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Claude Science
- daiz2025 3mo ago[dead]
- cws_ai_buddy 3mo ago[flagged]
- JoshGlazebrook 3mo agoThe 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?
- striking 3mo agohttps://xcancel.com/AnthropicAI/status/2070665903440871779 https://xcancel.com/AnthropicAI/status/2070665903440871779 > Anthropic @AnthropicAI Jun 27, 2026 · 12:29 AM UTC > Since June 12, we’ve been working closely with the US government to restore access to Claude Mythos 5 and Fable 5. Today, the government notified us that Mythos 5, our strongest cybersecurity model, can be redeployed to a set of US organizations that operate and defend critical infrastructure. > We’re restoring access for these organizations quickly, and we’re continuing to work with the government to expand access to Mythos 5 and make Fable 5 available for general use again.
- deleted 3mo ago[deleted]
- ianm218 3mo agoI mean the company has like 3k employees or more right? Lots of them are just working on more applied AI use cases that don't require frontier AI just the right integrations and structure etc. Opus 4.8/ GPT 5.6 level models with the right workflows/ data/ access are still good enough to do huge amounts of economically valueable work.
- imperor 3mo agoThis plus it's entirely plausible their employees have access to Fable or their own other pre-released models internally. Other than the perks you mentioned they've got excellent distribution too.
- shellfishgene 3mo agoThis thing is also surprising considering Fable was not allowed to answer any biology questions.
- bigyabai 3mo agoHow 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.
- torginus 3mo agoMeanwhile in the real world, these Math Olympiad AIs can't even take your fast food order correctly.
- cmiles8 3mo agoScience 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.
- godzillabrennus 3mo agoScientific research is suffering from a reproducibility crisis. Not a publication crisis. LLM's aren't going to solve reproducibility issues.
- messh 3mo agoThey're gonna worsen it
- ianm218 3mo agoIsn'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.
- dag100 3mo agoUnless 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.
- ianm218 3mo agoJust 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 https://arxiv.org/pdf/2308.10008
- nickandbro 3mo agoSo I guess they released this instead of Sonnet 5?
- tripleee 3mo agomaxed out on coding improvements so now they're trying to expand to other markets
- cma 3mo agoWhy have they talked about this for a long time? They predicted date of code maxing out, and did so not from fitting a sigmoid or something but they predicted it would max out right during a steep part of the slope?
- aplthrowaway67 3mo ago[dead]
- raphman 3mo agotl;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 https://github.com/swaruplab/operon as evidenced by the authorization dialog and https://x.com/testingcatalog/status/2037684573161783373 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)
- sampo 3mo agoBiosciences mostly don't use arXiv, they have their own https://www.biorxiv.org/ https://www.biorxiv.org/ but it's usage is not as common as arXiv is in e.g. physics.
- Retr0id 3mo ago> The lint flags em-dash overuse An explicit text desloppification pass (i.e. LLM-use obfuscation) seems like outright scientific fraud.
- sansseriff 3mo ago
- jvanderbot 3mo agoThought I'd give it a whirl - crashed immediately. I was tickled they had a "Download for linux" button prominently shown, but nothing yet.
- calldacopsidgaf 3mo agothis a great application for the sycophantic, non-deterministic lying machine!
- thrill 3mo agoIt's called Claude Science, not Claude Politician.
- calldacopsidgaf 3mo agoBill Maher ass joke
- Sol- 3mo agoSo 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.
- Abh1Works 3mo agolebovic answered this, but it isnt just claude cowork especially with connection and abilities related to SPC clusters. I could defientiyle see my former team at a national lab integrating this with their systems, and forgoing the use of Claude Code all together
- khurs 3mo agoBig Pharama = Big Budgets. So targeting them with a tailored product is understandable.
- asdff 3mo agopharma is currently in a tailspin and not really spending money. they'd rather outsource everything possible to china or india right now.
- imperor 3mo agoEli Lilly's recently partnered with NVIDIA to spend a lot of money for a new research lab in the Bay Area so not entirely
- asdff 3mo agoLily is probably the one major pharma company doing alright these days. That being said this thread has a more sober take: https://old.reddit.com/r/biotech/comments/1rgjnrj/lilly_bets_a_boatload_on_nvidia_gpus_hoping_to/ https://old.reddit.com/r/biotech/comments/1rgjnrj/lilly_bets...
- minimaxir 3mo agoWhen 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.
