Thomas Vetterli retweeted
We’re thrilled to share that Lamin is now generally available! With just a few clicks, anyone can create a database on lamin.ai
In 2022, we set out to build an open-source data management tool that’d make it easier to scale AI workflows in the life sciences. Over the past few years, we’ve served research labs and enterprises of all sizes with what used to take a dozen tools:
- Data lineage
- Format-agnostic lakehouse
- Notes, ELN, LIMS, ontologies
- Versioning, branching
- Data lake, catalog
- Agents, workflows, notebooks
- Feature store, MLOps
With Lamin, it’s just Postgres and storage in a Python package, plus an optional GitHub-like web platform.
Give it a try: pip install lamindb
Thanks to @_DimensionCap and @ycombinator and many others who made this possible
Thomas Vetterli retweeted
We raised a $40M Series A to build the automated lab for agentic biology.
Last week, we shared the work we did with @Anthropic: Claude designed proteins, sent them to our automated wet lab, and got real experimental data back.
We believe this is where biology is going: AI agents designing experiments, running them in automated wet labs, learning from the results and iterating.
But AI can only move as fast as the experiments behind it. To use the potential of AI to cure all diseases, we need to build high-throughput wet lab infrastructure: a “biological gigafactory”.
That’s exactly what we’re doing at Adaptyv.
Over the past year we’ve grown our lab throughput by over 5x and onboarded more than 100 customers, ranging from bio AI labs like @chaidiscovery and @boltz_bio to pharmas like @Roche and @novonordisk to dozens and dozens of new startups that use AI to radically speed up drug discovery.
Thomas Vetterli retweeted
We released our first public model: t0-alpha.
t0-alpha is a foundation model for time-series forecasting. It can handle predictive variables, which is important to optimize the context for what you are predicting.
It is Apache 2.0, so check it out!
If you'd rather play with it in your browser, no setup required: checkout app.retrocast.com.
Download it here -> huggingface.co/theforecastin…
Today we’re proud to be releasing t0-alpha, our first public forecasting model.
t0-alpha is a 102M-parameter transformer built for time-series forecasting, released under Apache 2.0.
huggingface.co/theforecastin…
Thomas Vetterli retweeted
Come build the world's largest factory for protein data.
We're hiring across engineering, biology, automation, AI, and operations to help us scale.
AI has solved software. Biology is the next frontier.
We're hiring across every team at Adaptyv.
We’ve built the best automated lab for protein designers to experimentally test their AI-designed proteins. Today, the most advanced protein design companies run their wet-lab work on Adaptyv, from the biggest biopharmas to frontier AI labs to dozens of virtual biotech startups.
Demand has grown faster than we have, so we’re hiring across the board:
• Bio: Research associates, scientists and lab technicians to develop and run new assays at scale.
• Lab automation: Engineers and interns to onboard new lab instruments and scale our automation infrastructure.
• Software: Product and backend engineers to scale LabOS, our internal lab orchestration platform, our API for agents and the data pipelines that turn messy physical-world data into clean results.
• Partnerships, customer success and operations: Building partnerships with AI & pharma labs, making sure customers understand their data and can run more campaigns, making sure the company operations run smoothly
Thomas Vetterli retweeted
Can AI agents autonomously design proteins?
We gave some AI agents access to protein design models and let them make binders to an Alzheimer’s drug target. Then we tested the designs in our wet lab - turns out the agents did pretty well actually, almost matching human protein designers on hit rates and maximum affinity.
GPT5.2 and grok_4.1_fast did best among the agents
Excited for the future of autonomous drug design :)
What happens when you let frontier LLMs design proteins, and then synthesize and test them in a wet lab?
We ran a protein design competition with @muni_bio where AI agents competed against humans to design molecules that bind TREM2, a key receptor linked to Alzheimer’s.
Results: GPT 5.2 and Grok 4.1 both placed in the top 5, with molecules showing strong binding to TREM2 when tested in our lab.
Thomas Vetterli retweeted
News! @airstreet has raised $232,323,232 for Fund III to back AI-first companies from the earliest stages in the US and Europe.
Now the largest solo GP venture firm in Europe.
Our third epoch begins today. Join us!
Thomas Vetterli retweeted
I haven’t been here much recently, but it seems it’s still the place to be for a lot of ML stuff.
So: at @forecastingco we’re an applied research lab building the full stack for temporal data manipulation.
Thomas Vetterli retweeted
𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗧𝘄𝗶𝗻 — 𝘁𝗵𝗲 𝗔𝗜 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝗯𝘂𝗶𝗹𝗱𝗲𝗿.
No setup. Secure. Infinitely scalable.
We just raised a $𝟭𝟬𝗠 𝘀𝗲𝗲𝗱.
After a beta with 𝟭𝟬𝟬,𝟬𝟬𝟬+ 𝗮𝗴𝗲𝗻𝘁𝘀 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱, we’re now opening to everyone.
