In a year or two, articles like this will either be artifacts from peak hype or evidence of the beginning of the singularity. Right?

That's black and white thinking; it will be a midgularity - so neither.

Mehgularity

The singularity, as defined by Hinton (and others) as RSI (Recursive Self Improvement) may actually be beginning already, as OpenAI has announced an AI acting as a "research intern" (!).

How is it improving, that would require rearranging its weights and biases which it cannot do easily or quickly.

Is easily and quickly a requirement? Isn't it enough that over time it improves itself even if the process is complex and slow?

Self improvement during training, and AI self training are already happening. Easily/quickly are seemingly a factor of how much power/hardware you want to use at once.

With the level of compute they have they aren't stuck with frozen models like you are.

How is this different from arguing that Microsoft Clippy was RSI? An AI tool being involved in the process of work can't be the bar for RSI.

I don't think there can be a coherent definition of RSI unless people lay out their theory for how intelligence scales. LLM-assisted coding is great but respectfully optimizing pytorch features or whatever is not gonna lead to exponential improvements. That approach to scaling diminished years ago, leading all the labs to switch to reasoning.

Now it seems reasoning is also yielding diminishing returns, so all the labs are pivoting to specializing in particular fields like math / infosec / biology. They're improving due to accessing new proprietary training data and doing RL with human experts. Again I don't really see any amount of "AI research interns" leading to an exponential improvement to this strategy, they're not the bottleneck in the first place.

Now it seems reasoning is also yielding diminishing returns

Not true. On the contrary, LLMs are developing faster than predicted. They were expected to solve a Millennium Prize by 2030... and here we are in 2026. Release cycles are getting faster. Just compare the most recent GPT or Claude with what they were an year ago.

How is this different from arguing that Microsoft Clippy was RSI?

We can argue about semantics, but that's not really the point. The point is that what started now - which no doubt is in its infancy - will result in full autonomy quite soon (they project an year or so), with the risk of RSI causing agent development to slip (long term) outside human cognitive control/capacity.

Now it seems reasoning is also yielding diminishing returns

Is the diminishing returns in the room with us?

so all the labs are pivoting to specializing in particular fields like math / infosec / biology.

They're not pivoting to anything. The goal has always been creating a machine that could automate all or nearly all human work. They're just coming along on that mission.

As for RSI...I think the term is a bit odd in the modern context. It was created at a time when conventional wisdom was that generally intelligent machines would be these logic automatons that could "alter their own code". Instead we have massive neural networks that take months to train.

In this paradigm, the ways a LLM could "improve itself" would be altering its own weights directly or creating and training better, vastly more efficient architectures for the next generation of models.

The former is probably not happening but the latter is possible.

Yes, diminishing returns. Not overall, they've still been able to create more intelligent models even up to today. But the strategy for scaling that intelligence has shifted. From the initial ChatGPT release to GPT-4.1, they were basically scaling up compute training compute / model size. Then 4.5 flopped, while o1 demonstrated that gains could continue by reasoning (scaling up compute at inference time). o1 is now the ancestor of all their flagship models from GPT-5 on.

This is why I'm trying so hard to drill down on the theory of scaling, and not just talk about improvement in general, hand-wavy terms. If the bottleneck of current scaling strategies is training data, or something fundamental about the model architecture, then just throwing more harnessed chatbots at it won't lead to an exponential increase in performance.

Now you could argue that the AI we have now will help us find that change in architecture, and I would agree. But that means we're firmly outside the singularity for the time being, and what people are in fact talking about is a hypothetical.

Then 4.5 flopped, while o1 demonstrated that gains could continue by reasoning (scaling up compute at inference time). o1 is now the ancestor of all their flagship models from GPT-5 on.

That's not quite right. They are still scaling model size and have had several new base pre-trains, just nothing so big as 4.5 (as far as we're aware). o1/4o has not been the base for some time now.

Data is obviously a bottleneck for some regimes and LLMs will have to get their hands dirty experimenting but it doesn't look like an insurmountable wall either.

This is great, but I can't help but wonder if we're going to have another post next week with a lab complaining that they were about to publish this same finding, and they had Claude proofread their paper, and whoops how'd that get into Anthropic's training data?

Lots of stuff gets discovered by AI bots that was always hidden in plain sight. They're remarkably good at "connecting the dots".

This is a very inaccurate manipulation of facts that fundamentally misrepresents everything that mathematicians wrote.

I wonder how long it will take for the damage Alpöge and Buckmaster have done to the perception of these AI-driven scientific developments to fade.

Not saying that they were right or wrong, but that single moment sullied all AI-driven breakthroughs that came after it, and I don't think it was ever particularly relevant, at least not nearly to the degree that it was presented in the media. But I guess it ended up being a convenient outlet for AI anxiety in the end.

I don't think of this stuff in terms of AI anxiety, I just think that the AI labs should be falling all over themselves to display deference and humility to those who made it possible.