- __MatrixMan__ 3mo agoMy take based on the video is that they're thinking more about bioinformatics, which might technically fall under the "data science" umbrella depending how you define your terms, but which is not described that way in common usage. It's the content that determines the sort of science, not the toolchain.
- winwang 3mo agoHonestly quite excited to see what can happen here, I think biology has generally had a lack of data science expertise.
- inciampati 3mo agoTell us, what gives you that impression?
- __MatrixMan__ 3mo agoI don't hold that view exactly. But something related... I once tried to replicate a bioinformatics result based on published data (for a class). I found that although the process did indeed yield plots A and B, as the authors claimed, they were typeset wrong in the PDF so plot A had B's caption and plot B had A's caption. It would be an easy thing to provide assurances against, if you wanted to. You could repeatably build the pdf so that such a mistake was in plain view, as a bug in the pipeline, rather than something you had to do offline calculations to support or reject. The situation as it is is not ideal. Instead of anything that would verify either side, it's my word against the author's until a third party bothers to repeat the analysis. That's the best we can do for scientific claims, but there are friendlier ways to make the computational claims verifiable. The Claude science video showed a little "provenance" button and talked about exactly this. Life sciences have their hands full with the actual science. They're not immature, but they are not in a great position to be proving the validity of the computational connective tissue that underlies their results. That's a whole thing on its own, independent of the underlying scientific reasoning being presented (though I wouldn't call it data science). Plus, its exactly the sort of thing we need AI to get better at: sourcing evidence that proves its claims and stitching it together so the proof is easily verifiable. I too am excited.
- bozdemir 3mo agoAnother overrated packaged workspace to drain more usage... No thank you.
- ChrisArchitect 3mo agoBlog post: https://www.anthropic.com/news/claude-science-ai-workbench https://www.anthropic.com/news/claude-science-ai-workbench
- stanford_labrat 3mo agoimpressive 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.
- game_the0ry 3mo agoDisappointing that science came after cowork. Shows how their priorities are for profitability first and help humanity second.
- uejfiweun 3mo agoNow this... this is a hot take. How exactly do you expect these companies to "help humanity" if they're bleeding money?
- imdsm 3mo agoWeird that it runs as a local webserver rather than as an app
- domrdy 3mo agoIt has Sonnet 5 as a usable model. Interesting.
- andai 3mo agoJust released! Claude Sonnet 5 https://news.ycombinator.com/item?id=48736605 https://news.ycombinator.com/item?id=48736605
- properbrew 3mo agoLooks like they've just announced it - https://www.anthropic.com/news/claude-sonnet-5 https://www.anthropic.com/news/claude-sonnet-5
- Retr0id 3mo ago> every step from data wrangling to *publication* Do they have no shame? Edit: seems like no https://news.ycombinator.com/item?id=48736814 https://news.ycombinator.com/item?id=48736814
- Recursing 3mo agoThis seems to have unblocked Claude Desktop for Linux ( https://code.claude.com/docs/en/desktop-linux https://code.claude.com/docs/en/desktop-linux )
- loufe 3mo agounfortunately no arch based distro support. I'm curious why it's not packaged as a flatpak.
- Recursing 3mo agoMany deb packages are easily repackaged for arch by the community
- arendtio 3mo agoWell, for Arch Linux, there was the unofficial version from the official binary in the AUR already... (Not sure what you mean by 'no arch based distro support').
- loufe 3mo agoFirst party support would be nice since this is not a high-trust in the AUR period, but fair point, I'll probably use it, thank you!
- lebovic 3mo agoI 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 https://x.com/phylo_bio/article/2029233694775624096 [2] In comparison, OpenAI's science product – Prism – was effectively a LaTeX editor they acquired with Crixet.
- aabhay 3mo agoCan you speak to what makes this different from simply including or configuring various agent skills? Or is it simply the combination of lots of helpful defaults that makes this product useful?
- CamperBob2 3mo agoClaude: "Not that science"
- trallnag 3mo ago"Pre-configured for your domain [...] cheminformatics" as in something like ChEMBL?
- qwerty_clicks 3mo agoShould be called Claude-bio-big-bucks. What about earth science, physics, engineering? The connectors and skills are all just biology and pharma. Boo
- eli_gottlieb 3mo agoIf I didn't want companies focused on making money to exclusively target the life sciences, I would simply fund literally anything or everything else commensurately with how much money is thrown at the life sciences for the sheer garbage they actually practice and produce. Don't like it? NSF annual budget (pre-Trump): ~$6-8 billion NIH annual budget (pre-Trump) ~$50 billion There it is.
