I am surprised they end on a gene mutation already known to be involved in a rare disease and a vague hypothesis about the mechanism. Among the many things DCTN1 does... it also directs autophagosomes toward lysosomes for waste degradation. Hm, disruptions in waste degradation.. build up of unwanted proteins and waste in cells... yeah that seems like it would cause neurodegeneration as well! Point being, there are dozens of things, maybe hundreds. Is cholesterol particularly compelling here? Not really. PhD students come up with similar hypotheses every hour. Hypotheses are cheap. I'm sure it can and will do better, but for now... I feel they might be underprepared for curing all disease in 10 years.
changoplatanero 2 hours ago [-]
The last section of the press release was definitely written by AI. I'm talking about the section that starts with "Finding the next experiment worth doing" all the way to the end.
SimianSci 5 hours ago [-]
Ai labs look to be desperate to try and stave off the cooling hype that looks to be snowballing in the industry right now. These next few months are going to be crucial to their potential survival and future.
Its not surprising to me that this press release looks half-baked.
mountainriver 4 hours ago [-]
How is the hype cooling? Opus 5.5 is doing most of my job
drewbeck 4 hours ago [-]
Hype and functionality are only loosely correlated.
vorticalbox 1 hours ago [-]
I assume your still verifying that opus is correct?
In which case congratulations you’ve just been promoted to manager with no pay increase!
Joking aside Ai is doing a large chunk of my job but all it’s done is shifted what I actually spend time on.
It’s not really saved any man hours.
Thanemate 1 hours ago [-]
That's not hype - that's the new norm. It's not novelty anymore.
caughtinthought 3 hours ago [-]
and the company serving it is losing 50B every half year lol
duckqlz 1 hours ago [-]
The staggering losses anthropic is facing are mostly due to their valuation increasing to just shy of 1T at the beginning of this year. That valuation increase caused the value of what they owe on future stock to triple which is shown as a massive loss on paper but doesn’t represent actual cash leaving their hands. The rules are being rewritten by frontier companies whose revenue growth and proposed spending are outpacing any thing we have seen in the past. Anthropic has committed to spending over 500B over the next 10 years on cloud infrastructure which might be what you are quoting but many project their revenue growth to outpace the 50B a year in spending so that may not even equate to any loss but will certainly be less than 50B/yr. The whole thing is bonkers but and it’s easy to get overwhelmed by the breathtaking numbers on their balance sheet.
wongarsu 2 hours ago [-]
If that company stopped training new models and just continued serving Opus 5.5 they'd be profitable. Being in an R&D race isn't cheap
SiempreViernes 2 hours ago [-]
If they would be profitable without further spending on R&D they would stop spending, but as you say they are in an R&D race so they can't stop and thus the hypothetical is irrelevant.
tintor 2 hours ago [-]
Because they are growing aggressively.
BeetleB 1 hours ago [-]
Paper loss. It's a sort of debt they have on bonds that is tied to their valuation. Because their valuation has grown significantly, so has their debt. It's standard accounting process to put that debt as a "loss", even though they're not paying anything.
Think of it this way. It's as if a public company gives you a certain amount in RSUs that won't vest for a while. A year later, the company is worth 10x more. So they list the increased value of the RSUs they owe you as a loss.
In reality, the fact that this "debt" has ballooned so much is a positive sign - the valuation is high (it's a separate issue whether that valuation is realistic).
Their "real" losses are about $8B.
lirolero 3 hours ago [-]
[dead]
lifeisloving 3 hours ago [-]
Because you have a simple job.
Smoofer 3 hours ago [-]
Would love to know what you do that’s more complex than say mathematics research
ofjcihen 2 hours ago [-]
Not stuffing every part of a number space into a sequence?
abirch 3 hours ago [-]
Math and Computer Science have low costs to verify answers. Biology is high due to reagents and instrumentation costs.
dyauspitr 4 hours ago [-]
That must be hard to say with a straight face. Over the last 4-6 months I think very few corporate developers have handwritten any code at all and the “intelligence” growth from one model to the next is very tangible.