The LLMs that make this stuff possible weren't created by the AI labs from whole cloth. They crept up and jumped onto the shoulders of giants, basically the collected (non-consensually, of course, but jingles keys look at this pelican riding a bicycle!) works of humanity. Every discovery LLMs enumerate in this fashion rightfully needs to have a billboard-sized asterisk regarding the provenance of the discovery. "Claude" didn't discover this, everyone who worked to produce the internet that Anthropic siphoned into their dataset belongs on the credits.

It's great that it happened, and I wish them the best of luck in using our work to make the world a better place. Just don't forget who the rightful owners are.

This shows why biology is so much harder a problem area for LLMs than math, finding RTs is tedious but pretty doable today, they had to scope the problem down a lot from something that would be the equivalent of Navier Stokes in biology. Glad they’re doing it though, even if it’s just marketing.

Every day now I expect that they or somebody alike will discover in our genes that we (ie life) are lambda terms, combinators or something similar to Universally Programmable Intelligent Matter https://web.eecs.utk.edu/~bmaclenn/UPIM/UPIM3.pdf or chemSKI https://imar.ro/~mbuliga/talks/chemski-with-tokens.html

All it takes is to identify the syntax, so to say.

This is something I like joking around about, with regard to how LLMs are 'decent' [debatable but taken as a premise] software engineers. For a long time people have said DNA/RNA/etc is the programming of life.

If it is indeed HIGHLY analogous to programming, we would then expect LLMs/future systems to be HIGHLY proficient at accurate ex-vivo gene [or enzyme/protein] modification/construction

I have bookmarked the links to read later but until then I would ask in what sense? To my knowledge the known physics currently is all within the realms of a Turing machine, which is equivalent to lambda calculus.

It's really a matter of iterating on the problem and validation right?

Models make progress on coding and math because they can write tests and proofs to an extent. Many industries that are more 'physical' and require performing experiments lack that instant feedback loop. Find a way to close that loop and AI begins to look useful.

But try and convince companies to invest on closing that loop just to see if the current models work well on their problems or not? Tough sell. So Anthropic just shows them, hey look, this is possible and if you don't do it I will.. so they fold.

Biology is much harder than math for humans as well!

I don't think that's a given - not sure how you'd even quantify that comparison.

My argument is mostly about the complexity and the immensely intricate physicality of biology.

We can barely inspect much of it, let alone fully understand it.

LLMs are really good at discovering patterns on huge dataset. Google also had similair breakthrough discoveries they stopped marketing them

yes and no; you cant dump DNA in the context window and call it a day, in the blog post it was a common tool calling session. you do can have actual ml models for that, that the llm could use as a tool.

Don't use it for biology, Dario said, as he turned humans into Teenage Mutant Ninja Turtles.. I reckon that soon, he too will return to dimension X.

It's clear Dario believes that the solution to AI's PR problem is to cure cancer. Or invent other revolutionary medical treatments. They're going to heavily promote every step along the way no matter how small or far away from commercialization they are, like this one.

No doubt that curing cancer would help, but I think the timeline might be a little too long. Even RSI AGI will not be able to get new medical treatments to market instantly. Real world testing takes a long time and is an unavoidable part of the process.

Even RSI will not be able to get new medical treatments to market instantly. Real world testing takes a long time and is an unavoidable part of the process.

Is it unavoidable, though?

In the way that breathing is unavoidable. Like yeah technically there is a way to avoid doing it, but not a way that you want to seriously consider.

Cancer can be cured in a lot of cases, its just so damn expensive and the treatment is beyond torturous that some patients cannot handle it. Stem cells are amazing. But we need cheaper technology to replicate them into the cancer destroyers they need to be, as well as find ways to ease the pain of that internal battle.

Please tell me more about these “cures” you speak of. Because to my knowledge, yes we are good at getting patients into remission, we do not have “cures” Coupled with the fact that treatment is often life altering in and of itself

CAR T-cell therapies (immunotherapy, tldr priming the immune system to respond)

https://www.cancer.gov/about-cancer/treatment/research/car-t...

https://www.cancer.gov/about-cancer/treatment/types/immunoth...

https://en.wikipedia.org/wiki/CAR_T_cell

https://www.theguardian.com/society/2026/may/10/cancer-treat...

https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

Semantics. Cancer is uncontrolled growth of cells. Treating it is killing/removing the cancer cells. Problem of course is you are never sure if you got all of them. If you got all of them you are “cured”. If you didn’t you are not cured in case the remaining cells manage to grow and spread again. We don’t talk about “cure” because of course it is impossible to verify if 100% is gone or not.

Why is it 'of course impossible'? Couldn't we someday have nanobots or other tech that could screen all your cells and be able to indicate whether any cancerous cells remain?

In addition to the other comment mentioning CAR-T therapies, we also have therapies based on tumor-infiltrating lymphocytes (TILs)

https://www.cancer.gov/news-events/cancer-currents-blog/2024...

https://jitc.bmj.com/content/8/2/e000848 (careful: Figure 1 can be very graphical, but it shows the huge positive impact of this therapy)

We also have therapies based on monoclonal recombinant antibodies conjugated with chemotherapeutics. Simply put, we can produce antibodies that are specific for markers present in the surface of cancer cells, and we can attach drugs that can kill those cells. The antibody part is what makes this type of therapy very effective (you target only cancer cells, and not healthy cells) and also very expensive.

