It is odd (or maybe not) that they decided to publish a marketing whitepaper rather than a more traditional journal submission + preprint. The work does appear to be sufficient for a publication, though there's a good chance a reviewer will rip into them for some of the assertions they make, but given the topic I'm sure the paper will be accepted regardless.
The market for entry-level programmers has already declined, but at least they were somewhat in demand and made reasonable salaries. Now what happens to post-docs who already make almost nothing and often get treated like crap?
Did anyone read the blogpost? They did publish a pre-print:
https://www-cdn.anthropic.com/22573675ada52a8ca8a97a1a4b4326...I just looked at it. I really hope they're not thinking of sending that to an actual bioinformatics, computational biology or molecular biology journal! So embarrassing...
(I love how Anthropic boast about building a lab, but don't seem to realise that you have to test your hypothesis in the lab! Right now, all their "spectacular" assertions are untested and unproven.)
I realise that this will only improve from here, but gods Anthropic has no idea about the biological sciences right now.
Um. Take a look at the authors. Every single one of them is an expert in this field. They did test this in a lab.
If you want to complain about things like this, it really helps to be specific. Given the author list, it's unlikely they made any truly spectacular errors (and also possible the system they studied is not interesting).
This comment chain is depressing. People who hallucinated things they really wanted to be true. Guess it’s not a uniquely AI problem.
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What's with all this pre-print business. It became very prevalent during covid, where it felt like every week some new pre-print was published that discusses some new aspect of the virus. These papers would then be used in arguments and put forward as proof of whatever claim the arguer was making.
Every man and his dog can publish a pre-print and in my opinion it's academically worthless.
Preprints are just a way to sacrifice rigor for accessibility and velocity. You can throw out "here, this is what I'm working on, here are the quick and dirty findings" really fast and with little friction.
This does skip the academic "checks and balances" like journal selection and peer review - but it can also help anyone else who's working on the adjacent topics.
If a field is moving fast, and you think there can be some value in your work for others in the near term? Preprint. If your work is too incomplete or too minor to warrant trying to polish and publish it, but you don't want to table it? Preprint. Too deep in corporate structures to care about academic "street cred", and want your work to be accessible? Preprint. Have an exciting early finding that you want to push out there, and are willing to take the rep risks of being wrong about it? Preprint.
There's a reason why preprints came to be the lifeblood of ML.
Academia isn't my thing but I also wonder if there isn't an aspect of putting a stake in the ground? So that if someone beats you to publishing you at least have some record of being on that track.
That is definitely a big motivator for publishing preprints. Journal submissions can take up to a year. Comference submissions take months. If the field is moving fast, claiming a finding early can become an important career move.
In older days, academics would just share notes on their work and word wouldn't usually spread widely before publication.
Preprints may be the better model. But public visibility means that non-experts now get to see the good and the bad research equally, but they won't have the domain knowledge and skill to distinguish one from the other with confidence.
I have a similar to pagerank method I use to evaluate such papers. I look for the references to see how many authors are using their own references (past work), the idea being that people do not jump too far, they make incremental progress.
For the pre-print I could only find only one author who has a single referenced article.
Journal articles are usually behind a paywall. Preprints are a fully open workaround allowed by most journals.
> Every man and his dog can publish a pre-print and in my opinion it's academically worthless.
Sure but if you look at the authors names and see they have 50 other published papers, you can get a rough idea that it's probably equivalently good to their other work.
Until you've done it yourself, it's hard to grok just how bad the peer review process is. It's like...5% better than nothing.
Honestly you could argue peer review is worse than nothing, as it also filters out actually quality work that violates some dogma of the field.
The review time on top journals is multiple years now (your paper will go through many review loops each of which takes months). It's just totally unworkable for active research, whether you're a student or a corporation.
I don't recall that being there when I first read their post a few hours ago... No way to confirm, sadly, as they've posted it to their own domain
Earliest snapshot is from 3 hours ago, more or less, it already shows the pre-print: https://web.archive.org/web/20260923180804/https://www.anthr...
archive.is has a snapshot from 18:47, showing the link was indeed there a few hours ago. https://archive.is/XM0Nw
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Just going to post this. And I think it's safe to say that no, they didn't read it.
Medical advances are more important than post docs
Medical advances require post doc levels of education and knowledge to advance. Otherwise we are pretty soon unable to determine what is trash and what is useful. It is easier to generate trash data than good data, and most data generated will be trash, so if nobody can sift through the good and bad the next level is going to be ingesting nonsense and getting worse every time.