IKnowMazin 3 hours ago [-]
Odd. I barely perceive the growth, and I use them a ton at work. Not saying the advancements aren’t there, I just wouldn’t describe every model release as having tangible growth.
Also the handwritten code doesn’t remove the work. If anything, it makes the thinking more difficult (for me) because instead of thinking during the coding, I have to before and after (in iterations).
For big projects I actually go back to tradcoding some to make sure I understand the system, since I’m the one responsible.
devin 2 hours ago [-]
Same. People are drunk on "agentic" and reality is coming for them. It's also coming for the holdouts who say it has no effect.
Like a lot of tech before it I think the overriding theme is misapplication during a hype cycle.
lifeisloving 3 hours ago [-]
I actually dont let llms code anything non trivial, I will have it help with the planning a bit usually, but I write most of the code, and wow turns out my brain doesnt rot in the process and I actually understand whats going on.
Im convinced the people letting llms do their jobs are going to get replaced, not by agents but people who use them more reasonably.
cautiouscat 2 hours ago [-]
That’s true. But that’s a really small slice of the pie they’ve cut for themselves in hype and valuation.
jostmey 5 hours ago [-]
The problem was never generating leads. The bottleneck is validated results. It’s performing clinical trials proving efficacy. And this is where I think AI will have the biggest impact—-helping scientist, navigate study complexity and regulatory burden
pebbly_bread 5 hours ago [-]
If you can increase the fidelity of your research model (in-silico, murine, etc) to real life humans then there are fewer false leads.
moregrist 4 hours ago [-]
Drug design is hard because it’s a system problem not a molecule-protein interaction problem.
At one point the gold standard for generating leads was using combinatorial chemistry to experimentally screen through millions of compounds.
I’m not sure how wide-spread that is any more; it used a lot of reagents. And it ran into the real bottleneck: lead generation tells you little to nothing about the efficacy, toxicity, and side effects of a drug or biologic in actual humans.
In silicon will never do a better job at lead generation than combinatorial chemistry. It could help with the real bottleneck. But… there just isn’t a lot of high quality training data on this.
They’ve been pushing ML approaches to drug design since at least the early 2010s. The approach has evolved with the trends in ML. Overall, I think the results have been very mixed; much like the traditional pharma pipeline.
busyant 4 hours ago [-]
> At one point the gold standard for generating leads was using combinatorial chemistry to experimentally screen through millions of compounds.
I don't think this was ever the gold standard. I mean, some companies did employ these approaches, but they were generally viewed as low-quality, brute-force approaches (at least at the handful of companies I was associated with).
i000 4 hours ago [-]
That is not true. For many diseases we lack good hypotheses about the underlying causal mechanisms which resulted in decades and billions being pumped into few questionable targets (e.g. amyloid and alzheimers). In other diseases such as many cancers we often lack "actionable" targets, resulting in hundreds me-too companies all chasing the same target with only subtle variations in approach (inefficient capital alocation).
So AI could help a lot in discovery, much more than the engineering like uses in antibody/drug optimization.
3 hours ago [-]
qurren 5 hours ago [-]
The real problem is generating leads that are more likely to yield positive results than throwing darts at hypotheses.
That's what top-tier scientists are good at.
sagentra 5 hours ago [-]
[dead]
throw310822 5 hours ago [-]
"The problem was never generating leads" is an absurd statement without any reference to the quality of those leads. Ideally you want a system able to generate one more lead, the correct one.
RomanPushkin 4 hours ago [-]
I hope OpenAI will prove its usefulness in stealing joy from mathematicians, engineers, and biologists this time. It feels like there's a chance of warmer feedback this time from everyone out there keeping an eye on what they do.