Real world testing takes a long time and is an unavoidable part of the process.

Not if it's a virus

Nothing like releasing poorly tested viruses on the public to really earn trust.

Dario would like to ‘cure’ aging. He’s got some personal experience with bad illnesses, but aging isn’t that. I also have reduced trust for people who want to live forever and don’t have kids.

I also have reduced trust for people who want to live forever and don’t have kids.

How so?

Not OP, but wanting eternal life without leaving a legacy just sounds like someone trying to be a god and is very narcissistic behavior

Or they just enjoy life and want to keep living? What about it is 'trying to be a god'?

The never dying part...

I also have reduced trust for people who want to live forever and don’t have kids.

I want to live forever (or until I'm bored of it) and I don't have kids. I'm not sure what that has to do with trustworthiness.

Edit: And, you're saying you want to die. Is that more trustworthy than not wanting to die? I suppose if you are religious, you might believe you're going somewhere good when you die, in which case, you don't actually believe death exists, so we're having different conversations. I believe death exists and is permanent, and I'd like to not do that.

Do you not want other people to die and be replaced?

How can you want for other people what you don't want for yourself? Why should other people die, for example of cancer, when having the chance I'll opt for the cure?

I don’t want to live longer than a natural human lifespan. When I was younger and immature I did, but I’ve outgrown that. Death is as natural a part of life as birth.

Obviously not? What an insane question

You would like Trump and Biden and their generation of leadership to be in power for the next 200 years? You would like for there to never be a disruptive new generation of people bringing fresh ideas and fresh thinking ever again? You wish to be encumbered by 17th century thinking and ideas for the rest of eternity because those people never died and grew set in their ways?

Not Op but there’s a inch of people asking why, and I have a similar feeling to op so here’s my post hoc justification for a weakly held and poorly supported prejudice:

It’s really because statistically, in my experience people without kids are more selfish than those without. This is more in description than judgement, but it’s true in my experience. We can speculate as to reasons, but looking after kids does train a certain kind of selflessness. Agreed we might be doing it for ultimately selfish reasons (self presentational or for care in old age or whatever). But for a good chunk of the time, caring for kids seems to require the fairly consistent subjugation of personal preferences, and a degeee of perspective taking, that I just think people without kids don’t have. And that often shows in their interactions at work and in daily life. Obviously there are myriad exceptions. But it’s true enough in my experience.

The wanting to live forever part also seems weird to me, and correlated with a certain sort of self regarding perspective. It seems obvious to me that I (or my generations) need to die for my children and grandchildren to have a good life. To try and subvert that also seems selfish or self important somehow.

I’m not really arguing this is a correct or good or just position. It might be terrible! But it did resonate..

It’s really because statistically, in my experience people without kids are more selfish than those without.

That would certainly be your opinion. I think the ultimate selflessness in a world being more and more damaged by humans would to elect not to perpetuate the species, and help try to leave the world a better place for those who do choose to have kids.

That's an absurdly selfish position. You're taking a stance that not existing is superior to living in the future, all the while living in the world yourself. Might as well advocate for nuclear genocide.

The flaw in that ideology is that everyone relies on the next generation for care in their old age. Taking advantage of the future generation without contributing to raising it isn't selfless in the slightest.

If you live in a developed country you probably already have a demographic crisis. Not having kids is hurting the next generation, not helping.

It’s really because statistically, in my experience people without kids are more selfish than those without.

I've witnessed the opposite: Having kids made people much more selfish. Resources were plenty before they had kids, so they would spend a lot (time and money) on others - be it friends or the general public.

When kids come along, two things happen:

1. Resources are limited, so a lot less goes outside the family.

2. At least one parent will put the foot down when being generous to people outside the family - even if the wealth/income supports being able to do so. Tribalism sets in.

Selfishness is commonly understood as putting one's own interest above everyone else's to an excessive degree, not the interest of their family. If you redefine it to include family interests then I think everyone would agree that having a family makes people more selfish, often dramatically so.

I just object to the redefinition.

I think this "redefinition" is apt in the context of the conversation. It's about people mistrusting those without kids because they are viewed as selfish, and I'm pointing out that they're often the least selfish, and more likely to "help the world" in situations where they do not benefit.

Paying full taxes to support a society where people with kids pay less taxes and receive more benefits from the State is certainly not selfish. That's the case in my country, at least.

The wanting to live forever part also seems weird to me

Wanting to die after a handful of decades seems weird to me, especially if you're in good health.

It seems obvious to me that I (or my generations) need to die for my children and grandchildren to have a good life

That is very much not obvious.

I've long been thinking about making a browser addon to block HN users. You've inspired me to get this done tonight, thank you for the push, your comment is unhinged and I'd rather not ever have to read what you say about anything else.

I want to live forever (or until I'm bored of it) and I don't have kids. I'm not sure what that has to do with trustworthiness.

When I hear people say stuff like this, I hear that they want to remove the single most universal chesterton's fence in all of living systems. I hear them take pride in their/our hubris, and demonstrate willingness to put the whole multiplex ecology of life at risk because they believe themselves/us to be more clever than thermodynamic evolution.

