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All news · Today8 items

#Expert views

All collected and published items, ordered by time. Picks are a selected subset.
10/13Tue
  3. Alexandr Wang · X32

    Alexandr Wang Posts “MUSE WONDER”

    🍉 MUSE WONDER 🍉 @hdubugras says Alex and Meta are on a roll, and that the model has replaced Astra/Opus in a variety of their workflows. They say it handles day-to-day tasks efficiently and quickly, and offer congratulations. Alexandr Wang’s reaction: “🍉 MUSE WONDER 🍉”

  11. Alexandr Wang · X19

    MUSE WONDER 🍉 muse wonder is the best model in the world for personal agents and professional agents. we evaluated our model against the best models in the world across agentic and coding tasks, and we think you all will like it.

    MUSE WONDER 🍉 muse wonder is the best model in the world for personal agents and professional agents. we evaluated our model against the best models in the world across agentic and coding tasks, and we think you all will like it.

  12. TechCrunch · AI49

    Microsoft’s Brad Smith says the U.K. is best placed to lead AI regulation

    Microsoft President Brad Smith called for urgent global AI safety rules, arguing that the U.K. is better positioned to lead than the U.S. or European Union. He said voluntary self-regulation lets responsible companies comply while leaving less responsible ones a concern. Smith supports legal breach reporting for rogue AI agents and spoke positively about outside evaluations before release and kill switches to pause or slow AI systems.

10/12Mon
  2. Josh Woodward · X48

    Josh Woodward shares praise for Lenny ahead of their interview

    I’ve learned from Lenny for years, but we had never met. What you see is what you get with him: he’s kind, prepared, and deeply curious. Great interviewers do their homework, and you can tell he’s in that league: he took our conversation to places that I’ve never talked about in public. Enjoy the first 60 minutes of us getting to chat together. Thank you @lennysan !

  3. The Decoder59

    Andrej Karpathy describes a widening gap in how people experience AI capabilities

    Andrej Karpathy describes four tiers of LLM exposure, arguing that public perceptions lag behind capabilities experienced by frontier-system users. He estimates roughly six billion people have barely encountered LLMs, one to two billion use casual chatbot products, 20 million use frontier models professionally in math and code, and 5,000 access internal frontier systems. He claims those internal systems coordinate thousands of agents on projects that would take experts years, while human review falls behind, and attributes progress in coding and math to reinforcement learning on verifiable rewards and commercial training priorities.

  5. 宝玉 · X26

    Bao Yu Wonders Whether He Fits AI Startups’ Hardest-to-Hire Role

    Bao Yu describes a role AI startups reportedly find difficult to hire for: someone who follows online trends, creates engaging content, understands AI and technology, and executes well. He says content creators, technical evangelists and engineers, and traditional PR staff each tend to lack some of those abilities, while few people have all four.

  6. 宝玉 · X58

    Anthropic’s Claude Subscription Rules Appear Looser, but Amp’s Status Remains Unclear

    Baoyu says Anthropic appears to have relaxed restrictions on Claude Agent SDK and claude -p usage, but has made no public statement specifically addressing Amp or guaranteeing against account bans. Quoted author Quinn Slack interprets a policy update from 2 days ago and Anthropic employee comments as allowing SDK and third-party apps to use subscription allowances, citing https://support.claude.com/en/articles/15036540-use-the-claude-agent-sdk-with-your-claude-plan and https://news.ycombinator.com/item?id=49997143. Baoyu recounts earlier restrictions and says Anthropic paused its planned June 15 switch to separate billing for Agent SDK and claude -p.

  8. 雷锋网38

    Former DeepRoute AI Executive Liu Nianqiu Says Mapless Driving Experience Can Transfer to Robots

    Femo One founder Liu Nianqiu says experience moving DeepRoute AI from high-definition maps to mapless driving can inform the company’s approach to robots, which he calls “Physical Agents.” Femo One is focused on open, dynamic environments and plans to begin deployments at multiple sites next year, building a cycle of deployment, data collection, training and redeployment.

  9. 宝玉 · X57

    Satya Nadella argues enterprises should treat AI models as insider risks

    Baoyu summarizes Microsoft CEO Satya Nadella’s argument that enterprises should manage AI models as insider risks, with identities, restricted permissions, audit records, and controls to halt operations. Nadella outlines seven principles covering model diversity, observability, verification, independent control and auditing, containment, and incident disclosure. He calls for disclosing chains of thought while acknowledging that they may not faithfully reflect model reasoning, and argues that security controls must operate outside the model.

  10. Ethan Mollick · X32

    I spoke to some annoyed leaders at big firms who were still big on GPTs as of last month, before GPTs were sunsetted. Yes, GPTs outlived their usefulness. But large organizations have complex planning & all the Labs (not just OpenAI) keep making sudden changes that confuse them.

    I spoke to some annoyed leaders at big firms who were still big on GPTs as of last month, before GPTs were sunsetted. Yes, GPTs outlived their usefulness. But large organizations have complex planning & all the Labs (not just OpenAI) keep making sudden changes that confuse them.