- brcmthrowaway 3mo agoDoA
- theplumber 3mo agoThey forgot to include an example of prompt error on “cancer” with Fable in that “nice” video.
- fastaguy88 3mo agoDownload for mac. Find out I need a different subscription. Cannot quit program (must force quit). Perhaps I need AI to use it.
- immmmmm 3mo agoWhen I was doing my phd, around 2 decades ago, I was often going to the library’s compactus to fish for a Phys Rev from the 80s. Back then papers were sparse and expensive. But the quality! The Higgs boson is 3 papers, 6 authors and 6 pages in total! At the end of my phd, 30++ pages slop papers were the norm. Nowadays, well.. The paper by Higgs was one page. The guy probably published less than a hundred pages in his career. One reason that made me abandon a career was the disgust caused by the publishing frienzy. And now tokens..
- trollbridge 3mo agoThere is an obscure topic where I have read basically every single dissertation, study, etc on that topic (or even just articles that mention it). It is very noticeable how much briefer older publications were. It would be impossible to do that today. I guess I could have an LLM just summarise all the papers…
- Daishiman 3mo agoWhat's the reason for this? Publish-or-perish? Papers have to be more thorough? Extra junk tacked on for the sake of showing lengthier papers?
- maleldil 3mo agoCS conference papers often have page limits (e.g. ACL ARR is 8 pages double-column), so most paper main bodies are exactly that, as it's seen as sloppy if you don't use the full count. I've had someone point out that it's best to use the entire page 8 without leaving any gaps. There are also appendices, which reviewers aren't required to read. If there's something relevant that doesn't fit in the main body and you don't put it in the appendix, reviewers will point it out and ask for it, and it will influence their grades. In the end, publishing papers these days is about convincing reviewers rather than actually writing a good paper. And you usually have reviewers asking for all sorts of things.
- jszymborski 3mo agoAny other researchers paranoid of using LLMs for fear of them using your data and front running your publications/work? Or incorporating it in training data and then spitting it out to a competing lab?
- malux85 3mo agoPay for enterprise or use one of the guaranteed no data retention models (e.g. Bedrock)
- davidpapermill 3mo agoI think with recent changes they still retain data on Enterprise, no? Or have I misread this?
- dmezzetti 3mo agoWhy does HN let OpenAI and Anthropic basically advertise but it throws down the gauntlet at a small developer like myself when we do "self promotion"? Top 3 posts as of this moment are all about Claude.
- PotatoFarmsKing 3mo agoBefore 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 created to discuss. I fear science is soon to taste the same thing - discussions about LLMs taking place instead of the actual topics that would be discussed otherwise.
- ai_fry_ur_brain 3mo agoWell LLMs are largely useless and people are realizing that.
- foxyv 3mo agoRaw 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.
- applicative 3mo agoWhat you are saying, if I follow, is that LLMs basically worthless: it turns out that coding is so simple that verifiable rewards can tune weights surprisingly well for that one peculiar task. ('agentic' is fancy word for letting them run what they write - not to put too fine a point on it.) You've made the most damning remark against Planet LLM I've read.
- eli_gottlieb 3mo agoMost of what's impressed me in working with LLMs is just how much "intelligence" you can get out of the agent iteratively refining something it looks back at with each turn, without its ever actually exhibiting human-level intelligence. I've always been an embodied-cognition guy, and it really seems to me like "agent harnesses" are basically task-specific pseudo-embodiments for LLMs.
- cute_boi 3mo agowhats up with all these samosa? Samosa Manuscript, Samosa Benchmarking?
- gjuggler 3mo agoThe 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.
- gonzalohm 3mo agoI 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
- annzabelle 3mo agoAnecdotally, 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 hour or so to sort out on my own. I know the relevant libraries well enough to read and verify the code, which is an important distinction from blindly using a black box AI. I will note that Claude Code and Jupyter in VSCode don't play nicely together right now - it forces me to rerun the whole notebook from the start after every edit Claude makes. This has led to me stepping back from notebooks and having Claude write standalone scripts that I then spend time merging back into a pretty notebook.