Biological singletons (outside very specific niche situations) are not meant to persist, and most anything that has tried, it has simply been selected out of the lineage. This constraint (which we don't understand yet) is presumably the whole reason why biology discovered and moved into the more ephemeral higher-order substrate of thought and culture.

Just my feelings though. Feel free to disagree.

Chesterton's fence implies intention, a will, a decision to stand up the fence. I don't believe in gods, so my existence and its length were determined by a series of accidents. It isn't right or wrong or even optimal, it's just the traits that survived thus far.

It isn't even a rule of biology. There are living things with much longer lifespans than humans, some even effectively immortal (absent predation or accident or climate change).

Your language implies you believe in a creator of some sort, something making decisions about how things should be. You've called it "biology", but "biology" doesn't "discover" or have a "reason" for doing things.

I hear them take pride in their/our hubris, and demonstrate willingness to put the whole multiplex ecology of life at risk because they believe themselves/us to be more clever than thermodynamic evolution.

I hear you taking pride in accepting death on a quite short timespan as a necessity, and hubris that one individual living longer puts "the whole multiplex ecology of life at risk".

We have already disconnected from evolution, to a large degree. Many people who would have died in childhood a couple hundred years ago now survive to adulthood and procreation.

Should we stop vaccinating children because they were supposed to die to protect the delicate balance? Surely it is hubris to prevent their deaths when evolution and biology discovered polio and smallpox to kill and maim them? If there is a biological Chesterton's fence it is probably sitting somewhere around five years old and half of people wouldn't make it past it.

Chesterton's fence implies intention, a will, a decision to stand up the fence

It most certainly does not.

How could it not? Chesterton's fence asks the question, "Why was it put there?" Without a will you can only answer "how was it put there" and not "why".

There is an assumption of correctness in the argument that "we must die because we do die". It's tautology. That doesn't comport with my understanding of how we got here, and I don't believe there is an answer to "why" we are here, beyond the meaning we make of our own lives. If our 70-90 year lifespan (if we're lucky and aren't struck down younger) is an evolutionary accident, and I believe it is, then extending that lifespan is Good, Actually.

As one obvious example, evolution is not agentic but still answers "why" questions.

"Why do we have a heart" "Why do we sweat", etc.

But Chesterton's fence is often used in an even MORE generalized way than just that, not "why is it there" but "what are we not seeing about how this connects to everything else"

As an example, eradicating mosquitos. We see many obvious reasons why it might be good, we can even see that they don't seem that important in the food chain, but it would be hubris to assume we understand every potential connection they have to world ecology.

they believe themselves/us to be more clever than thermodynamic evolution.

"Thermodynamic evolution" says that sick kids should be left to die so that we can replace them with a better roll of the genetic dice. Yes, I do think we're more clever than that.

sick kids should be left to die so that we can replace them with a better roll of the genetic dice.

That's not what I'm saying. Sick kids dying is not the same as old people living and holding social/economic/positional/etc capital into perpetuity.

And further, what I'm saying is about "us" as a larger living system, at coarse-grain scale. We each live at fine-grained scale. Negotiating truths and values between those is the fuckin work of being alive. Bluntly, some might reasonably ask: who would reasonably prioritize your individual happiness and health if the cost on your society/culture means a trend toward collapse? That's not me saying "I don't care about you" (I do!) but it's me pointing out that there are fuzzy lines when negotiating values across scales. A thing that makes you happy (heck, that makes a majority happy) might conceivably invite some variant of the endtimes. Something good for the health of some parts can be bad for the health of the whole.

Death is part of our thriving and a part of us ("us" in the Gaian sense) at the largest coarse-grain scale, though it hurts like hell at the fine-grain one

who would reasonably prioritize your individual happiness and health if the cost on your society/culture means a trend toward collapse?

What evidence do you have that people living longer would cause a trend toward collapse? What evidence do you have that people who live longer and without debilitating health problems wouldn't care more about the future of our planet and society and be able to achieve more toward improving it?

You're accusing people who want to live longer of selfishly causing societal collapse acting as though you're taking a moral high road, preserving a precious thing, but you're arguing that 8 billion people alive today should die. That's a remarkable bit of ethical gymnastics and a monstrous position to take by my reckoning.

I was kind of OK with it when I was thinking, "OK, religious people believe nobody ever really dies." Which I believe is a fairy story, but one that many people believe and are raised to believe. But, yours seems to be your own brand of religion, and it doesn't even pretend people actually never die and go to heaven but you want it to happen to everyone anyway, which is really something.

There is no coherent reasoning with this crowd. I have had hundreds of discussions of this form. In the end, in every case: it's just rationalized copium about the fact that they will die.

It is very easy for them to say "people should die" on an Internet forum. On their (or a family member's) deathbed, presented with a cure to death, they would say something very different. When push comes to shove, no one but the suicidal actually hold the belief that people should die.

In my experience the pro-death crowd takes this stance because they don't dare to dream of a world in which death is cured - because you can't get hurt by the potential of a future you don't believe in.