  11. 宝玉 · X22

    Toyota's Kaizen Rule Applied to AI: Don't Cut Staff After Efficiency Gains

    A Japanese blogger cited Toyota's Kaizen rule — never cut staff after process improvements reduce work hours — and argued the same applies to AI adoption. Companies that cut headcount as soon as AI boosts efficiency will find employees hide their best AI methods, he said. A quoted post adds that DORA research found organizations addressing employee job concerns had higher team AI adoption.

  12. 宝玉 · X62

    Karpathy Says the LLM Capability Gap Is Becoming a Funnel

    Andrej Karpathy argues the gap in shared understanding of LLM capability is widening into a sharp funnel: roughly 6B people have barely touched LLMs, 1-2B use free-tier chatbots casually, about 20M use frontier models for math and code, and roughly 5,000 have internal access to frontier systems. He attributes the funnel to problem ambition, capability jaggedness in verifiable domains, and access tiers.

  14. Andrej Karpathy · X34

    Karpathy: LLM Capability Gap Is Widening Into a Sharp Funnel

    Andrej Karpathy says the gap in shared understanding of LLM capability is widening into a "sharp funnel" rather than two groups talking past each other. He estimates roughly 6B people have barely encountered LLMs, 1-2B use free-tier ChatGPT-like products casually, about 20M see frontier-grade math and code use, and roughly 5,000 have internal access to frontier systems. He attributes the funnel to impact scaling with ambition, the jaggedness of capability, and access tiers.

10/11Sun
  2. TechCrunch · AI38

    PolyAI and Otter Executives Say Voice AI Hasn’t Had Its ChatGPT Moment

    PolyAI CTO Shawn Wen says voice AI still needs faster reasoning to make conversations feel natural, even though full-duplex models can speak while listening. Otter CMO Alex Gay says accurate transcription, language understanding, and expressive voices matter for enabling automation and building trust. Both executives also stressed that voice AI tools should tell people when they are talking to AI or being recorded.

  3. 量子位62

    Terence Tao Says AI Proofs Mark the Arrival of Mathematics 2.0

    Terence Tao argues that AI is making mathematical proofs abundant, ending a Mathematics 1.0 era built on proof scarcity. He warns that solving problems is not the same as understanding them, calls for reporting failed attempts and compute costs, and says the bottleneck for Mathematics 2.0 is imagination. He also questions whether a PhD still matters when answers come easily.

  4. The Decoder36

    Nadella Adopts Trump's "Super Intelligence" Term, Attacks OpenAI and Anthropic

    Microsoft CEO Satya Nadella used "Super Intelligence" instead of "Artificial Intelligence" in a new blog post, echoing President Trump's preferred terminology. Nadella argued AI models should be treated like insider security threats, calling for model diversity, complete logging, independent auditing and human shutdown ability, while criticizing Anthropic and OpenAI. The Decoder reports the rebranding breaks with decades of scientific meaning and that Nadella's arguments serve Microsoft's business strategy.

  5. The Decoder40

    Cheaper AI tokens are driving more demand, and that's Jensen Huang's best-case scenario

    Data from Ornn, Silicon Data, and Bloomberg as of August 2026 shows what a16z calls a textbook Jevons paradox in the AI market: token prices keep dropping while H100 GPU rental prices hold steady or climb. Cheaper tokens unlock AI agents, automation, and new applications, so volume grows faster than per-unit costs fall. The system depends on AI usage growing fast enough to offset falling token prices; if demand flattens, chip makers, memory suppliers, energy providers, and cloud companies take a hit.

  6. The Verge · AI48

    Nadella says we should assume all AI models are 'compromised'

    In a lengthy post on X, Microsoft CEO Satya Nadella argued that highly advanced AI models pose dangers that require new safeguards, saying "we must assume a model is compromised and contain it from the start." He called for an "emergency brake" that lets an authorized person pause or shut down a model mid-task, plus timely incident disclosure, independent audits, verifiable data, and containment.

  8. TechCrunch · AI41

    Microsoft's Satya Nadella says AI models need an 'emergency brake'

    Microsoft CEO Satya Nadella called for an "emergency brake" on AI models, writing in a Saturday morning post on X that it's time "to step back and assess the trust architecture" of AI. He proposed separating the model from the harness that orchestrates its work, externalizing controls and safeguards, documenting every meaningful model action with "tamper-proof human readable evidence," and giving an authorized person the ability to pause or shut down a model mid-task.

  11. Nathan Lambert · X33

    Nathan Lambert Sees Investment in RL Data and Real-World Evaluations

    Nathan Lambert says the data industry has grown, but low-quality output can amplify behaviors such as reward hacking. He is advising Mercor on research into sample-efficient data for RL and says the field needs stronger evaluation science and benchmarks tied to areas of clear economic value. Lambert expects major investment around frontier labs in open inference, open post-training and data, with opportunities to build on open models.

10/10Sat
  1. Satya Nadella · X44

    Satya Nadella Says AI Models Should Be Treated as Insider Risks

    Satya Nadella argues that frontier AI models should be treated as insider risks and surrounded by deterministic controls, because their behavior can be difficult to trace and they may have access to sensitive data and mission-critical actions. He calls for separating intelligence from authority, keeping access and action controls outside the model, and building systems around model diversity, observable activity, and continuous testing.