I 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 researcher's institutional cluster.

That alone is valuable. I founded a startup after struggling with this problem at a bio startup; integrating these tools and databases is hard and time consuming. If the only outcome of this product is that great APIs are built for LLMs, it will be a massive positive impact. Many databases used in computational genomics are still only accessible through FTP!

LLMs are particularly good at navigating these tools and databases. It's often very specialized, but straightforward, work that benefits from in-context skills. Seeing an early glimpse of my former customers – bioinformaticians – using LLMs to solve this problem is what led me to join Anthropic in 2024.

Also, this pattern isn't fundamentally constrained to data science: you can also integrate with a wet lab or a CRO for some kinds of science. This is what I'm spending my time on now.

This type of science doesn't solve everything, but it's useful in some niches. For example, progress on many rare diseases is bottlenecked by researcher attention rather than a fundamental breakthrough.

[1] https://x.com/phylo_bio/article/2029233694775624096

[2] In comparison, OpenAI's science product – Prism – was effectively a LaTeX editor they acquired with Crixet.

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 update my resume.

This seems to have unblocked Claude Desktop for Linux ( https://code.claude.com/docs/en/desktop-linux )

So it's like Claude Cowork for Science, i.e. for less tech-savvy users? I would imagine scientists with some coding background might just prefer to use Claude Code normally and integrate it with their stack of choice, but perhaps the comfort and ease of use of Claude Science still wins out.

"Pre-configured for your domain [...] cheminformatics" as in something like ChEMBL?

tl;dr: Use this if you don't like doing science or doing things well. It hallucinates references.

Seems to be based on https://github.com/swaruplab/operon as evidenced by the authorization dialog and https://x.com/testingcatalog/status/2037684573161783373 .

Mostly targeted at life sciences - e.g. integration for FDA, PubMed, genomics databases but no ACM / IEEE as far as I can tell.

Edit: arXiv search seems to be supported - but not Google Scholar etc. So, this tool is of little use for most researchers outside life sciences.

Edit 2: Quick walkthrough: the AppImage starts a browser window with an onboarding wizard and a chat interface. It suggests a few things one might do at the start of a research project - e.g. do a quick literature review. When I chose that option, wrote Python scripts that used MCP calls to do arXiv searches. Stayed seemingly stuck there for a few minutes not returning anything. Then:

> The free-text search returned too much noise

Claude decided to choose a certain paper as a starting point for further research. Shortly afterwards:

> That DOI resolved to the wrong paper. Let me find the correct anchor papers by title/author search directly.

Then it meandered a few more minutes doing research and creating a citation graph (that it did not show to me).

> I have a complete picture. Let me verify the key DOIs resolve and then write the review.

Then:

> The lint flags em-dash overuse. Let me reduce them, then save.

Then: a nice but verbose literature overview of my chosen topic

<blink>BUT it includes at least one hallucinated reference!</blink>

P.S.: What does this mean?

  [reviewer] verifier_mode=default-on downgraded to off: pro subscription tier, autoReviewer withheld (frame=f2a81cb2)

impressive to me, but sadly i feel a little misleading since this is only the data-science part of life sciences.

every few weeks though i test claude and chatgpt on their scientific reasoning and it has definitely improved over time. in my experience without specific instruction on what is known/unknown they typically are lagging behind the leading edge of the field (dev bio/pluripotency in my case). probably because scientific research articles are not open-source so they can't crawl them.

claude has definitely outperformed chatgpt in this regard however, it's scientific reasoning is impressive.

It has Sonnet 5 as a usable model. Interesting.

Big Pharama = Big Budgets.

So targeting them with a tailored product is understandable.

The fact that we are coming up on a month of Fable being unavailable with essentially zero actual signal from Anthropic around when it may be back is crazy to me. Yet still we have these random new products coming out?

Thought I'd give it a whirl - crashed immediately.

I was tickled they had a "Download for linux" button prominently shown, but nothing yet.

So I guess they released this instead of Sonnet 5?

Weird that it runs as a local webserver rather than as an app

"Not that science"

Blog post: https://www.anthropic.com/news/claude-science-ai-workbench

Disappointing that science came after cowork. Shows how their priorities are for profitability first and help humanity second.

Science isn’t suffering from a lack of papers. It’s suffering from a lack of good papers. Making it easier to just pump out paper-mill publications is about the last thing science needs right now.

maxed out on coding improvements so now they're trying to expand to other markets

Another overrated packaged workspace to drain more usage... No thank you.

> every step from data wrangling to *publication*

Do they have no shame?

Edit: seems like no https://news.ycombinator.com/item?id=48736814

this a great application for the sycophantic, non-deterministic lying machine!

How about no?

AI brand identity has made the unfortunate pivot to "how much do you trust us" which is going be a real race to the bottom. I don't want LLMs managing nuclear reactors or replacing junior lab technicians. I don't trust any of these LLMs to do the bare minimum, regardless of how good it is for your brand.

It's gross watching these stunts unfold. Next ChatGPT will fly a passenger jet, which Claude will one-up with an agentic surgery, which OpenAI will respond to by putting a humanoid robot on the moon. If this is what 21st century market competition looks like, we are all fucked.