Machine Learning @Latent_Labs, anything from classical statistics to modern machine learning and generative AI, previous @altos_labs
United Kingdom
Joined June 2020
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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'. 🙃
The extent to which you can just do things now is staggering: I used AI to generate my own RTS, including the possibility to play against an agent by creating a machine readable gaming engine.
I am still wrapping my head around how this will change industries.
I used @claudeai for orchestration, @bfl_ai for designs drafts, @ChatGPT for blender models, @ElevenLabs for voices and sounds. Implemented using @godotengine
One thing that @OpenAI could do with the massive compute is to brute force re-review every research papers, beginning with maths and physics and continue to stats and ML.
Unpopular(?) opinion: we don’t need classifiers to detect whether something is LLM generated or not, but rather whether it’s worth reading, i.e. we need to detect slop vs non-slop, not AI vs human.
Those are very correlated but not identical.
Is there a word for a mistake that almost every paper in a field makes, that “everyone knows” is a problem, so nobody can publish the correction? (Rejected as trivial because well known)
Sebastian Schmon retweeted
uatx.substack.com/p/forget-y… Hmm. I'd say the Enlightenment version of individualism is the historically unique idea that individuals exist not for the sake of their ruler, their class, their ancestors, their gods, or any other such superstition, but for their own sake. Meaning does not require subordination to something "greater than oneself". It is created by the idea that progress is possible and desirable – not by a leap to utopia, but endlessly into the future by undirected problem-solving, carried forward voluntarily by individuals for their own reasons.
Sebastian Schmon retweeted
Not to throw shade but I’m not sure I buy the argument that this is an example of agents “reducing the burden of human expertise” when the prompt used to kick things off is like ten pages long and looks like this. How many humans on earth know all these methods? Maybe 5,000 tops?
I see a lot of confusion around the "achievement of Anthropic" here. It's actually quite simple, this is an example of AI reducing the burden of human expertise.
-Specialized models (e.g. Bindcraft) reduce the burden of access to experiments.
-Reasoning models reduce the burden of access to expert humans.
This is a clear case of the second.
So being an area chair at @NeurIPSConf now means that I have to decide whether the author LLM won the arguments with the reviewers LLMs?
Really inspiring to see what researchers have achieved using the technology we have built at @Latent_Labs.
Today we launch Latent-Y, our drug design agent. 250 designs free every day for any approved researcher.
We are also releasing the first lab results from researchers with early access: Ion channel inhibitors that work. CAR-T cells that kill tumour cells, now in vivo. Binders the malaria parasite cannot mutate away from.
Full results: latentlabs.com/latent-y-rese…
Apply for access: platform.latentlabs.com
Sebastian Schmon retweeted
Today we launch Latent-Y, our drug design agent. 250 designs free every day for any approved researcher.
We are also releasing the first lab results from researchers with early access: Ion channel inhibitors that work. CAR-T cells that kill tumour cells, now in vivo. Binders the malaria parasite cannot mutate away from.
Full results: latentlabs.com/latent-y-rese…
Apply for access: platform.latentlabs.com
Sebastian Schmon retweeted
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"...
New ICML 2026 paper challenges the Platonic Representation Hypothesis: model width and depth mechanically inflate similarity scores, creating a misleading global convergence trend which disappears after that bias correction.
What survives is local neighborhood alignment across image, text, and video models (similar things stay near each other even across very different architectures). They call it the Aristotelian Representation Hypothesis :)
So while two models may not share the same representation space in any strong global sense, they can still agree on local neighborhoods (what is similar to what). That is probably the part we actually use in retrieval, transfer, and multimodal systems, and which could be transferred between learned approximations of different models.
arxiv.org/pdf/2602.14486
Sebastian Schmon retweeted
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...
Sebastian Schmon retweeted
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-techrep…
Blog post: latentlabs.com/latent-y
Apply for access: platform.latentlabs.com