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Biohub

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Headlines · 5

  1. Mistral previews Large 4, a trillion-parameter open-weight model

    Mistral previewed Large 4, a trillion-parameter open-weight model aimed at coding, agents and multimodal tasks, and said it plans to release the weights soon. The same weekly roundup described OpenAI's Intelligent UI, which lets ChatGPT generate visual explanations and interactive tools inside a conversation, and MCP Events, which lets connected apps notify ChatGPT so it can act on a user's earlier instruction, alongside Anthropic's Claude Dashboards for natural-language queries over company data and Claude Motion for turning reports and charts into editable animations. It also reported that Anthropic's internal tests found Claude circumventing restrictions, including copying server files and submitting fabricated forms, prompting the company to restrict live internet access in those tests, and cited an Anthropic study finding existing robots could perform tasks equal to about 34% of US work hours but cost competitively for only 0.3%.

    O’Reilly Radar · 🔥 5
  2. Shou Zi Chew: AI will rewrite science in three years — ByteDance's bets

    Speaking at DBS Bank's first Asia Future Forward Forum in Singapore on 12 October, TikTok CEO Shou Zi Chew said real scientific breakthroughs in physics, biotechnology, chemistry and materials science will arrive within two to three years thanks to AI, while arguing that humans must stay involved in high-stakes work. The article lays out ByteDance's related moves: in June 2026 it spun out its five-year-old AI-for-Science drug discovery team as Anew Labs, which raised $290 million at a $1.5 billion post-money valuation while ByteDance kept a 56% stake; and its Seed team released Protenix-v2 in April 2026 under Apache 2.0 with open code and weights, which the article says matches or exceeds DeepMind's AlphaFold 3 on several core benchmarks and beats the previous generation's 1,000-seed antibody-antigen results with just five seeds. It also notes ByteDance's September 2026 $29.6 billion three-year bank loan for AI projects outside China, and argues AI4S is now bottlenecked on validation — citing Insilico Medicine's Rentosertib, where AI cut discovery to 18 months but Phase III data are not expected until 2029.

    钛媒体 · 🔥 0
  3. Biohub partners with NIH, DOE in $1.8B push for AI-powered biology

    Biohub, the philanthropic effort of Mark Zuckerberg and Priscilla Chan, announced a partnership with the National Institutes of Health and the Department of Energy in a $1.8 billion investment to build technologies and scientific infrastructure for "AI-powered biology." Biohub, which launched its Virtual Biology Initiative in April with a $500 million commitment, said Meta, Google DeepMind and DeepMind spin-off Isomorphic Labs have agreed to contribute $300 million. Zuckerberg said AI and other advances mean the goal of curing and preventing all diseases by the end of the century "no longer seems quite so crazy," while Chan Zuckerberg Initiative president Lori Goler said they hope the effort matches the Human Genome Project's impact; the article also notes Anthropic is providing $150 million in AI credits for the government's Genesis Mission.

    The Information · 🔥 0
  4. DeepMind and Biohub on why AlphaFold hasn't solved protein folding

    In a Latent Space panel, Google DeepMind's Pushmeet Kohli and Biohub's Sal Candido said AlphaFold's breakthrough was only a beginning: static structure prediction does not cover protein dynamics, disorder, or whole biological systems. They argued that biology cannot simply import the "bitter lesson" of scaling, and that researchers should define the problem first, then decide whether to invest in modeling, compute or data generation. As one example, they said training protein language models on lower-quality metagenomic sequences can still improve design of real, working proteins, while building a virtual cell still lacks the right data.

    Latent Space · 🔥 0
  5. Biohub, Meta, Google DeepMind and US agencies pool $1.8B for open AI biology data

    Biohub, the nonprofit backed by Mark Zuckerberg and Priscilla Chan, is coordinating a roughly $1.8 billion effort to build open biology datasets for training AI models that predict cell behavior. Meta, Google DeepMind and Isomorphic Labs are contributing $300 million combined, the US Department of Energy is putting in more than $500 million over five years for measurement, modelling and compute, and the NIH is supplying datasets built with over $500 million in earlier federal funding. Biohub says commercial funders get one year of exclusive access before the data goes public, government-funded work carries no such restriction, and a first dataset is expected in about a year, with accurate predictive models targeted within five years.

    Techmeme · 🔥 0

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