Nima Alidoust

Introducing Tahoe-x1 (Tx1) by @tahoe_ai. A 3-billion-parameter, single-cell foundation model that learns unified representations of genes, cells, and drugs, achieving state-of-the-art performance across cancer-relevant cell biology benchmarks, open-sourced on @huggingface. 🧵

Context

Number of whatsapp threads in which individual power users are announcing their exodus from Claude Max 20x: 8 so far ... And these are Claude die-hards.

Today @Recursive_SI emerges from stealth to build self-improving superintelligence. Founded by @RichardSocher, @_rockt, @jeffclune, @timshi_ai, @tydsh, @CaimingXiong, Alexey Dosovitskiy & @josh_tobin_, @aixventureshq backed them from day one. The company is building AI that safely improves itself, in an open-ended process of automated scientific discovery. Read more in the @nytimes: nytimes.com/2026/05/13/tec…

I’ve traveled in the last weeks to a few places where the AI bug has not spread wildly yet (funnily New York is one of them). What surprised me: outside Bay Area, most communities are yet to grasp the power of AI and the speed it is improving. What that mea: simply adopting emerging capabilities is a massive edge (at least in the short term).

@mobav0 :))

Stochastic gradient descent

Feature request from @Spotify : automatic reduction of playback speed when it detects @pmarca speaking.

What you are pointing out here has a simple implication, often overlooked: it won't be inference from a single model that builds conviction around a target. It is reasoning (partly relying on inference from that model) that can / may lead to conviction. Thinking of virtual cell models as the panacea is the problem. And casting them as "world models" miss the point.

AI for Bio is hot again. Given that, I wrote a primer on why this field is so hard. tl;dr it's because the APIs are fuzzier than you might think. ankitg.me/blog/2026/05/0…

I had almost entirely moved on from podcasts (some exceptions); but @dwarkesh_sp episodes in the last few months and the serious exchanges have been a pleasure to listen to. If you haven’t, you should listen the recent ones with @michael_nielsen and Terence Tao. Great scaffolding for how to think about AI in science.

We will look back and see this as the start of a wonderful accelerator. And we @tahoe_ai are committed to building alongside these great orgs.

@alexrives Wonderful news for the field. Congrats @alexrives and the team!

Scaling laws are powering AI. It’s time to scale biology. Today we’re launching the Virtual Biology Initiative to generate the data to unlock scaling laws in biology and build accurate predictive models of the cell. Digital representations of proteins are already expanding our understanding of life at the molecular level, and accelerating the design of molecules and medicines. Accurate digital representations of the cell could reveal the mechanisms that are responsible for disease, and show how to reverse them. The protein data bank, and worldwide repositories of protein sequence biodiversity were created through decades of work by the scientific community. The advances in artificial intelligence for proteins would not have been possible without them. The cell is orders of magnitude more complex, and we will need to create the data in just a few years rather than decades. This will require a coordinated global effort. We're partnering with Broad, Wellcome Sanger, Arc, Allen, Human Cell Atlas, Human Protein Atlas, NVIDIA, and Renaissance Philanthropy. Biohub is contributing to this effort as both a funder and a builder. We are developing microscopy to observe millions of cells in living organisms, and cryo-ET to resolve the cell in atomic detail. We're building instruments that expand the range of modalities and parameters that can be simultaneously measured. We’re developing molecular, cellular, and tissue engineering to create models of disease and design interventions. The data we generate will be available to the worldwide scientific community. We’re also committing $100M over the next five years to support work beyond Biohub. We invite other scientific teams and funders to join. Link: biohub.org/news/virtual-b…

This is so amazing to see! @tahoe_ai's Tahoe-100M at the top of the list of Scientific Datasets on HF!

@genophoria @huggingface :)))

@nalidoust @huggingface I said the same thing not too long ago 😀

Super excited about the launch of Hugging Science by @huggingface. And even more thrilled that Tahoe-100M is top downloaded dataset across all datasets.

@davey_burke @arcinstitute 💙

@arcinstitute is hiring a CTO. It may be the most important technical role in biology right now - and here's why I'm the one posting it. This summer I'm transitioning from CTO to Strategic Advisor. When I left Android 18 months ago, I said I wanted to use AI to accelerate drug discovery. Joining Arc was how I put that into action - and the team has delivered: frontier AI x Bio models like Evo, STATE, and STACK, AI research agents like scBaseCount, the Virtual Cell Challenge, a TED Audacious grant, and world-class compute. Given what my family has been through these past few years, a full-time operational role isn't the right fit right now. The mission still is, which is why I'm staying close as an advisor. Thanks to @skonermann, @pdhsu, and @patrickc for their partnership. We need a cracked ML and technical leader - mission-obsessed, ready to architect the future of science. DMs open. arcinstitute.org/jobs/cto

💙

@zavaindar Why is the low switching cost necessary for that conclusion?

given the low switching costs for gen code + the provably massive TAM + the nonlinear returns to incremental r&d it’s hard to not see generative software + autoresearch not being entirely solved in the next 5 years the stakes too high, the talent to dense, the returns too real

@michellearning Would be a pleasure. And I’d love to see the lab. Grand ambitions meeting grand execution!

@nalidoust Thanks for coming, we have to get you on a panel for next year

UNLOCK2026 was something like a labor of love for the AIxScience community. One founder told me it was the best event he’s attended since starting his company 8 yrs ago. Another said it felt like JPM 2.0 🤯 If you missed it, we’ll be sharing videos next week. Stay tuned.

@parmita Mmm.. the acquired weren’t even doing drug design.

A $400M dollar acqui-hire is NOT going to make Anthropic win in life sciences. It is the same thing as every other company: they need DATA, not DRUG DESIGN.