Absolutely. But without post docs, it won't be long before we are unable to understand what the LLMs are suggesting.
many drugs were discovered, evaluated and approved without understanding at all how they worked.
iirc back in the day chemists synthesized a whole bunch of random compounds, observed their effects (in mice etc., or even the chemists tasting them!) then did clinical trials to measure safety and efficacy.
high-throughput screening of chemical libraries on in vitro assays is the modern version of this. "rational" drug design, which uses understanding of mechanisms to design chemical structures for a specific purpose, largely failed back in the '80s.
Well I guess who gives a shit about knowledge
The way I ask it in public situations with scientists is this: If you had an AI that could output cures for diseases (IE, drugs that pass phase III clinical trial, get approved by the FDA, and are highly effective), but it couldn't explain how it worked, would you use it?
Opinions are mixed. Some folks will say that it's morally imperative to cure people even if we don't understand the specific or general principles. Other folks will insist that it's a terrible idea to hand over the comprehension of medical treatments to LLMs, because in the long term it will leave us helpless and dependent.
Ive been thinking about this a a lot, like now if LLMs can just try a bunch of things, you can just try them all now. Are there some applications where we can just brute force and test at scale and no longer need to understand? Where understanding is now in essence that it “works” and passes our acceptance tests.
There's been a decent amount of drugs that have been made via a brute force method, but it's a pretty physical process, usually pipetting a few hundred thousand compounds and samples. There's also a lot of drugs where we don't fully understand how they work.
I give a shit about knowledge! I think it's good entirely for its own sake.
I agree! I'm also not going to turn down an Alzheimer's vaccine that's been demonstrated to be safe and effective even if we don't know exactly how it works. (And if you think that's a contrived fantasy, check out the shingles vaccine).
I can't understand what the post-docs are suggesting.
True, but it's also not your job to understand what post-docs are suggesting (hopefully), unlike post-docs who kind of need to understand what LLMs are suggesting.
Not to get back into the AI safety debate from last week, but I really, really want a team of human experts to understand what the AI is suggesting before we administer new medical treatments or synthesize new lifeforms in the lab.
At this point it should be clear that Anthropic are determined to create the doomsday scenario as the most idiotic "I told you so" gotcha in history.
If you can't, then you aren't in the field, and it doesn't matter if you could or not.
There will always be a %age of humans who will be curious how the universe works including LLMs. Delusional to think those humans are only incentivized by degrees, or money.
Humans were curious and started the intelligence / learning explosion much much before money and degrees were invented.
For most of history we died of easily preventable diseases because we lacked the scientific institutions to learn how to prevent them. The fact that a percentage of the population wanted to know more is why we live so well today, but it didn’t stop many of those people from dying awfully. It wouldn’t take a lot to go back there, or at least to a civilization that would go back there the second the AIs have a major outage.
Sure. But unless they are born into a very wealthy family, or decide to pass up on having a family and other hobbies, they won't be able to satisfy that curiosity beyond a very basic level.
once everyone lives to 200 yo there will be no need for post-docs - afterward we can just upload PI's brain to some AI.
I wonder who's going to pay for that extra 120 years of living we're gonna be doing?
I have no idea what prompts questions like these.
We got to 80 without inventing money. Living that long back then was hard work every day.
Then the industrial revolution happened, and we got state pensions at one end of life and extended childhood a few years past adolescence on the other. We currently pay for this… by taxes funding both education and a pension.
Absent the radical transformations of an AI driven economy, we live 200 years in exactly the same way.
With those transformations, all bets are off unless they violate the laws of physics.
But the majority of people in the world are still working just as hard now as before the industrial revolution? Most of the labor rights activists of the 19th and 20th century spent their time advocating for working hours closer to their pre-industrial grandparents. Industrialization increased working hours with the promise that eventually everyone will have to work less hours once the equipment was built. And yet many generations later countries are talking about increasing retirement age, reducing worker rights, and wage theft is more prevalent than all other forms of theft combined.
What is AI going to do that industrialization and automation hasn't already made the same promises for?
Musk said we will all be rich so we will?
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This is a bit like saying that shoes are more important than shoe factories. Yes, sure, I can't wear a shoe factory, but we'll all run out of shoes if all the factories are gone.
cobblers used to make and mend shoes before shoe factories existed..
Perhaps if you assume we will continually be offered highly valuable medical advances into the future without humans who understand it.