RT and comment “Twin” — first agents on us. 👇
Thomas Vetterli retweeted
The results of the Nipah Protein Design Competition are out!
🧬 1200 proteins experimentally validated (3x more than last year)
📈 99 novel binders against the target protein (a challenging tetramer with little prior work)
💪 26 single digit nM or better binders, with the best ones at single-digit picomolar affinity!
All data now available open-source on Proteinbase!
Let's take a look at the results ⬇️
Thomas Vetterli retweeted
🌍 The biggest decentralized science experiment of 2025 is starting now!
The protein design competition returns: we’re inviting scientists, engineers, and hackers from around the world to help design new proteins capable of neutralizing the Nipah virus, a pathogen with up to 75% mortality and no effective treatment.
All you need is a laptop to participate: submit your computational protein designs, and @adaptyvbio will synthesize and experimentally test 1,000 of the most promising proteins, with all results released open-source on @proteinbase.
Thomas Vetterli retweeted
Today we’re releasing real-world experimental data for over 1000 novel AI-designed proteins on our new platform @proteinbase!
Thomas Vetterli retweeted
🤓 i'm running an ai usage survey for the @stateofai
the results will be open sourced with the State of AI Report in october '25
it takes 10 mins and i want to hear from everyone, regardless of their level of expertise and usage
head to stateof.ai/survey
thanks!
Thomas Vetterli retweeted
Wooop! Episode 3 of Europe's Most Ambitious Startup is here!! 🇪🇺🔥
This time, I am visiting a company in Berlin that's hell-bend to become the world's #1 inventor of modern materials using robotic labs and AI.
Their first mission?
Tackle climate change by generating better catalysts used for pretty much every important process towards net-zero. But ultimately the sky is the limit and even materials in your future phones might be based on top of their discovery.
We go live inside their office and lab and see what they do. How it works and talk with their founder Alex and Marcus how they plan to 200x the world's output in material discovery!
Dunia AI – Europe's Most Ambitious Startup – Episode now live on Youtube
Please help promoting by sharing/liking/subscribing ❤️
Thomas Vetterli retweeted
We're organizing AI x Bio drinks event @SlushHQ together with @HederaDx, @adaptyvbio, Gosta Labs and @AminoCollective.
Join us for the interesting discussions with people at the frontier of biotech and AI research during Slush!
lu.ma/97fu7lss
#Slush24 #Slush2024
Thomas Vetterli retweeted
More and more submissions are rolling in for Round 2 of the Protein Design Competition! 💪
Our virtual leaderboard is refreshing every 24h and we just published the scripts we're running to compute the evaluation metrics. This way you can check your protein designs by yourself and improve them before submitting!
You can also submit more than once but we will only count the last 10 designs for the leaderboard
The submission deadline is November 4 at 11:59 PM PT -- good luck everyone!
Join us next Tuesday 5th November for the next @bitsinbio Lausanne.
Insightful presentations on how software and biology are used in CGT and drug discovery.
Thanks for @DebiopharmHR and @VerveVentures for hosting!
lu.ma/17qou1i2rom
Thomas Vetterli retweeted
Europe – we need your help.
Please sign this petition to create a pan-european legal entity and promote it as much as you can: eu-inc.org
We got RIGHT NOW a once in a generation chance to improve Europe for startups. 🔥
We got 6 weeks until the new comission sets their work agenda for the years to come. Uniting the European startup ecosystems needs to be part of this agenda!
The solution is known, it's just one out of hundreds for politicians. It's our job as industry to show how important it is.
First co-signatories are people like @patrickc, @nzennstrom, @martinmignot, @MattClifford, @Taavet, Eléonore Crespo, @jobvo, @roxannevarza and many many more coming in the next weeks. Hopefully including you! ✌️
How you can help:
- Sign this
- Get your friends, your team, your investors, your portfolio to sign
- Share this in your whatsapp, slack and discord groups
- Get this in front of press, newsletters, and influencers
eu-inc.org/
For Europe, for the next generations to come: Let's make Europe the best place for innovators.
Uniting as one ecosystem is the first step - a pan-european ecosystem is the key here. Let's go!
Kickoff of the @adaptyvbio protein design competition 2! Thanks to @MartinPacesa and Lennart Nickel for the overview of the winning solution of round 1 - Let’s go!
Thomas Vetterli retweeted
You can also follow the competition directly on @Polaris_HQ - protein.polarishub.io/
Designing better cancer therapeutics using AI - Round 2!
🧬 In Round 1 of our competition, 90 designers submitted 700+ protein designs with the goal of developing a new therapeutic by blocking a cancer-associated receptor called EGFR.
🔎 We then validated 200 proteins in our lab, found some promising designs and open-sourced the results.
It’s now time for Round 2 - same goal, more data: Protein designers can use the new dataset to inform their design strategy and create even better proteins!
