Sebastian Schmon

Saying there is a "distribution shift" between train and test data is a great marketing ploy in #machinelearning to make overfitting somehow the data's fault, not the model's or modellers'. 🙃

Last week, our Head of Marketplace Max Winston spoke at @5x15 Tech: The Sublime at the Royal Society of Arts - an invitation-only evening bringing together some of the sharpest minds in AI and technology. Five speakers. Fifteen minutes each. One question. Max spoke on AI and the future of storytelling, sharing the stage with @SeBayesian, Ali Eslami, @nikitaandersso3, @anilkseth, @thecoolgeek. Incredible conversations and even better company. 🙌

How about we leave the ancient Greeks behind? To me this looks more like a "family resemblance"...

I'll tell you why so many people upset about the "no hallucinated citations" ban on the arxiv: because they've all been copying citation lists from each other without checking them since the beginning of time. And why did they do this? Because half of the citations in scientific papers are politics and not to the benefit of the reader. If you don't list the right papers, your paper doesn't look 'right' and reviewers will complain that you didn't cite this-and-that other unrelated work. For what I am concerned, these are all bullshit citations that shouldn't be in the papers in the first place. They can easily be automated by "related papers" links, that are (wait for it) provided by... AI...

Today we're launching Latent-Y: the world's first autonomous agent for drug design, lab-validated end to end. Give it a research goal. Latent-Y reasons, designs, iterates, and delivers lab-ready antibodies, autonomously or collaboratively, with the biological reasoning of a PhD protein design expert. Technical report: tinyurl.com/latent-y-techr… Blog post: latentlabs.com/latent-y Apply for access: platform.latentlabs.com

Love seeing external teams succeed—Onava just published their Latent-X1 binder results! Using the Latent Labs Platform to design proteins in the web browser, the team around Sharrol Bachas was able to design binders against a particularly challenging immune target. They completed design-lab loops in just 7 days! Key highlight: Nanomolar-strength binders with high target specificity, outperforming that of other approaches in their lab comparison. Of course we just launched Latent-X2 now enabling drug-like antibody design. Reach out if you'd like to explore what that could mean for your pipeline. See their preprint here: biorxiv.org/content/10.648…

Super proud of the team's achievement 🚀 Shipping our second model Latent-X2 that allows users to design antibody binders on our platform. Check the below thread for more details 👇

5 months from Latent-X1 to Latent-X2. AI-generated antibodies with drug-like developability and low immunogenicity in human panels — zero-shot. Available now for selected partners.

Amazing work by my friends at latent labs!

Latent Labs Announces Latent-X2: AI-Generated Antibodies With Drug-Like Developability and Low Ex Vivo Immunogenicity sfbn.org/san-francisco-… #news #biotech

New latent labs report on de novo antibody design closely follows what we’ve seen from Chai and Nabla. Promising results, and I respect that they admit that half of the targets were unsuccessful with their approach

Introducing Latent-X2 — AI-generated antibodies with drug-like developability and low immunogenicity in human panels, zero-shot. Technical report: tinyurl.com/latent-X2-repo… Blog: latentlabs.com/latent-x2 Apply for access: partnerships@latentlabs.com

Another packed room and great company, thanks everyone for coming to our second In Silico event. Special thanks to @amyxlu @SimMat20 @SeBayesian and @DominiqueLaLo for the great talks! And our sponsors and hosts @RenPhil21 and @IDEALondon Look out for the next edition soon 👀

Proud to share that our founder Simon Kohl was named in the @observer's 2025 A.I. Power Index. @saakohl's recognition reflects both his groundbreaking contributions and enduring influence in AI's transformation of biology. See the full roster of A.I. leaders: observer.com/list/2025-ai-p… #ObserverPowerIndex

In Silico is back for round #002. Come see great talks on the future of protein and molecular design from @amyxlu @SimMat20 @SeBayesian and @DominiqueLaLo. October 1st 6pm at @IDEALondon luma.com/txswapqo

Showcasing Latent-X's breakthrough macrocycle designs. Our AI achieved an unprecedented 91-100% hit rate with single-digit micromolar binding affinities—functional binders on every single target tested. Explore our binders without logging in: platform.latentlabs.com

It's been a fantastic first few days of public usage of the Latent Platform! The team has been providing white glove user support - for feedback or requests, you can reach us through our feedback channels: form.typeform.com/to/P4vxcyT2?ty… Also, check out our sharing feature below: You can share design batches for others to view right in the platform, without even needing to sign in!

🧬 Latent-X is our first frontier model for protein design. For mini-binders, our AI model achieved picomolar binding affinities — the strongest reported vs prior methods in head-to-head lab validation. Explore our best binders here (no login required): platform.latentlabs.com More details on the breakthrough in this🧵

I'm really excited about what we build here, the machine learning, the science, but also the platform! Proud to be part of an amazing team!

Introducing Latent-X — our all-atom frontier AI model for protein binder design. State-of-the-art lab performance, widely accessible via the Latent Labs Platform. Free tier: platform.latentlabs.com Blog: latentlabs.com/latent-x/ Technical report: tinyurl.com/latent-X

@Latent_Labs comes out of stealth today with $50M funding. Our goal? To push the frontiers of generative biology, giving partners instant access to tools capable of accelerating drug design. Every biotech or pharma company searching for the best therapeutic molecules understands the role AI can play - but not all are in a position to develop their own advanced models. That’s where @Latent_Labs comes in.