Personally I would forgive all of the joy being stolen by AI if they discover something fundamental and outstanding that would help all of us.
dyauspitr 3 hours ago [-]
> stealing joy from mathematicians, engineers, and biologists
This is the weakest possible rationalization against the AI takeover. Solving real world problems isn’t “stealing joy”. Those problems shouldn’t be gatekept. It paints our scientists as rent seekers.
nritchie 2 hours ago [-]
This comment totally misunderstands why scientists get into science. Let me tell you, it isn't the money. It is for the joy of exploring the frontier. LLM's are taking this from us. Maybe they will be better than us but I'm not sure how many scientists will get into science for the joy of being an understudy to an LLM.
ChickeNES 2 hours ago [-]
It doesn’t misunderstand, it just treats that as irrelevant, which it is.
lkey 19 minutes ago [-]
If you could press a button and obliterate the joy experienced by every professional at their work, in exchange for a 1% boost in marginal productivity for the next 2 quarters, would you do it?
nilkn 58 minutes ago [-]
I understood them to be arguing that AI models are taking away the joy of certain things like mathematics but not producing commensurate value for humanity. We have a lower bound on twin primes, but that doesn't improve life for anybody, and the cost of getting the bound was removing human involvement from a lot of mathematical research, which was a source of joy for some portion of the human race. If all of this leads to curing major diseases without an AI takeover, it will have been worth it. But if it doesn't, then the ends don't necessarily justify the means.
RomanPushkin 3 hours ago [-]
> Solving real world problems isn’t “stealing joy”
Well, pretty good amount of the training data was stolen. Not only from the repositories without a license, but also archives of books, and they even steal training from each other. Funny enough, they still blame each other for stealing. I don't mind if you think your joy is not stolen. But I mind if you insist when your opinion is the only right one and joy has definitely not been stolen. It's quite sensitive territory starts here, and I don't think anyone (incl.yourself) has a right to speak for everyone in that regard.
BeetleB 60 minutes ago [-]
I keep hearing these analogies to "rent seekers" - particularly with mathematics.
I just don't understand it. No mathematician would be upset if a total amateur solves a centuries old problem - even one they've worked their whole life on. They cheer and celebrate it.
Nor do they oppose the spread of math knowledge.
Nor do they have high salaries. Nurses make more.
Where is the "rent seeking"?
binlog 3 hours ago [-]
“AI shouldn’t make groundbreaking advancements because the scientists who otherwise wanted to make those advancements feel sad”.
All those scientists can go pound sand as far as I am concerned. I don’t give a shit about “joy” I care about curing diseases and solving the universe’s mysteries. If AI can get us there faster then I’m 100% for it.
haickernews 2 hours ago [-]
> I don’t give a shit about “joy”
Exactly. Fuck these selfish pieces of shit for delaying me getting administered heroin in a cube until the heat death of the universe.
nritchie 2 hours ago [-]
Until there are no more scientists...
solyin 2 hours ago [-]
> I don’t give a shit about “joy”
> solving the universe’s mysteries.
What do you get out of solving the universe's mysteries then? Ennui?
2 hours ago [-]
2 hours ago [-]
mdevere 4 hours ago [-]
This is very, very weak.
Clinical science is inundated with well-reasoned "potential leads". Ideas for targets, and even designing drugs to interact with those targets in the desired way, is not the bottleneck. Hasn't been for decades. The bottleneck is in clinical development i.e. human trials.
There are many many AI drug discovery companies out there, many of them very well funded, and ALL of them with no shortage of "potential leads".
These companies usually start out with the idea that their potential leads are better than the alternatives (generally because they cast a much bigger net/ considered more screening criteria than a human could, thanks to AI) and that big pharma will pay them license fees.
And yet, all of those companies, pretty much without exception, have turned into drug development companies themselves. They are forced to develop their own "potential leads" into actual approved drugs. And they are subject to the same timelines, same costs and - so far - the same probabilities of success as any other drug developer.
PerturbAI & OpenAI's "potential leads" might be better or worse than the next AI company. I would guess worse, given there is zero proprietary data involved and no clarity about why the underlying models are going to generate insightful findings. Either way, not useful.
qlte 2 hours ago [-]
I just saw a similar post from Anthropic which also landed like a thud. The deep need of OpenAI/Anthropic to churn out flashy announcements today to with upcoming IPO is in serious conflict with the realistic pace of biological or medical research, let alone successful clinical applications. They would produce many cool leads like this which ultimately turn out to be useless before landing on the one that makes it to human clinical trials (and may fail there too).