The prejudice is based on billionaires being the first to get access to the cure for aging in these hypothetical scenarios.

While everyone else can't afford it. Hard to think of a more demoralizing "off with their heads" dystopian scenario.

I also have reduced trust for people who want to live forever and don’t have kids.

Why are you only allowed to live forever if you have kids?

Seems like someone seeking immortality should be willing to do for the elixir if they want it even a little bit...

Why? Who in their right mind would have children in 2026? Everything is burning, gone to shit, and projected to get worse. Having children is insanely irresponsible.

HackerNews' neuroticism is unmatched

Your dramatization of society's ills are not tethered to reality

It's not? Have your seen climate change forecast? Have you seen the cost of diesel? Eeosion of democracy in the US?

Have you lived long enough to see it go up and down?

Please. Every single age of humanity, there have been hardships. It was actually much worse before: Diseases galore, famine, pests, wars. You're severely negatively biased as is a lot of other people I've seen.

I don't care how hard it was to live in Abyssinia. This is absolutely the worst time to try to make a life in the United States since WWII ended 80 years ago, and there's every reason to believe it is going to continue to get worse for a long time. I have no idea why you are dismissive of people saying this is a difficult time.

Probably should have left off the kids, but lets start with just distrusting anybody who wants to live forever. At the level of influence billionaires have, it is downright dangerous.

For everyone else confused: Think of all the people throughout history we would prefer would not have lived forever. Then multiple that by A LOT. Then consider how greedy and sociopathic most of the billionaire class is already.

Now, we could spend time getting distracted by childless. I don't think it matters.

I mean, wanting billionaires to not live forever (read: wanting power structures to not become excessively entrenched) is a pretty different thing.

I'd even be fine with people who are billionaires living forever, so long as they don't remain billionaires / don't fuck with politics / etc.

You can't have your cake and eat it too.

Fundamentally the problem with living forever goes beyond billionaires. People get stuck in their ways of thinking, the mindset of living forever is completely different. Why should I even listen to someone who only lives a mere 40 years? What is a suitable punishment for someone that lives forever? How does it change murder?

Philosophically, living forever may be corrupt by nature.

The only way to tear down tiers of society is for some of those tiers to literally die off.

I also have reduced trust for people who want to live forever and don’t have kids.

I have reduced trust in people who make judgements about the value systems of others based on fairly meaningless characteristics.

> the solution to AI's PR problem is to cure cancer

I think its much simpler than that. Anything actually useful for people would be a good solution.

Obviously image gen and code gen is not the case, as though it does increase productivity, it doesn't make anyone's life actually better. If it led to 4 day work week - sure. Otherwise it could easily be net negative.

If something is being used, it's by definition useful, and AI is used a lot.

Really now, everything is bad? Trying to cure diseases? Talking about it? That’s bad somehow! Let me sit here on my ass and do nothing instead.

Who are you referring to? This reads like projection.

Read the comment. This is cynical and bad because they’re going to advertise that they’re trying to do something socially beneficial.

It’s the top rated comment in the thread. Somebody tried to do something good, this is the response.

This pisses me off severely.

You're only seeing part of the picture and you're pissed off about how people dislike the whole other part of the picture you're disregarding.

No wonder it feels confusing.

Your comment is vacuous. There isn’t any other part of the picture. Trying to advance medicine is inherently good. It doesn’t matter how much you use it for marketing. None of what they have done is fake or useless, it is at worst early.

Unit 731 supposedly advanced medicine no?

This is just silly.

There isn’t any other part of the picture.

Except there is. At the risk of mixing pop references, you're a Sith dealing in absolutes saying "doesn't look like anything to me".

Would you care to state what this picture is?

In fact, I think it's great and I'm rooting for them. I just don't think it's likely to improve AI's public image anytime soon.

You can't say this. We have no idea. There is nothing about the law of physics that pushes cancer cure a long time away. A lot of people would have told you AI was decades away, yet here we are. We are still on track for possible strong take off.

Now on real world testing, you think the rule applies? I tell you it doesn't. Human life might be precious, but human life in practice is also not precious. We waste so much of it. In some countries regulations will stop/slow it, but there are plenty of places around the world that will turn a blind eye for a fistful of dollars. Countries will go to those locations if it means gaining an edge.

please no more doomer talk, can we just be excited that we have ai doing science

I am already having a headache thinking of the whining from the biologist community (if any? I hope their reaction is not as extreme as that of mathematicians).

Real world approvals for drugs are accelerating through, even with all the steps. Think about it, Moderna went from zero, to approved vaccine in 10 months. While COVID vaccines were the exception, not the rule, there are ways to accelerate the process if there is will and $$$. In the last 20 years, the number of new drug approvals per year in the US has doubled, and the length of time to get approval has been cut in half.

the length of time to get approval has been cut in half.

Is this true? I haven't heard this before. Cost to get approved is also important, are we making progress there?

I think this approach of actually doing useful science is better PR than hiring an army of influencers to shill for you, OpenAI style.

Generally speaking, hiring an army of influencers to shill for you results in bad PR, and comments like this one.

