Nano Banana, Veo, Lyria and TTS models for images, video, music and narration. His broader case is that multimodal production depends less on a single model than on schemas, reference assets, state management, cost controls and prompt handoffs between specialist systems.
GPT Image 2 Beats Nano Banana 2 on Control, Not Speed
ElevenLabs’ side-by-side test of GPT Image 2 and Nano Banana 2 argues that the models are complementary rather than interchangeable. Across more than 20 generation and editing prompts, the comparison found GPT Image 2 stronger when briefs required tight prompt control, text hierarchy, layout discipline, and source fidelity, while Nano Banana 2 more often won on speed, 4K cost efficiency, fine detail, and polished editorial transformations. The practical recommendation is to route work by failure risk — and A/B test important prompts — rather than pick a single default model.
AI Competition Shifts From Models to Chips, Power, and Supply Chains
Bloomberg Technology framed the latest AI race less as a contest over individual products than as a fight over infrastructure constraints, from Nvidia chip export politics and U.S. semiconductor labor to cloud spending, energy, memory and data-center capacity. Ed Ludlow, Caroline Hyde and Bloomberg reporters treated Donald Trump’s discussion of Nvidia’s H200 chips with Xi Jinping as emblematic of that shift: significant for markets, but short of any clear export deal. The program’s interviews with Goldman Sachs’ Eric Sheridan, OpenAI CFO Sarah Friar and Figma CEO Dylan Field similarly argued that compute, distribution and ownership of the stack are becoming the decisive limits on AI growth.
Figma Says AI Makes Design More Valuable as Code Gets Easier
Figma CEO Dylan Field told Bloomberg that the company’s stronger-than-expected quarter shows AI is expanding rather than undermining its market. He argued that as large language models make code easier to generate, design becomes the more valuable layer above it — while acknowledging that AI features carry real inference costs that Figma is now trying to monetize through usage credits.
AI Tools Are Moving Creative and Software Work Toward Specification
TBPN’s discussion uses Debater Center, AI-generated Monet-style clips, Cursor, Figma and a 67-year-old AI founder to question whether tech labels describe what is actually happening underneath. The speakers argue that ranked debate software may need an audience to create the performative pressure people associate with online debate, while AI tools such as Luma and Cursor are shifting creative and technical work from manual execution toward higher-level specification. Their shorter points on Figma and the older founder make the same corrective move: they resist premature obituaries for products, skills and founder archetypes that are still active.
Images 2.0 Moves Image Generation From Novelty to Workflow Tool
OpenAI product lead Adele Li and researcher Kenji Hata argue that Images 2.0 marks a shift from novelty image generation to a working visual layer inside ChatGPT. In a podcast discussion with Andrew Mayne, they point to 1.5bn images generated weekly, sharper text rendering, stronger photorealism, broader aspect ratios and more consistent characters as evidence that the model is moving into education, internal communication, marketing assets, software mockups and other practical creative work.
ElevenCreative Adds Templates for Reusable AI Creative Workflows
ElevenLabs is introducing Templates in ElevenCreative, a feature that turns its node-based Flows into reusable creative workflows with defined inputs and outputs. The company presents the tool as a way to run repeatable production tasks — such as product shots, mockups, style transfers, character sheets, and thumbnail translation — without rebuilding the workflow each time. Users can run templates from a gallery or publish their own, choosing which variables others can edit, what asset is returned, and whether access is private, workspace-only, or public.
Suno Bets That Making Songs Can Become a Mass Consumer Medium
Suno founder and CEO Mikey Shulman argues that AI music should not be understood as a cheaper substitute for streaming catalogs, but as a new form of active consumer entertainment. In a conversation with Sequoia’s Sonya Huang, he says Suno’s technical choices — modeling raw sound, prioritizing full songs, and using preference data rather than conventional benchmarks — support a product thesis that making music can be as much the point as listening to it. Shulman also frames partnerships with labels such as Warner as central to building new participatory music formats, not as a concession to incumbents.
Condé Nast Plans for a Media Business Beyond Search Traffic
Condé Nast chief executive Roger Lynch argues in a TBPN interview that publishers should plan for a media market in which search traffic is no longer a reliable foundation and generic AI content is not a defensible advantage. His case is that brands such as Vogue and The New Yorker can become more valuable if they rely on direct audience demand, subscriptions, events, editorial authority and human-reported work, while using AI mainly to make product and technology teams faster.
