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  • I’m confused why AI companies are using agents in-house for this type of research instead of partnering externally.

    I guess the improvement loop is tighter and they have more control over how discoveries can be used for marketing?

    But, in my mind, it begins to feel like they are setting themselves up to be “everything” companies instead of focusing on their core product…

  • Why is everyone quick to point out how blogs/articles are "ai slop", but no one blinks an eye at the subtle, almost deceptive or manipulative, ways these companies choose words to nudge along the narrative that their LLM systems are conscious/sentient/persons/etc? The systems they are creating are impressive enough on its own merit. There is absolutely no need to play into the populations lack of understanding even the basics of systems by using language in such a slimy way.

        We gave Claude a prompt to search through a massive database of DNA sequences for interesting new examples of RTs. Our involvement was limited to the initial prompt and the lab work, while Claude agents combed through the database, investigated the distinct RT families, and used their own judgement to identify interesting candidates.
    
    Alternative: We prompted Claude to find patterns of distinct RT families within a database of DNA sequences. The returned data included interesting candidates.

        After 21 hours spent searching this data by roughly 950 agents using 210 million tokens, one of the agents spotted something remarkable: a repeating pattern of DNA sequences that occurs next to the gene for an odd-looking RT.
    
    Alternative: After running 950 instances for 21 hours, one of the instances hit on a repeating pattern of DNA sequences that occurs next to the gene for an odd-looking RT.

        After further analysis and testing in our lab, we recognized that this pattern marked a previously uncharacterized enzyme system found in bacteriophages (the viruses that infect bacteria) that we call array-associated reverse transcriptases (ART).
    
    Alternative: We took the matched pattern data to the scientist in our lab to analyze. The scientist recognized that this data pattern marked a previously uncharacterized enzyme system found in bacteriophages (the viruses that infect bacteria) that we call array-associated reverse transcriptases (ART).

    Maybe give more credit to where it is due, the actual real people scientist that verified data.

  • This shows why biology is so much harder a problem area for LLMs than math, finding RTs is tedious but pretty doable today, they had to scope the problem down a lot from something that would be the equivalent of Navier Stokes in biology. Glad they’re doing it though, even if it’s just marketing.
  • It is odd (or maybe not) that they decided to publish a marketing whitepaper rather than a more traditional journal submission + preprint. The work does appear to be sufficient for a publication, though there's a good chance a reviewer will rip into them for some of the assertions they make, but given the topic I'm sure the paper will be accepted regardless.

    The market for entry-level programmers has already declined, but at least they were somewhat in demand and made reasonable salaries. Now what happens to post-docs who already make almost nothing and often get treated like crap?

  • It’s probably a delimiter. Or an escape indicator.
  • I don't understand how an LLM is able to reason about those things

    LLM use language, but it can't "think" about biochemistry

    I saw that LLM have reasoning capabilities, which is different from machine learning, but I don't understand how it works.

  • Current evolved Cas9 (CRISPR) variants are highly efficient and relatively unconstrained in terms of their human genome targeting coverage. Smaller nucleases and higher targeting specificity would be useful. But therapeutic use is mostly limited by delivery.

    This seems revolve around a known retron-like reverse transcriptase. A sober framing would be something like: Claude identified a previously undescribed genomic arrangement around a known reverse transcriptase. Not all that sexy.

    For now, this is mostly a story about how AI can be used to parse existing data to discover new biology (which is fantastic!).

  • > While combing through the raw DNA sequence near the RT, the agent exclaimed: “[The DNA next to the RT] is spectacular: I can see by eye a tandem repeat array … that's a CRISPR-like … repeat array?!”

    I love that with AI discoveries, we can relive the discoveries from agent transcripts like this.

    I'm sort of imagining future histories involving notable AI events peppered with direct quotes like these.

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