You really think there aren’t an equal number of Claude influencers on social media?

Yes, I think there aren’t an equivalent number of Claude influencers on social media.

Is there an equivalent headline for Anthropic of this?: https://www.businessinsider.com/inside-open-ai-influencer-ma...

Takes 2 minutes to search for news beyond the HN front page - https://www.cnbc.com/2026/02/06/google-microsoft-pay-creator... https://www.inc.com/georgia-fearn/openai-anthropic-both-cour...

https://www.businessinsider.com/emma-orhun-canceled-claude-p...

Anthropic’s head of influencer, Lexie Barnhorn, has described creators as essential to building trust in complicated technical products. Its strategy is partly consumer-to-business: People who adopt Claude personally may later introduce it in their workplaces.

Anthropic’s best-known creator events have been smaller dinners and pop-ups in which Claude remained the ostensible subject.

Personally I feel like Anthropic is underrepresented in "normie" marketing, all of my non-tech savy friends only know of ChatGPT and use "ChatGPT" in the same way my mom says "Nintendo" when talking about game consoles

I’m confused why AI companies are using agents in-house for this type of research instead of partnering externally.

I guess the improvement loop is tighter and they have more control over how discoveries can be used for marketing?

But, in my mind, it begins to feel like they are setting themselves up to be “everything” companies instead of focusing on their core product…

Because the goal is marketing and maxxing the IPO, not real-world results.

Better than doing this, just in case you hadn’t heard: https://www.businessinsider.com/inside-open-ai-influencer-ma...

...which Anthropic is always doing:

  Who, you may ask, would take that money? People like business influencer Megan Lieu, who chose not to disclose just how much she'd made from her AI deals, but says her biggest sponsorship to date has been with Anthropic (makers of Claude), as well as that her biggest sponsored contracts (for any client) are normally around the $30,000 mark.

(from the third link)

https://www.cnbc.com/2026/02/06/google-microsoft-pay-creator...

https://www.reddit.com/r/NYCinfluencersnark/comments/1sn3t9k...

https://aftermath.site/ai-influencer-creator-deals-sponsorsh...

If an amazing drug or other therapeutic falls out of this I bet they would be happy to own it outright.

Because their core product is not a long-term sustainable business strategy. Local hardware and models will continue to improve to the point of not needing the hosted solutions. And if you do need a hosted solution, remember that the big cloud providers already offer these solutions, so signing up for OpenAI/Anthropic _and_ AWS/GCP/Azure is not a sound business decision compared to just signing up with 1 of them that offers your cloud infra + GenAI infra. (Which is why the long-term benefits for cloud companies will probably be for the likes of AWS and not the likes of OpenAI).

They'll continue to burn money for marginal model improvements in the next few years all the while having no moat _and_ having Open-Weight / Local models eat their lunch.

The only way for them to stay relevant as a company is to expand beyond simply providing the models.

I'm old enough to remember the arrival of RDBMS, once IBM primed the space with DB2.

There was a pitched battle over features like row-level locking as competitors like Sybase, Ingress and Oracle scrapped it out. New features arrived on a monthly cadence, with immense engineering effort behind them. The winners (Oracle mostly) won a great moat which led to them to where they are today.

The fact that so many AI companies can produce amazing coding tools so quickly shows there is no moat, supporting your theory.

The AI companies moat, if any, is hoarding all the hardware so local solutions are no longer cost-effective.

It is more of a regulatory capture byproduct to prop up an artificial token driven Ponzi scheme.

There is a serious alternative to NVIDIA "AI" hardware dropping out of China in February 2027. There is no moat, but a whole lot of unpaid debts in the near future.

Popcorn ready =3

Which Chinese alternative is that?

Huawei is upgrading its Ascend 950PR (2.8 times an Nvidia H20 performance.)

https://apnews.com/article/huawei-ai-chips-nvidia-superpod-t...

Take it lightly until the benchmarks drop. ymmv =3

I honestly have no expert knowledge about this stuff. What I say is based only on intuition.

  - China is heavily, heavily incentivised to enhance their own chip making
  - Looking at the rate Chinas has expanded into just about every single other
    space, and from quantity to quality, I just think it is impossible that they
    don't compete on equal grounds pretty soon.
  - I don't buy the insurmountable moat of TSMC

This is not really sustainable when there is a constant supply of increasingly powerful and efficient hardware.

Because clients don’t know how to use the tools.

I run into this all the time - we have such powerful functionality available to our users, and further we provide the elements that undergird all of it, so it’s totally possible for clients to take the services they buy from us and reconfigure them to make their own tools, better even than the ones we have built, purpose-built for their workflows…

And 9/10 clients will just click on the one thing they know and recognize and are familiar with and comfortable with… and then stop thinking about it.

It’s crazy how much of our job is not only building our product, but interrogating our clients over what they need, so we can demonstrate how our tools solve their problem. The users simply are not interested in figuring it out for themselves.

A chatbot for cancer researchers to talk to is worth single-digit billions at most. Anthropic is already valued at over a trillion dollars, on the premise that they can replace the majority of jobs in most knowledge industries. All the announcements about hacking / math problems / biological science are meant to create the impression that that strategy works and is repeatable across industries.