That's a big assumption to make, so I hope you at least have some proof to back it up.
Post docs is the base that AI was born from...
We still need post docs. What will change is their specializations.
That's why nobody writes their paper on gravity or polio in 2026.
Then we end up like that anti-aging guy and end up older and giving ourselves untreatable diseases
But do we get any without them?
> The market for entry-level programmers has already declined, but at least they were somewhat in demand and made reasonable salaries. Now what happens to post-docs who already make almost nothing and often get treated like crap?
Waiting for frontier labs to get into Political Science to show that SOTA models can be vastly better politicians...
It's not odd, it's a for profit company that's using it for marketing.
Why do you think they're going to be treated badly? Right now, I think it's kinda accepted that the people best suited to directing AI for programming tasks are programmers - only we operate at a higher level.
Claude's going to be a similar productivity booster to researchers and postdocs.
I'd be totally lost talking to an AI about biochemistry.
Novel discoveries are now marketing ads.
If individuals had power to allocate funding or not to public research projects rather than get a blanket tax, there would be a lot more conventional marketing in the public sector as well.
No, it's not odd; IMO. It's by design.
I see all of this leading to a setup for: We did cure Cancer, everyone else (Healthcare, Gov., Rx) etc... has just not caught up or even worse; "you just don't have access top that model/version".
I have seen several times on HN recently how people don't see the impact of AI/more code etc... and I believe this is because its following the K-shape of the current economy.
At the top where most of us aren't but CAN see via stock market news etc...; they are making more money by adding efficiencies etc...
At the bottom; efficiencies are being applied at a scale that they could not before such that social and Gov. programs are more manageable and optimized at scale.
> Now what happens to post-docs who already make almost nothing and often get treated like crap?
At least in the US, that particular brain drain has already been happening due to Trump's administration. The best of the best are exiting to other countries that will gladly have them, and then there will be far fewer people getting into the field. Science in general has taken a massive hit under the current administration and it going to take decades to fix if it's even possible.
Why decades?
Need risk aversion to reset after risk was raised temporarily. Humans are cautious creatures
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Anecdotally our US office which used to be a hub for talent is now a feeder to other locations around the world with most applications seeking opportunity outside the US, from inside the US. I've been doing this for two decades and it's never happened before at this scale. Engineering consulting.
you must not have a lot of immigrants in your circle if you have any doubt of this being true
https://www.aip.org/statistics/more-us-trained-physics-phds-...
Does this AIP report on physics PhDs count as data?
Or statnews? https://www.statnews.com/2026/05/04/trump-immigration-policy...
Or, for the other side, Europe reporting a 46% increase; 169 vs 116 us based researchers applied for ERC grants. https://erc.europa.eu/news-events/news/erc-2026-starting-gra...
> Now what happens to post-docs who already make almost nothing and often get treated like crap?
This sort of discoveries are what gets postdocs funded lmao.
Every new idea like this creates several years worth of highly specialized work to test out derivative ideas, productizing it, and connecting dots to existing work.
I’m curious, what differentiates this from a preprint given the assumption it’s sufficient for publication? It didn’t read like marketing, they don’t seem to sell anything, and there's a link to a not-anthropic.com hosted paper.
> they don’t seem to sell anything
i'll give you a hint: they're selling something
Let's say "anything talking about your product is selling something instead of doing science"
Then we're faced with "why would a (insert whatever makes this a preprint) mean they're not selling something"? (well, at least OP is faced with that, FWIW I think there's ~infinite snarky replies available, but they're sort of uninteresting, no? :)
Well because it is not talking about your product that is what would've created the publication. But what is argued is the research should just be properly published. That publication would have been some advancement in enzyme research and not "Hey we pretend our fancy model created new research and we forget to mention that it was queried for weeks by experts in the field constantly correcting the model whenever it did something wrong until it resulted in something that the researchers could also have created on their own"
Tbh I might be misrepresenting the original post, because in this case I did not read it, but for your point I feel like I also don't have to
"Look at what our product achieved" isn't selling anything? Do you want to take at this bridge I'm selling?
Sure! (presuming it's "take a look at" :)
After I entertain you by doing that, is there a steelman version of my reply you're interested in entertaining me with, by replying? Or, just the strawman?
It's not odd at all. Every single "AI did this cool thing" type post is an Ad. Remember AI outputs slop and never produced anything valuable that wasn't heavily assisted by humans or is a lie.