Posted by raahelb 5 hours ago
no mention of opus/mythos/fable or anything..
> After reviewing the pre-print, Feng Zhang, one of the pioneers of CRISPR genome editing and a professor at MIT and the Broad Institute said:
> This is an exciting example of how AI agents can contribute to biological discovery. The identification of RNA-repeat arrays associated with reverse transcriptases is genuinely intriguing and merits further investigation. I hope this work encourages more scientists to explore how AI can support their research.
Not saying that they were right or wrong, but that single moment sullied all AI-driven breakthroughs that came after it, and I don't think it was ever particularly relevant, at least not nearly to the degree that it was presented in the media. But I guess it ended up being a convenient outlet for AI anxiety in the end.
The LLMs that make this stuff possible weren't created by the AI labs from whole cloth. They crept up and jumped onto the shoulders of giants, basically the collected (non-consensually, of course, but jingles keys look at this pelican riding a bicycle!) works of humanity. Every discovery LLMs enumerate in this fashion rightfully needs to have a billboard-sized asterisk regarding the provenance of the discovery. "Claude" didn't discover this, everyone who worked to produce the internet that Anthropic siphoned into their dataset belongs on the credits.
It's great that it happened, and I wish them the best of luck in using our work to make the world a better place. Just don't forget who the rightful owners are.
The people that say "It's just a next word predictor" might as well be saying "Well, it's just a long rage nuclear missile".
Generally speaking, hiring an army of influencers to shill for you results in bad PR, and comments like this one.
It's not novel, and they don't know if it means anything. They published it here for PR purposes.
Is there an equivalent headline for Anthropic of this?: https://www.businessinsider.com/inside-open-ai-influencer-ma...
https://www.businessinsider.com/emma-orhun-canceled-claude-p...
> Anthropic’s head of influencer, Lexie Barnhorn, has described creators as essential to building trust in complicated technical products. Its strategy is partly consumer-to-business: People who adopt Claude personally may later introduce it in their workplaces.
> Anthropic’s best-known creator events have been smaller dinners and pop-ups in which Claude remained the ostensible subject.
Let me know when OpenAI starts actively trying to cure diseases.
The pre print clearly states it’s a well defined problem limited by the man hours required to sift through the data. I think everyone knows it’s not setting the world alight?
> Startup aims for Claude AI to direct robots in lab environments, one source says
> Company to stop short of clinical trials to avoid drugmaker competition, life sciences head says
https://www.reuters.com/world/anthropic-quietly-sets-up-biol...
Caveating I'm not a biologist, but my understanding of the way this kind of thing works right now is a basic three-step process:
1) Find molecules and DNA/RNA sequences in the wild and catalog them.
2) Discover interesting subsequences among these.
3) Figure out whether any useful applications can come from what was discovered.
All three of these generally take a long time. Systematic automatic analysis of known databases speeds up and removes some of the luck from 2. But 1 and 3 are still long poles. 1 has the further issue that we usually discover these in existing organisms. I recall much of the outcry over tropical deforestation back in the 90s and replacing of rainforests with palm oil monoculture today is that the vast majority of terrestrial biodiversity is found in rainforests, and destroying them at industrial scale risks losing potentially useful molecules forever. 3 has the problem that you need to conduct physical experiments, and are limited by the speed of biochemical reactions no matter what and by the speed at which human subjects can be found and ethically experimented on assuming we care about being ethical.
A lot of good can come of this, but I don't see a path to singularity here, assuming we're talking the original Kurzweil meaning there of all technological progress that will ever happen all happening at once. Data collection and experimentation on living subjects, human or not, can only happen so fast, regardless of automation. It's not computational. Whenever you have to interface with the real world, you're now working at the speed of the real world, not the speed of electricity. CRISPR was discovered in 1987 and first used to edit a gene sequence in a human zygote in 2015. I'm sure there are plenty of ways to make the candidate discovery to human application step not take three decades, but it's never going to be three months, either.
To me this strikes me as an incremental discovery that would have taken someone with time, interest, and expertise to make before. It could have cool applications or it could just be interesting biology. Molecular biology has progressed through many years and many rounds of automation and new tools, but the problems are still hard. This just strikes me as one more way we may be able to speed up one part of the process.