- cowpig 3mo agoI'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
- ai_fry_ur_brain 3mo agoWhy would you people ever use this companies products? They're actually evil and are trying to scam you and or make you unemployable./worthless. You people really gotta wake up.
- ml_more 3mo agoYou (and people like you) refusing to use it won't make it go away. Now what? Acknowledge that it exists and figure out what it means for the world?
- dbcooper 3mo agoA "standing review agent" seems to be one of the main differences beyond the new connectors and in place visualisation tools. >A standing reviewer agent. This runs in the background during a session, checking citations against sources, flagging numbers it can't trace back to evidence, and catching figures that don't match the code that supposedly generated them. That's not something Code or Cowork do automatically — you'd have to ask Claude to double-check itself as a separate step.
- woadwarrior01 3mo agoLooks like Cursor and Jupiter Lab had a baby.
- ml_more 3mo agoThat's probably almost exactly what they did.
- celltalk 3mo agoI basically did the same thing almost one and half years ago and not many people cared, but I still believe that this is the future for computational biology. https://celvox.co/solutions/axon https://celvox.co/solutions/axon
- keepupnow 3mo agoCompetition is healthy, yours looks cooler.
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- gravelc 3mo agoTried this to see how it goes in my particular field - computational design of RNAi-based biopesticides. One-shotted a design for targeting the DvSnf7 transcript of western corn rootworm. It took a fairly naive approach (maybe how a 1st year PhD student would go about it), but got the job done. Also noted caveats with its approach (e.g. using mammalian design rules, limited off-target screening). Not bad really. But also not great. When its flaws were pointed out, the AI determined that it could have taken a more informed approach. Then Opus 4.8's safety system flagged the session.
- greenavocado 3mo ago> Then Opus 4.8's safety system flagged the session. The jokes write themselves these days. I suggest collecting 10 seminal works on the subject matter including 10 textbooks in the general field, converting them to plain text via OCR or text extraction, then trying the same thing with a superior agentic harness, like omp.sh /goal set create biopesticide targeting the DvSnf7 transcript of western corn rootworm <sarcasm>make no mistakes</sarcasm>
- solenoid0937 3mo ago> Then Opus 4.8's safety system flagged the session. If you think you can use this to land real positive impact, you, your institution, or your company should apply for OpenAI and Anthropic's bio programs!
- jerven 3mo agoWorking on the uniprot services that might be used from the connector it would be nice to learn if this uses public resources or if there is a private anthropic copy of certain uniprot data sets.
- botfriendsarent 3mo agoDude! Give me some stolen science!
- kfse 3mo agoI've worked with similar tools and while they're impressive, it's too often the case that the LLM literally makes up fake but realistic looking data and pretends that it's real. This includes pretty deep fakery like setting up mock database connectors so that it looks like you're fetching data from the right place, but it's just getting synthetic data How does this guard against that?
- devilfileprong 3mo ago[dead]
- hooloovoo_zoo 3mo agoDoesn’t seem like much value-add beyond pointing Claude code at org mode.
- evolighting 3mo agoAround the time I graduated from the research institute in 2020, it seems my lab already had a similar infrastructure, just without LLMs and agents. Back then, we had data repositories, databases, Jupyter Notebooks, Slurm batches, open computing platforms, and so on. It could do similar things ---- just by hand. While adding an LLM agent can indeed drastically improve usability, it must be a massive headache for system administrators. It honestly sounds like introducing a huge, uncontrollable wildcard into the system.
- nmilo 3mo ago> Inspect proteins, alignments, genomic tracks, chemical structures, and PDFs in their native form, with no extra installation required. I like how this implies parsing PDFs is as hard as like protein folding
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- chazeon 3mo agoIsn't this the company that make the LLM become a degenerate when it comes to bioscience?
- packeted 3mo agoI 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 mutation was likely passed down from mom or dad. It performed a read-backed phasing analysis on the data, identified a nearby SNP with overlapping coverage where mom was homozygous and dad was heterozygous. Identified my variant on his mutated allele so looks like it came from me.. It also crosschecked my data against AMCG Secondary Finding genes and ClinVar likely pathogenic/pathogenic variants and came back with identical results to my Natera Horizon carrier screening results. I'd previously tried and failed to do this all with some ChatGPT guidance and subsequently hired a couple of bioinformatician post-docs at top tier universities via Upwork who had failed to give me satisfactory results. And this is just getting started!
- letmetweakit 3mo agoYou're not worried your whole genome is being sent over to some commercial entity?
