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All news · Today8 items

#Expert views

All collected and published items, ordered by time. Picks are a selected subset.
10/15Thu
  5. Alexandr Wang · X49

    Alexandr Wang Reviews Muse Wonder Full

    @davis7’s review says Muse Wonder Full has good writing and “voice,” capabilities on par with 6.1 sol for non-specialized tasks, and orchestration. It lists the naming scheme and price and usage limits as cons, and says the full model is available in Muse Code through a subscription, with no API. Alexandr Wang called it a thoughtful review, said there is lots to improve, and was glad people enjoy using the model. https://twitter.com/davis7/status/2110533786895356118

  7. Ethan Mollick · X30

    I think people believe that OpenAI and Anthropic, since they are so good at AI, are also somehow not normal companies that suffer from the normal problems of hypergrowth, but they are not immune from the inevitable politics, disfunction and confusion that haunt fast-growing firms

    I think people believe that OpenAI and Anthropic, since they are so good at AI, are also somehow not normal companies that suffer from the normal problems of hypergrowth, but they are not immune from the inevitable politics, disfunction and confusion that haunt fast-growing firms

  10. TechCrunch · AI41

    Ricursive Intelligence Is Developing AI to Design More Efficient Chips

    Ricursive Intelligence is developing AI that designs chips, learns from each iteration, and improves later designs to automate and accelerate chip design. At TechCrunch Disrupt, founders Anna Goldie and Azalia Mirhoseini said AI can find unconventional layouts and optimize entire chips; they cited a “donut-shaped” arrangement produced by their earlier system, AlphaChip. Goldie said demand for compute could grow at least 10,000x in the next five years.

  12. Latent Space60

    Crossing the Threshold: How OpenAI and Anthropic Approach Autonomy and Safety in Financial Agents

    Speakers from OpenAI, Anthropic, Two Sigma, and Bloomberg at AI Engineer New York described how financial agents can gain autonomy through targeted controls and human oversight. OpenAI’s Joseph Kim predicted agents could handle investment idea generation and trading in 2027, while Anthropic illustrated an agent that proposes order amendments for human approval. Two Sigma described classifiers that route important requests to people, and Bloomberg advocated deterministic controls outside the model, including tool-call checks, audit logs, and kill switches.

  14. Latent Space67

    Ian Quigley Explains Leash Bio’s Data Methods and Lab-in-the-Loop Agent Research

    Brandon Anderson interviews Leash Bio’s Ian Quigley about generating reproducible protein–small molecule interaction data using DNA Encoded Libraries and detecting misleading signals in experiments and models. They discuss a Kaggle competition with about 4B measurements where nobody beat chance on an unseen chemical library, and an agent sandbox searching 6.5M molecules on a budget of 100. Anderson reports that the sandbox has matured into Minos, with a preprint, blog, and open dataset being released today.

  17. Aravind Srinivas · X40

    Aravind Srinivas says America is the market to build for

    America is the market to build for 🇺🇸 More than 50% of our users who spend money on Automations (recurring agentic tasks) or on the higher tier plans are American. Net dollar retention for an American self serve business onboarded on agents is consistently high https://twitter.com/mollysoshea/status/2110118882102890524

  21. The Verge · AI54

    My AI doppelganger tells me what to eat

    Victoria Song reviews roughly 100 days with Twin Health, an AI digital twin program that predicts glucose responses to food using personal health data and continuous glucose monitoring. She reports improved labs, including triglycerides dropping by 70mg/dL, but no meaningful weight loss or hoped-for success reducing medications; some lab values were already improving before the program. Human coaching helped motivate exercise, while extensive tracking caused fatigue and raised questions about privacy and trust in higher-stakes medical uses.

  23. Ethan Mollick · X49

    Ethan Mollick Questions the Purpose of Anonymous AI Slop Comments

    I really don’t understand the point of the AI slop comments flooding my posts. At least on LinkedIn they are pushing fake expertise to make their posters look good (it doesn’t, but whatever). But what is gained by dozens of anonymous bots making similar replies to posts like this? https://t.co/rM8ywQCrwA

10/14Wed
  2. Alexandr Wang · X35

    Alexandr Wang Says Muse Wonder Is Fast and Token-Efficient

    @merge_api says Muse Wonder completes an average task in 6.8 minutes, compared with 13.2 minutes for Claude Opus 5.5 and 15.3 minutes for Claude Sonnet 5.5. The quoted post says the scores are 52.4, 57.6, and 56.0, respectively. Alexandr Wang calls Muse Wonder “super fast and token efficient” and says, “give it a go!” https://twitter.com/merge_api/status/2110385332046762163

  5. Clément Delangue · X19

    Very cool to see Embedding Gemma 2 by @Google, number on trending on HF! The media and silicon valley bubble only talks about reasoning LLMs when there is a much bigger variety of AI models that are super impactful and useful like embeddings, decision models, audio, video, time-series,... (over 3M public models on HF!). Let's put them back in the spotlight!

    Very cool to see Embedding Gemma 2 by @Google, number on trending on HF! The media and silicon valley bubble only talks about reasoning LLMs when there is a much bigger variety of AI models that are super impactful and useful like embeddings, decision models, audio, video, time-series,... (over 3M public models on HF!). Let's put them back in the spotlight!

  12. François Chollet · X31

    The ideal outcome for science isn't a couple of labs using proprietary models and millions of dollars to crack trophy problems, it's to have millions of AI-aided human scientists who follow their curiosity and become way more ambitious

    The ideal outcome for science isn't a couple of labs using proprietary models and millions of dollars to crack trophy problems, it's to have millions of AI-aided human scientists who follow their curiosity and become way more ambitious

  15. Ethan Mollick · X15

    Hey, AI give me your best "Unless it is from X, its just sparkling Y" style joke": GPT-6 Pro: "Unless it comes from the Stockholm region of Sweden, it’s just sparkling employee engagement." Gemini 4 Argon High: "Unless it comes from the 3:00 AM region of staring at the ceiling,

    Hey, AI give me your best "Unless it is from X, its just sparkling Y" style joke": GPT-6 Pro: "Unless it comes from the Stockholm region of Sweden, it’s just sparkling employee engagement." Gemini 4 Argon High: "Unless it comes from the 3:00 AM region of staring at the ceiling,