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Claude Science

claude.com

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Re: Claude Science

#81

Post by gjuggler »

The most interesting thing here is that Claude Science runs a local server and a web-based UI that connects to that server from your browser. This is very different from Claude Code and Cowork, where the UI is more tightly coupled to the host machine (which makes things like computer use possible).

I think I recognize the strategy: most pharma environments connected to interesting data are tightly locked down, to the point where you can't just connect your Macbook to the source data.

Similarly, access to large genomic biobank datasets like UK Biobank or NIH's All of Us program is granted only through a Trusted Research Environment (TRE), a remote data analysis platform usually quite restricted on internet access, etc. You can't easily run desktop apps, but these environments do usually support running JupyterLab or VS Code, tunneling the user interface through to the end user. (Source: I previously ran the team that built the All of Us TRE.)

Claude Science looks a lot more like something one could imagine spinning up in one of those highly-constrained data environments (with the "server" running within the TRE and the UI proxied to the end user's browser) than the does-everything Claude mega-app. That will be critical for traction within pharma R&D environments.

I will say that for moderately-computational scientists, who are daily driving RStudio, JupyterLab, or maybe VS Code, Claude Science will be quite an unfamiliar shaped product. I'll be curious to see whether something like this gains adoption (1) in place of, (2) alongside, or (3) eventually wrapping around the more traditional data science workbench tools out there.

Re: Claude Science

#82

Post by cowpig »

I've always found that what science is really lacking is closed, proprietary ecosystems trying to build for-profit moats around research.

Thank our lords at Anthropic for stepping into this void

Re: Claude Science

#83

Post by __MatrixMan__ »

ritzaco wrote: post #34
minimaxir wrote: post #20

When I saw "Science" I didn't think they meant Data Science , which is what the UIs full of pandas code and plots imply. Even if the focus is on the sciences, I suspect that's the less valuable part of the announcement particularly with the implication of Jupyter Notebook 2.0. Image-understanding for data viz is a use case that has been ignored, and modern LLMs are getting better at proper EDA. But, uh, I may need to…

A lot of the soft and hard sciences use hacky matplotlib code to produce results and visualisation, without being necessarily data science From the bits I've seen, I'd take claude-generated code any time over that written by maths, physics, biology, linguistics people. Even though I've seen Claude make some super-big mistakes while doing data analysis I'd guess it's already more reliable than most academics trying to…

Conveniently, you can use published results as tests of equivalence, provide the ugly code as context, and regenerate it to your liking. I think the odds of such a regeneration introducing a bug that's within the usage domain but that dodges the golden tests are quite low... so long as you resist the urge to add features along the way.

Re: Claude Science

#84

Post by ianm218 »

dag100 wrote: post #45
ianm218 wrote: post #26

Earlier quoted context omitted.

Isn't this just blanket cynicism? In the long run conceivable we could use AI to hold papers to a much higher standard, audit all the data and code that is associated etc.

Unless reviewing becomes more profitable than publishing, anything that makes both easier will drive one up far more than the other. And it is difficult to conceive of something that would make reviewing much easier without making publishing much easier.

Just as a counterpoint ML and AI research has become much more reproducible over time. I feel like this is relevant because ML / AI researchers are huge power users of AI tools.

Between 2016 and 2021 the share of ML/ robotics/ AI researchers being reproducible (ie contianing code and similar instructions to reproduce) doubled [1].

The major US labs have gone largely closed source (I.e. they no longer publish frontier research) but the Chinese ecosystem has incredibly reproducible code.

This is field dependent obviously but I think it atleast gives reason to be optimistic.

Yes people will churn out fake slop research, but it feels like that can be categorized and then ignored.

[1] https://arxiv.org/pdf/2308.10008

Re: Claude Science

#85

Post by ianm218 »

xpct wrote: post #54
ianm218 wrote: post #26

Earlier quoted context omitted.

Isn't this just blanket cynicism? In the long run conceivable we could use AI to hold papers to a much higher standard, audit all the data and code that is associated etc.

> audit all the data and code that is associated For a while now there has been very little incentive for providing these alongside the paper, and I don't see why exactly 'AI' would change this. I could even see how making it vague to be harder to test with LLMs could be profitable for citation hackers.

You can imagine using AI agents to tag papers that don’t have code or similar work attached and just filtering them out.

The Chinese open source community has made a lot of incentive to make research reproducible for example. The most reproducible works from I.e. deepseek get widely cited and adopted.

I don’t think we can just say “AI” and it’s fixed but with deliberate effort there’s reason to be optimistic.

Re: Claude Science

#87

Post by ai_fry_ur_brain »

PotatoFarmsKing wrote: post #74

Before LLMs the tech groups I followed were ripping with discussions about this and that topic, what to use and when; I believe these discussions sparked the creation of many frameworks and tools out of "this seems like a good idea, wouldn't hurt to implement it". Unfortunately it all resolves around LLMs nowadays and how to make some LLM work some way or another, we don't even discuss the very topics the groups were…

Well LLMs are largely useless and people are realizing that.

Re: Claude Science

#88

Post by dag100 »

ianm218 wrote: post #84
dag100 wrote: post #45

Earlier quoted context omitted.

Unless reviewing becomes more profitable than publishing, anything that makes both easier will drive one up far more than the other. And it is difficult to conceive of something that would make reviewing much easier without making publishing much easier.

Just as a counterpoint ML and AI research has become much more reproducible over time. I feel like this is relevant because ML / AI researchers are huge power users of AI tools. Between 2016 and 2021 the share of ML/ robotics/ AI researchers being reproducible (ie contianing code and similar instructions to reproduce) doubled [1]. The major US labs have gone largely closed source (I.e. they no longer publish frontier…

That's good to hear about ML and AI research, but most research is not based on computers and so would require laboratory setups to reproduce. Not only is trying to reproduce such findings (beyond what is effectively a sanity check) through simulations a lost cause, if AI can reproduce such research it would be capable of doing such research itself... in which case it would be far more fruitful to use AI to do further research.

Re: Claude Science

#89

Post by foxyv »

ai_fry_ur_brain wrote: post #87
PotatoFarmsKing wrote: post #74

Before LLMs the tech groups I followed were ripping with discussions about this and that topic, what to use and when; I believe these discussions sparked the creation of many frameworks and tools out of "this seems like a good idea, wouldn't hurt to implement it". Unfortunately it all resolves around LLMs nowadays and how to make some LLM work some way or another, we don't even discuss the very topics the groups were…

Well LLMs are largely useless and people are realizing that.

Raw dog Chat LLMs are pretty worthless. But run an agent with tool invocation and they get scary good. It's amazing how much reasoning is packed into the English language. Provide your model with enough information and it can pull some miracles out of thin air. It's not the "Replace humans" level yet, but you can automate a lot of stuff you wouldn't expect to be able to automate.

Re: Claude Science

#90

Post by gonzalohm »

gjuggler wrote: post #81

The most interesting thing here is that Claude Science runs a local server and a web-based UI that connects to that server from your browser. This is very different from Claude Code and Cowork, where the UI is more tightly coupled to the host machine (which makes things like computer use possible). I think I recognize the strategy: most pharma environments connected to interesting data are tightly locked down, to the…

I agree that it's an interesting architecture, but I'm not sure how it would work in a highly controlled server.

If you can't connect from your Mac, then I doubt they will allow an agent to make requests from the server

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