- packeted 3mo agoMarginally but the data manipulation is actually being done locally as the genome CRAM files are like 24Gb each.
- make3 3mo agoit's not, the genome is treated locally by tools called by the LLM, the LLM itself can't do much with the raw DNA sequence
- maherbeg 3mo agoI wouldn't care where my data went if it was to help my children.
- yuppiepuppie 3mo agoNot sure how to feel about this. I think its super cool that you can dive into this, but it sucks that its your son that has this condition for which you have to do this analysis. I hope it all turns out well. Quick question: where did you get your genome read and get the raw files? As far as I know, as service like 23andme does not give you back the raw files.
- teekert 3mo agoI'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/from the LLM) and searching for documentation. With scientific assignments I find myself searching literature on my own, read whole papers as I used to. Checking the LLM constantly but adapting to it and I don't like it, don't like how it steers me, just let me search, let me wander the scientific landscape on my own, let me read the words of the authors with opposing views. Then let me make 20 plots and only use 1, let me wrestle with the data. Let me make wrong visuals that by chance communicate something important about the data. Because otherwise I feel uncomfortable, I need to understand, that is what I do. I can reason about so many things because my internal world model is comprehensive and mostly correct. That has taken 44 years so far. Hard work from time to time, but I've mostly enjoyed it. I still don't know what to make of these models, I use them everyday, but sometimes I wonder if I was not just as fast with Stack Overflow, because what I crave is understanding, not "some finished app". Yes, I rarely finish things fully (that's how I feel), but in research I've often been told they like my ability to move very fast and creatively in phase one, the development is left to others anyway... I crave an understanding of what these tools mean to me exactly. This comment is part of that. HN is part of that.
- teekert 3mo agoPerhaps 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 new knowledge does not just explain the problem at hand, but also a lot of things that still lingered in the back of your mind. Recently my wife said that my daughter (ill at the time) may have heatstroke, my response was: It looks like it but she also has a hefty fever (hot after being more than 24 hours out of the sun), I can't really imagine the immune system being involved in heat stroke, although it's possible... My mind went out to heat damaged proteins presenting neo-antigens triggering an immune reaction. I also labelled that as unlikely and more dangerous than what we were observing. I like that I can do that (of course I went on to verify these thoughts!). That reasoning, it's not exactly 100's tokens a sec, but I like the process and it has value. I also recently observed some weirdness in a dataset, I spend 3 days hunting it down. Long story short: I though I understood how genes make transcripts but I was wrong and ended up adding a new transcript to the human reference genome annotation together with the Gencode people. Now I understand my data better and can separate two different transcripts better in my data (a difference important to our research). Things like that. The LLM doesn't speed that up, not really. I read a part of a book on gene expression and the function of transcription factors and their interaction with promoters, but I also used LLMs, In the end it was the book with the pictures and clear language that communicated the concepts most clearly. It was made for that of course, and I knew I could trust it (it's tiring to assign <100% confidence to LLM answers), although I know a real scientist also does that with books :) Maybe I, we all (humanity), will really be faster in the future. Maybe when you grow up with these things you can build world models better and faster. Maybe I'm just too stuck in my ways, as my neuro-plasticity degrades over time. Or maybe it doesn't degrade, maybe I just need more evidence before changing my world models, they have been building on a heavy foundation for a while now.
- zmmmmm 3mo agoI can't decide if this will make science better or be the death of it. The potential wave of slop about to hit journals is frightening. Essentially what happened with GitHub code reviews is about to hit academic peer reviews and it isn't going to be pretty.
- alpineman 3mo agoSo that's why Fable was refusing those biology questions
- mariorossi25 3mo ago[dead]
- mariorossi25 3mo ago[dead]
- jkwang 3mo agoClaude Science sounds like a useful shift toward reproducible agentic research. The built-in error recovery and tool orchestration could make it practical for real lab workflows, not just demos.
- mv_d5339e31 3mo ago[dead]
- Alexadar 3mo agoInteresting 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.
- agastalver 3mo ago[dead]
- trevor519 3mo agoThey are offering this free to igen students which is really cool
- simonuuu 3mo ago[dead]
- Aeroi 3mo agowhat happens when anthropic launches products for every vertical?
- deleted 3mo ago[deleted]
- zftnb666 3mo agoClaude Science: $200/mo. Me, a scientist: copy-pasting into Claude and saying "I did the analysis."