Jay Moore

studying neuroscience and genomics (he/him)

[Jay Moore @JayMoore_res]

@lpachter We at least know all of the symptoms

[Manuel Corpas @manuelcorpas]

1/ Out today in Cell Genomics: "Agentic genomics: From pipeline automation to autonomous validation." With @HeinnerGuio and @SFatumo .

For 20 years the bottleneck in genomics was writing the code. That is going away.

[Jay Moore @JayMoore_res]

@0xCodez + valuable use case where a relational db could’ve been used just as well

[Jay Moore @JayMoore_res]

@0xCodez took this, didn’t find it very helpful. the material builds with either graphdb or embeddings and doesn’t provide a valuable use case.

[Jake Wintermute 🧬/acc @SynBio1]

A use case of scientific AI I hadn't considered

- Retroactively comb the literature for obvious mistakes like this

- Delete from the scientific corpus all the bad papers and all the papers citing them

- Re-train AI on a better dataset than the one humans have been reading

[Jay Moore @JayMoore_res]

Would hope this effect happens to scientists and research

[Noam Brown @polynoamial]

After AlphaGo, the skill of human Go players noticeably improved. I suspect we will see a similar pattern in math.

[Nathan Skene @n_skene]

This Thursday (28th May), we'll be partnering with @sotalikesfuture and Unfabricated VC for an event on enabling an AI-native biotech sector in the UK.

We'll meet in Oxford for an unconference-style discussion to map out specific bottlenecks and challenges on the way to adapting the UK's scientific enterprise for the AI age. We want to meet aligned builders, researchers and engineers who would like to join this effort.

Register at https://t.co/e0PSCi8ftl

[Jay Moore @JayMoore_res]

@charlesmurray @n_skene PDF freely available on their site: https://t.co/fLBulgaBX0

[Jay Moore @JayMoore_res]

@MaziyarPanahi @n_skene

[Saloni @salonium]

I’m a disbeliever in accidental discoveries (at least, in biology). Whenever I’ve looked into one, the story turns out to be false.

The most famous is penicillin – supposedly, the fungi wafted in through a window, fell into a petri dish of cultured staphylococci, and suppressed the bacteria’s growth.

But in a recent article (https://t.co/s99LBvhZkY), @kevinsblake explains that doesn’t really work (grown staphylococci aren’t affected by penicillin; it only works if introduced before the bacteria begin growing); plus, Fleming’s notes on the discovery provide very little detail and the specific results he described couldn’t be replicated by other scientists (even though penicillin does work against staphylococci when introduced correctly.)

There are more: Pasteur’s supposedly accidental discovery of a chicken cholera vaccine was more likely the result of systematic work by his then-assistant, Émile Roux. (https://t.co/GzhMmBxPQv)

And, as @NikoMcCarty writes, the discovery of GFP, nanopore sequencing, and optogenetics are also often described as accidents, but none of them happened that way either. https://t.co/0qeStnCNPT

People love serendipity, so why am I bursting their bubble?

I don’t think this is limited to accidental discoveries; I think many historical science anecdotes are highly embellished:

- Edward Jenner didn’t deliberately expose a young boy with full-blown smallpox to test his vaccine (he used variolation); and he wasn’t the first to try using cowpox https://t.co/tPg9k6DqO7
- Cobra catching bounties in British India didn’t lead to a rise in the number of snakebites, and there was only hearsay evidence that cobras were bred in response at all https://t.co/fuXEL49nu2
- Barry Marshall didn’t develop stomach ulcers from drinking a concoction of H. pylori (he did develop gastritis though…) https://t.co/WwG23fkIbI
- No one knows who actually found the highly-productive strain of penicillin on a cantaloupe, but it probably wasn’t 'Moldy Mary' https://t.co/u8q2U4i386

But in this case it irks me for an additional reason – it gives the impression that innovation happens sporadically, by chance, when there are actually ways that we can systematically speed it up – such as better funding, institutions and incentives.

So: are there any true accidental discoveries that hold up to scrutiny?

[Jay Moore @JayMoore_res]

@DrSamuelBHume @DrSamuelBHume i want to use this but the demo limit doesn’t let you screen enough papers to get enough data to analyse. Another major blocker for me was I don’t see a way to continue when I couldn’t get a PDF (and had a paper from the 80s it couldn’t read!)

[Jay Moore @JayMoore_res]

@AI4S_Catalyst @lecong @MengdiWang10 @Charles_Y_Wu We are dying to try this at Skene lab at Imperial @n_skene. Signed up for the beta test!

[AI4Science Catalyst @AI4S_Catalyst]

We’re thrilled to open-source LabClaw — the Skill Operating Layer for LabOS by Stanford-Princeton Team

One command turns any OpenClaw agent into a full AI Co-Scientist.

Demo: https://t.co/TgGtKO2lxQ
Dragon Shrimp Army reporting for duty 🦞🔬

#AIforScience #OpenClaw

[Jay Moore @JayMoore_res]

@n_skene Looking forward to it!

[Jay Moore @JayMoore_res]

Made a chess game: https://t.co/6Le6BRTPoO

Chess but your board gets teleported to a new position of the same eval!

[Jay Moore @JayMoore_res]

Anyone let agents rename their projects to be more intuitive to the agent?

Accurate naming seems crucial to MCP tooling. For codebases, I wouldn't be surprised if precise naming of functions, files and folders has an outsized impact on performance.

[Matt Pocock @mattpocockuk]

If you throw AI at a bad codebase, you're going to get worse results. Garbage in, garbage out.

And holding it together in your head will land you in cognitive debt.

But these problems have a 20-year old solution: deep modules.

Here's how:

[Jay Moore @JayMoore_res]

@lpachter @tylercowen @sinabooeshaghi @NeuroLuebbert Publishing an MCP server alongside your papers

[Jay Moore @JayMoore_res]

@BostonGenomics @IgorUlitsky You guys crush me! 6.7% here

[Jay Moore @JayMoore_res]

@BostonGenomics If long introns are transcribed then spliced you might find transcripts where the transcription was halted by a stop codon?