AI Companies Are Running Into Infrastructure, Distribution, and Trust Bottlenecks
TBPN’s discussion argued that AI’s value is now being tested less in model demos than in the bottlenecks around deployment: inference speed, power, workflow integration and access to customers. Cerebras was framed as a public-market bet on faster inference, while Giga Energy’s data-center business showed how scarce powered shells have become part of the AI supply chain. The same bottleneck logic appeared outside core AI, from Audemars Piguet using Swatch as an official low-cost entry point to Augustus, with conditional OCC approval, trying to rebuild dollar clearing as a national bank.
Certainty, Convenience, and Optimization Can Become Substitutes for Living
Mark Manson, the writer and author, argues that people stay lost less because they lack information than because they use certainty, convenience, optimization and advice-seeking to avoid contact with reality. In a wide-ranging conversation with Chris Williamson, Manson’s case is that growth usually comes through friction: tolerating uncertainty, choosing the costs attached to the life you want, accepting a partner’s ordinary Tuesday as well as their best moments, and acting before more insight becomes another form of procrastination.
Travel AI Needs Visual Agents, Not Chatbot Booking Flows
Airbnb chief executive Brian Chesky argues that today’s AI chatbots are the wrong interface for travel and e-commerce, even as AI becomes central to how Airbnb operates. In a live TBPN conversation, Chesky said consumer AI’s next wave will depend on richer, more visual and collaborative agentic products, not text-first chat boxes or another round of enterprise software. He also tied Airbnb’s recent growth reacceleration to more hands-on “founder mode” management, saying AI makes operating intensity more important rather than less.
Prediction-Market Scandals Spur Calls for Insider-Trading Rules
Hard Fork’s Kevin Roose and Casey Newton argue that prediction markets have entered a more dangerous phase, with recent scandals showing how liquid event-betting platforms can reward insider knowledge, manipulation and even national-security breaches before regulators have caught up. The episode broadens that concern into a larger question about technologies whose incentives are outrunning public rules, through Joanna Stern’s year-long test of AI in daily life and Rachel Cohn’s reporting from a Brooklyn school trying to resist the commodification of attention.
ElevenLabs Shows Voice Isolator Cleaning Noisy iPhone Audio in Seconds
ElevenLabs presents Voice Isolator, a tool inside ElevenCreative, as a fast way to salvage noisy recordings that cannot be reshot. In the tutorial, the company demonstrates a single workflow on an iPhone recording made on a London street: upload or drag in the file, click send, and play back an isolated voice track. The presenter says the street noise is removed and the file is processed within nine seconds, while interviews, podcasts, social clips, audio files and video files are named as broader use cases.
Airbnb Is Rebuilding Around Identity, Not Homes, for AI
Airbnb’s challenge in the AI era is less a feature rollout than a company reinvention, chief executive Brian Chesky argues in a conversation with Patrick O’Shaughnessy. Chesky says the company has to move beyond a business still identified mainly with homes, rebuild around identity and personal preferences, and do so without damaging a large public platform that hosts and investors depend on. His answer is a more hands-on operating model: fewer abstraction layers, smaller elite teams closer to users, continuous recruiting, and a CEO directly engaged with the work.
Luma Is Rebuilding Video AI Around a Unified Multimodal Transformer
In a Stanford CS153 guest lecture, Luma AI co-founder and chief executive Amit Jain argues that generative video is only a staging point toward “unified intelligence”: models that understand and generate across text, images, video, audio, code and tools in a single work loop. Jain traces Luma’s path from Apple-era LiDAR and 3D capture to internet-scale video, saying the company followed the data but now sees prettier clips as insufficient. The destination, he says, is a multimodal AI factory for professional creative and physical work, where human skills, tool use, feedback and unified transformer architectures produce full campaigns, schematics, productions and eventually robotics workflows.
Descript Bets Creator AI on Reliable Editing, Not Content Slop
Laura Burkhauser, Descript’s chief executive, distinguishes generative AI tools for creators from the “slop” she defines as mass-produced content arbitrage. Her case is that Descript’s future depends less on adding AI everywhere than on making editing automation reliable, reversible and useful for recorded human media. That means choosing third-party models by fit and taste, building in-house systems where Descript has workflow data, and treating creator backlash as a product constraint rather than a branding problem.