A previous blog post from Anthropic used the mention of "CRISPR-like" to activate a mini hype cycle by association with a well-known groundbreaking discovery. Without that kind of manipulative hook these announcements are pretty thin gruel and below the bar of thousands of Pubmed papers that never made it into public view.
Metacelsus 3 hours ago [-]
So they did a perturb-seq experiment and then launched one agent per gene in the library?
Seems quite inefficient to me. Unless the goal is to spend millions in API credits.
5 hours ago [-]
londons_explore 2 hours ago [-]
And here is me just trying to keep ~10 agents busy....
lifeisloving 2 hours ago [-]
Well thats the trick. OpenAI publishes things like this, making you feel like you need to do more, you frantically increase your token usage.
You dont need too, I know like 2 people out of 30 devs I know closely who legitmately accomplish anything behaving this way and they were superhuman before AI as well, it probably has little to do with just having access to lots of agents.
dude250711 5 hours ago [-]
OpenAI in sciences: "We have bitten off a bit of each of these apples - you guys finish eating them, because that is what you are best at - finishing half-eaten food. May we have a $2T valuation, please?"
crmd 3 hours ago [-]
The valuation bubble pops if the market comes to believe frontier AI will not disrupt other industries at the rate that it did software engineering.
suddenlybananas 5 hours ago [-]
Why waste so much space on a chart on whether "human experts preferred distributed-agent reports over single-agent reports"? I thought we were supposed to be curing alzheimer's and cancer!
coppercrisp62 5 hours ago [-]
[flagged]
Noaidi 5 hours ago [-]
I am sorry, but if you still have stupid humans these leads will end up going the same place all the leads go. Nowhere.
So what if DCTN1 is linked to Alzheimer's? All they will do is invent a drug to mess with the enzyme and it might only still help a small percentage of people and no one will be able to afford it.
It is well know that diet plays a large role in Alzheimer's[1] and is largely an issue of personal genetics and environment.
If anyone cares to comment why I am wrong here I would appreciate it.
lirolero 3 hours ago [-]
[dead]
anfogoat 3 hours ago [-]
More PR bs from unscrupulous people. Until you've cured an actual disease for actual people, please shut up.
vatsachak 4 hours ago [-]
"new leads"
I use LLMs every day but damn... can we please market them and value them as a coding tool and not the savior/destroyer of the world. "new leads" comes off flat after the previous tone
sweetdingoes 4 hours ago [-]
[dead]
Rendered at 20:47:06 GMT+0000 (Coordinated Universal Time) with Vercel.
Its not surprising to me that this press release looks half-baked.
In which case congratulations you’ve just been promoted to manager with no pay increase!
Joking aside Ai is doing a large chunk of my job but all it’s done is shifted what I actually spend time on.
It’s not really saved any man hours.
Think of it this way. It's as if a public company gives you a certain amount in RSUs that won't vest for a while. A year later, the company is worth 10x more. So they list the increased value of the RSUs they owe you as a loss.
In reality, the fact that this "debt" has ballooned so much is a positive sign - the valuation is high (it's a separate issue whether that valuation is realistic).
Their "real" losses are about $8B.
Also the handwritten code doesn’t remove the work. If anything, it makes the thinking more difficult (for me) because instead of thinking during the coding, I have to before and after (in iterations).
For big projects I actually go back to tradcoding some to make sure I understand the system, since I’m the one responsible.
Like a lot of tech before it I think the overriding theme is misapplication during a hype cycle.
Im convinced the people letting llms do their jobs are going to get replaced, not by agents but people who use them more reasonably.
At one point the gold standard for generating leads was using combinatorial chemistry to experimentally screen through millions of compounds.
I’m not sure how wide-spread that is any more; it used a lot of reagents. And it ran into the real bottleneck: lead generation tells you little to nothing about the efficacy, toxicity, and side effects of a drug or biologic in actual humans.