Cancer research is a lot harder for LLMs than math millennium problems though, because there is no fast feedback loop to iterate on. Even if you have a really good idea based on a solid theoretical insight, doing the experiments using in-vitro/mice/monkeys/humans can take years or even decades. I have no doubt that AI will help find new avenues that boost certain parts of research in these fields, but I don't see a potential for a drastic change until we at the very least give LLMs a direct way to interact with lab equipment and train them using RL on it.

... until we at the very least give LLMs a direct way to interact with lab equipment and train them using RL on it.

Which is exactly what is being done.

https://www.reuters.com/world/anthropic-quietly-sets-up-biol...

Not according to Anthropic:

  Our lab, located in the Bay Area, looks like a typical molecular biology lab. We do research that involves only the lower-levels of the biosafety risk level (BSL-1 and BSL-2) and we do not handle pathogens that can infect humans. All of the lab work is performed by human scientists. Although we’ve experimented with using AI to accelerate lab work with initiatives like the Model Hardware Standard, this approach is less conducive to the sort of ad hoc workflows that are involved in our molecular biology research.

I was actually thinking the other day that it makes perfect sense for AI companies to develop a professional services oriented software development arm. Imagine that you want to develop a training pipeline for "tasteful" programming: you might make a reward metric for that does some obvious stuff (nothing that anyone could easily agree is a bug like a crash, good performance, perhaps minimize LoC), but you really want to also want to also track "bugs" where the feature was discovered to be missing some unspecified nuance that was only discovered through product use, or train on ability to keep a small codebase while also keeping diffs small (essentially, "maintainability") as real new requirements come in.

So then you want a training set full of real product requirements and product evolution, which is something you could get if you offered custom software development, with a lot more control than you'd get trying to do the same by scraping random FOSS projects on github.

Other industries are perhaps similar. If you offer a service directly, you have much more ability to build collection of training data into the process. Want to make the best law bot? Buy a law firm, offer legal services, and integrate extremely deeply into their workflows. If their models turn out to be as good as they hype up, they should be able to scale to be a major player in any endeavor they move into with a relatively small number of staff and develop a strong feedback loop (not that that would be good for the rest of us).

I'm confused of why this is a question. First of all everyone is doing something because it benefits them. You and I included. Second of all as long as it's a real discovery, it will be beneficial to us all eventually (after benefiting Anthropic for sure).

Perhaps you're not on HN long enough, but there have been many posts where someone bemoaned the lack of basic science research by corporations, that IBM and Microsoft were the only a few remaining companies with any science research. Guess what? they do it for their own benefits as well.

What area of basic research are they bemoaning?

Because as I see it, there are a lot of already established labs that could take research like this a lot further with the help of AI instead of just throwing more agents at the problem.

That’s my confusion around this topic. Does the strategy change when you can throw a bonkers amount of compute at the problem with fewer guardrails?

I'm getting tired of the marketing.

There are so many people involved on this yet we still say things like "Claude did", we need to start waking up and being more real about how we are still in "AI + Human" land.

What's wrong with saying "A team of researchers backed by Anthropic using Claude discovers a novel enzyme system with CRISPR-like repeats" or, ffs, mention the lead researcher in the headline?

Because they’re trying to pump their stock price before their economic walls come tumbling down

What stock?

If it requires humans in the loop it throws cold water on the hopes of replacing millions of jobs, which is priced into their current valuation.

eh, farming still requires humans in the loop, only <1% of the number that it used to

OpenAI/Anthropic have never pitched themselves as a replacement for farmers. They do explicitly say that they're going to cause significant job loss in knowledge work sectors all the time.

Right - I'm saying that you can greatly improve productivity / reduce employment while still having humans in the loop. We've already seen it happen with farming, from 1900 -> present.

It looks like the researchers just wrote the agentic harness and the rest of the work really was done autonomously by Claude with only extremely limited guidance after.

BTW the first author of the paper worked in the Doudna lab studying the origins of crispr (and after their PhD, joined Anthropic). All of the authors either have, or are going to have, excellent careers. I dont' think they are worried about attribution.

just wrote the agentic harness

I think "just" and "harness" are carrying a lot there, you likely underestimate how much that matters and how their knowledge made it possible

I wish we could discuss this in a way that didn't immediately devolve into people shouting up or shouting down that this is either meaningless or singularity.

Caveating I'm not a biologist, but my understanding of the way this kind of thing works right now is a basic three-step process:

1) Find molecules and DNA/RNA sequences in the wild and catalog them.

2) Discover interesting subsequences among these.

3) Figure out whether any useful applications can come from what was discovered.

All three of these generally take a long time. Systematic automatic analysis of known databases speeds up and removes some of the luck from 2. But 1 and 3 are still long poles. 1 has the further issue that we usually discover these in existing organisms. I recall much of the outcry over tropical deforestation back in the 90s and replacing of rainforests with palm oil monoculture today is that the vast majority of terrestrial biodiversity is found in rainforests, and destroying them at industrial scale risks losing potentially useful molecules forever. 3 has the problem that you need to conduct physical experiments, and are limited by the speed of biochemical reactions no matter what and by the speed at which human subjects can be found and ethically experimented on assuming we care about being ethical.

