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Claude Science
161–170 of 199 posts
Re: Claude Science
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Re: Claude Science
#163I built one of the connected tools included in this launch (the Biomni HPC [1]), and I have spent an inordinate amount of my life working on this problem. (I also worked at Anthropic, but not on this product.) As other comments have pointed out, this is for data science – but it's capable of more than making plots and writing papers [2]. It has integrations with many databases and computational tools, including a res…
Thank you for this summary. Especially interested about the wetlab & CRO tie-in. What is meant by a ‘researcher’s institutional cluster’?
Re: Claude Science
#164Interesting to test. I set up all scientific subroutines with claude code generated automation and visualization. Honestly, i think that this product would not be a fit for all given diversity of scientific tasks.
Re: Claude Science
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Re: Claude Science
#166[dead]
Re: Claude Science
#167They are offering this free to igen students which is really cool
Re: Claude Science
#168Earlier quoted context omitted.
Anecdotally, as someone with a lot of moderately computational sciencey tasks at work (part of my job is as a data analyst for a geology firm that has some interesting sensor data), combining Claude Code and standard python data libraries has been extremely powerful and sped up my workflows immensely. If I just need a quick analysis or visualization, Claude can write something for me in minutes that would take me an…
There’s a dead sibling comment but I’d also recommend looking at marimo, I just used it to do some analysis for my brother in law and has Claude write the whole thing. It tracks variables used across cells to see what needs re-running. It’s also got an in built AI helper thing where you can put an api key but I’ve not tried that yet.
Just to add to this: Marimo notebooks are set up in a way that ends up being easier/more-token-efficient for agents to work in. They're just python files with some custom formatting to be read by their front-end UI, sort of like cell notation in (# %%) but with a lot of QoL bells and whistles built in. Jupyter notebooks in comparison, are mostly json and are pretty messy to work with as far as git diffs goes, which is annoying. VS-Code's Github Copilot actually had pretty good Jupyter integration, letting you refer to specific cells, and allowed the agent to run individual cells and read their output before writing subsequent cells etc etc. I suspect there are vs-code specific tool calls for jupyter notebooks being used that I haven't bothered trying to replicate with claude.
A month or two ago, Marimo released Marimo Pair, which works about as well as that. It appears to be a skill that just points claude code (perhaps other harnesses, haven't tried) at whatever localhost the Marimo UI is worked off of, and tells it the structure of a Marimo notebook (very necessary since I imagine there isn't as much training data on them compared to Jupyter etc). https://marimo.io/blog/marimo-pair
Re: Claude Science
#169I watched the announcement and gave it a spin as I'm a heavy user of cowork/code. So far I'm super impressed. I used it to analyze my whole genome sequencing data I have as my son has a rare genetic condition. I used it to answer a question I'd asked a few bioinformaticians to help me with but never got a satisfactory answer, it solved it in about a minute - whether his n-of-1 de novo, heterozygous single nucleotide…
now try it again.
Re: Claude Science
#170I'm a scientist, (biophysicist). Over time I have become a bioinformatician and a python dev. I wrote articles and applications, and it always was a struggle. But now I can speed up, make it all go much faster. But I often feel like my mental models can't keep up. Recently the AI has generated a comprehensive data model (in Django) and I find myself retracing its steps with long discussions and explanations (with/fro…
Perhaps it is true that the faster you can internalize knowledge (thoroughly, there is a quality aspect to it), the faster you are. Maybe I'm getting old and learning new skills is getting tougher. Maybe, as my world model grows I'm becoming a slow thinker, or a slow learner? New stuff has to be evaluated against a lot of knowledge. But when it clicks, it really feels like a click, it feels satisfying. Like when some…
Your comments really resonate with me. I have been trying to square the rapid progress in AI's abilities to generate proofs of unsolved math problems with comments that Terence Tao has made regarding whether or not these (incredibly impressive) models are actually contributing to mathematical progress.
From Tao on Mathstodon on April 27, 2026: "We are transitioning in mathematics from an era of proof scarcity to an era of proof abundance, but our mathematical infrastructure and culture has not yet adapted to this. As mentioned previously, there is now a strong (and growing) impedance mismatch between the three core components of mathematical problem solving: proof generation, proof verification, and proof digestion.... Perhaps surprisingly, this massive acceleration in proof generation has not actually produced significant acceleration in mathematical progress itself (with the possible exception of #1196, in which all three stages are largely carried out at this point, and for which some digested assessment of developments will soon be forthcoming)."[0]
And I guess my question is, will it matter if humans grasp these new discoveries? If the models are capable of incorporating these discoveries and using them to recursively self improve to unlock new discoveries without humans in the loop, then I guess we humans never really need to understand. I find it hard to believe that a machine can understand concepts that we never will, but I can't reason why that couldn't be the case. Something that holds trillions of concepts in its mind at once might be capable of generating a proof to something that we simply aren't capable of understanding. And the machine just tells us, "Listen, if you are too stupid to understand the new laws of physics I am giving you, then simply follow these very explicit instructions on blasting hydrogen with this laser at this angle in this exact magnet conformation, then you will get cold fusion."
I am really struggling with this. I think superintelligence implies that there will be things about the world that the models understand that we won't. And I can't quite articulate why that is depressing. Because we should still get some cool new tech and some life saving drugs.