Andrei Tyrin

We’ve built autoresearch for liquid handling and cut robot cycles by more than 30%. Link in reply.

Today we're launching free-energy perturbation (FEP) on Rowan! Using Rowan FEP, scientists can predict how tightly a potential drug will bind to a target, allowing teams to explore ligand modifications without having to wait for synthesis. Here's what this looks like:

@onepot_ai is always looking for Ш and Ж shaped engineers. T was never enough.

LLMs revolutionized software creation. The software we ship? Not as much. The moment we ship software, we freeze it. What if software evolved with your needs? Introducing Mana, an AI-native OS. Mana is a personal OS that understands the context of your life. It remembers what matters to you, creates personal apps for your needs, and evolves them as your needs change, growing in lockstep with you. Not software you adapt to. Software that adapts to you. Mana is built from four primitives: - A cloud filesystem so it can remember - A code execution sandbox so it can act - A realtime UI renderer so changes become real interfaces - And an LLM with access to it all. It not only creates apps but also acts as an assistant on top of every app you build. This makes everything in Mana feel alive: - Your todo list knows what's inside it - You can talk to your analytics dashboard and change what it tracks - You can make a multiplayer game in a party in 60 seconds Creating apps becomes as easy as creating markdown files.

OnePot just released a paper / blog post describing CORE, the enumerated chemical space they discussed in this interview. If you've been looking for more details on their technology, check it out! onepot.ai/core

Wildly cool. In the age of AI, design-make-test-analyze in drug discovery is bottlenecked by “make.” onepot's AI chemist picks routes + conditions, runs synth→HPLC→QC, and learns via ML feasibility. Totally automated! 3.4B molecules across 7 reactions. As fast as 5 days!

Today on Rowan's blog, I interview @daniil_boiko and @andrei_tyrin from @onepot_ai. onepot is a startup "making small molecules faster and cheaper" with lab automation and ML. They recently raised $13M from @fiftyyears @khoslaventures @speedinvest @JeffDean @woj_zaremba + others. I quite enjoyed this conversation because: - I've known these two for some time and deeply respect them - Readers of my blog will know that I'm also a skeptic of lab automation - And both Daniil and Andrei are quite funny rowansci.com/blog/automatin…

Announcing onepot — making small molecules faster and cheaper Read more at onepot.ai/announcement

Valthos builds next-generation biodefense. Of all AI applications, biotechnology has the highest upside and most catastrophic downside. Heroes at the frontlines of biodefense are working every day to protect the world against the worst case. But the pace of biotech is against them: more powerful methods to design biological systems, with near-universal access, open up an increasing surface area of threats. In this new world, the only way forward is to be faster. So we set out to build the tech stack for biodefense. Our team of computational biologists and software engineers applies frontier AI to identify biological threats and update medical countermeasures in real-time. We are backed by $30M from @OpenAI, @Lux_Capital, @foundersfund and others including @Definition_Cap. We are actively hiring engineers to join in the mission - if that sounds like you, get in touch.

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Code: github.com/Ananikov-Lab/d… Paper: pubs.rsc.org/en/Content/Art… Co-authors: @daniil_boiko, Nikita Kolomoets, @AnanikovLab (6/6)

Analyzing total syntheses, we found human synthetic strategies differ notably from natural biosynthesis by analyzing strychnine molecules. Modern methods prioritize atom economy, whereas nature uses flexible “ascent–descent” strategies to diversify molecules. (5/6)

Excited to share our work published in @ChemicalScience, where we digitize molecular complexity — a fundamental but elusive concept in chemistry — by formulating it as a ranking problem! (1/6)

the ones that come to mind are - organic chemistry by Jonathan Clayden - probabilistic machine learning (2 parts) by @sirbayes - intro to the theory of computation by Michael Sipser

carefully written textbooks are underappreciated in the modern world

@CorinWagen @RowanSci @aigrant @manntis4 congrats, Corin!

Thrilled to share that @RowanSci is a part of @aigrant batch 4! (We haven't done much model-building work publicly yet, but this will change soon... thanks @manntis4)