A lot of good can come of this, but I don't see a path to singularity here, assuming we're talking the original Kurzweil meaning there of all technological progress that will ever happen all happening at once. Data collection and experimentation on living subjects, human or not, can only happen so fast, regardless of automation. It's not computational. Whenever you have to interface with the real world, you're now working at the speed of the real world, not the speed of electricity. CRISPR was discovered in 1987 and first used to edit a gene sequence in a human zygote in 2015. I'm sure there are plenty of ways to make the candidate discovery to human application step not take three decades, but it's never going to be three months, either.

From ravid shwartz ziv:

https://x.com/ziv_ravid/status/2102844800345251858

Thank you for sharing, that provided some good context for how to interpret this

Post content:

_____

I wish we didn’t need these again, but here is the honest version of Anthropic’s biology announcement (Caveat: I haven’t worked in bioinformatics for many years.) The good: Anthropic ran ~950 Claude agents over a large biological sequence database. Claude searched, wrote code, compared sequences and genomic neighborhoods, and found an interesting pattern that apparently had not been noticed before: a known reverse transcriptase associated with another gene and a repetitive DNA array.

That is cool. Automating this kind of open-ended bioinformatics search at scale is useful, and Claude may have found a lead a human would have missed.

But: Claude did not do a biological experiment. It searched databases and analyzed data.

Humans then took the candidate into the wet lab. And the wet-lab result so far is modest: they showed that the repeat array produces short RNAs.

We still don’t know what the system does. No function, mechanism, phenotype, targeting, defense activity, or programmability has been demonstrated.

This is also where the CRISPR framing gets ahead of the result. Right now, “it has some features reminiscent of known programmable systems” is a hypothesis for what to investigate next, not a discovery that it behaves like CRISPR.

And there is a missing baseline: bioinformatics has had tools for finding unusual gene neighborhoods and candidate systems for years. The interesting comparison is 950 Claude agents vs. an expert using the best existing computational pipelines - not Claude vs. someone manually looking through 200,000 sequences.

So my honest announcement would be:

Claude autonomously found an interesting candidate for a previously uncharacterized biological system. A small human wet-lab experiment confirmed that part of the candidate is expressed. We don’t yet know what it does.

That is a good result.

But in a regular biology lab, this isn’t the finished paper. It is the result you show at lab meeting and say: “This looks interesting. Now we need to figure out what the hell it does.”

Maybe that next step leads to a major discovery. But that discovery hasn’t happened yet.

A more spicy follow up take :) https://x.com/ziv_ravid/status/2102850969537225149

The sad thing is that Dario knows better.

He was a PhD student. He knows the significance level of this result. He knows that if he had walked into Bill’s office (his advisor) with “we found an interesting system, but we still don’t know what it does” and said he was ready to graduate, Bill would have kicked him out of the room.

But somehow, when the IPO is around the corner, this becomes “AI is starting to drive biological discovery.”

100% AI per Pangram. I caught it at "This is also where the CRISPR framing gets ahead of the result." -- somehow this is not a sentence anybody non-obnoxious would write. It's a weird structure where the AI talks about something specific as if it were an example of a common theme. This paragraph is an even clearer ekample:

"But in a regular biology lab, this isn’t the finished paper. It is the result you show at lab meeting and say: “This looks interesting. Now we need to figure out what the hell it does.”"

This is not how people write!

Fake news to pump up their share price. You can't trust any news about A.I. these days, especially near their IPOs.

This A.I. hype makes the Internet Bubble look like a walk in the park.

If by now you still think it's all just hype, it's safe to say you've succumbed to a mind virus that renders you unable to think critically about AI. Otherwise you'd have some level of awareness of just how far this technology has developed, and you should find these developments more than plausible.

This work seems directly dangerous to me?

The study results themselves aren't really dangerous in any way I can see. This is basic microbiology, and not necessarily some kind of major breakthrough that will change the world on its own. It's possible this leads to something big like CRISPR, but most likely not. The work is more the case of noticing something that someone hasn't noticed yet. It would have gotten noticed eventually, they just did it before someone else did (assuming they didn't get a hint somehow).

A lot of molecular biology is noticing something that you can't explain or that seems weird and might be interesting. Once it's noticed the followup is often fairly straightforward and it either pans out or it doesn't. The exciting/scary/unlikely part is that the LLM on its own recognized something as being important to follow up.

From my skim of the paper, the work could only be done by someone with a pretty good understanding of the biology and an extremely good understanding of how to use LLMs and agents. LLMs are not going to take over biology yet.

You don’t see a problem with LLMs in wet labs doing biology work?

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?

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?

Medical advances are more important than post docs

Absolutely. But without post docs, it won't be long before we are unable to understand what the LLMs are suggesting.

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?

I can't understand what the post-docs 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.

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.

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

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.

I give a shit about knowledge! I think it's good entirely for its own sake.

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.