In silicon will never do a better job at lead generation than combinatorial chemistry. It could help with the real bottleneck. But… there just isn’t a lot of high quality training data on this.
They’ve been pushing ML approaches to drug design since at least the early 2010s. The approach has evolved with the trends in ML. Overall, I think the results have been very mixed; much like the traditional pharma pipeline.
I don't think this was ever the gold standard. I mean, some companies did employ these approaches, but they were generally viewed as low-quality, brute-force approaches (at least at the handful of companies I was associated with).
So AI could help a lot in discovery, much more than the engineering like uses in antibody/drug optimization.
That's what top-tier scientists are good at.
Personally I would forgive all of the joy being stolen by AI if they discover something fundamental and outstanding that would help all of us.
This is the weakest possible rationalization against the AI takeover. Solving real world problems isn’t “stealing joy”. Those problems shouldn’t be gatekept. It paints our scientists as rent seekers.
Well, pretty good amount of the training data was stolen. Not only from the repositories without a license, but also archives of books, and they even steal training from each other. Funny enough, they still blame each other for stealing. I don't mind if you think your joy is not stolen. But I mind if you insist when your opinion is the only right one and joy has definitely not been stolen. It's quite sensitive territory starts here, and I don't think anyone (incl.yourself) has a right to speak for everyone in that regard.
I just don't understand it. No mathematician would be upset if a total amateur solves a centuries old problem - even one they've worked their whole life on. They cheer and celebrate it.
Nor do they oppose the spread of math knowledge.
Nor do they have high salaries. Nurses make more.
Where is the "rent seeking"?
All those scientists can go pound sand as far as I am concerned. I don’t give a shit about “joy” I care about curing diseases and solving the universe’s mysteries. If AI can get us there faster then I’m 100% for it.
Exactly. Fuck these selfish pieces of shit for delaying me getting administered heroin in a cube until the heat death of the universe.
> solving the universe’s mysteries.
What do you get out of solving the universe's mysteries then? Ennui?
Clinical science is inundated with well-reasoned "potential leads". Ideas for targets, and even designing drugs to interact with those targets in the desired way, is not the bottleneck. Hasn't been for decades. The bottleneck is in clinical development i.e. human trials.
There are many many AI drug discovery companies out there, many of them very well funded, and ALL of them with no shortage of "potential leads".
These companies usually start out with the idea that their potential leads are better than the alternatives (generally because they cast a much bigger net/ considered more screening criteria than a human could, thanks to AI) and that big pharma will pay them license fees.
And yet, all of those companies, pretty much without exception, have turned into drug development companies themselves. They are forced to develop their own "potential leads" into actual approved drugs. And they are subject to the same timelines, same costs and - so far - the same probabilities of success as any other drug developer.
PerturbAI & OpenAI's "potential leads" might be better or worse than the next AI company. I would guess worse, given there is zero proprietary data involved and no clarity about why the underlying models are going to generate insightful findings. Either way, not useful.
A previous blog post from Anthropic used the mention of "CRISPR-like" to activate a mini hype cycle by association with a well-known groundbreaking discovery. Without that kind of manipulative hook these announcements are pretty thin gruel and below the bar of thousands of Pubmed papers that never made it into public view.
Seems quite inefficient to me. Unless the goal is to spend millions in API credits.
You dont need too, I know like 2 people out of 30 devs I know closely who legitmately accomplish anything behaving this way and they were superhuman before AI as well, it probably has little to do with just having access to lots of agents.
So what if DCTN1 is linked to Alzheimer's? All they will do is invent a drug to mess with the enzyme and it might only still help a small percentage of people and no one will be able to afford it.
It is well know that diet plays a large role in Alzheimer's[1] and is largely an issue of personal genetics and environment.
[1] https://news.harvard.edu/gazette/story/2024/07/alzheimers-st...
I use LLMs every day but damn... can we please market them and value them as a coding tool and not the savior/destroyer of the world. "new leads" comes off flat after the previous tone