One way to make sense of this specific case at least.
- He's on track to becoming a top-tier AI researcher. Despite having only one year of a PhD under his belt, he already received two top awards as a first-author at major AI conferences [1]. Typically, it takes many more years of experience to do research that receives this level of recognition. Most PhDs never get there.
- Molmo, the slate of open vision-language models that he built & released as an academic [2], has direct bearing on Zuck's vision for personalized, multimodal AI at Meta.
- He had to be poached from something, in this case, his own startup, where in the best case, his equity could be worth a large multiple of his Meta offer. $250M likely exceeded the expected value of success, in his view, at the startup. There was also probably a large premium required to convince him to leave his own thing (which he left his PhD to start) to become a hired hand for Meta.
It's strange that Zuck didn't just buy options on that guy? (Or did he? Would love to see the terms.)
Zuck's advantage over Sir Isaac (Newton) is that the market for top AI researchers is much more volatile than in South Sea tradeables pre-bubble burst?
Either that or 250M is cheap for cognitive behavior therapy
If it were me, yeah, park it in bonds and live off the interest on a tropical beach. Spend my days spearfishing and drinking beers with the locals. Have no concerns except how even my tan is (and tbh I don't see myself caring too much about that).
I met a traveller from an antique land,
Who said: “Two vast and trunkless legs of stone
Stand in the desert. Near them, on the sand,
Half sunk, a shattered visage lies, whose frown,
And wrinkled lip, and sneer of cold command,
Tell that its sculptor well those passions read
Which yet survive, stamped on these lifeless things,
The hand that mocked them and the heart that fed;
And on the pedestal these words appear:
"My name is Ozymandias, king of kings:
Look on my works, ye Mighty, and despair!"
Nothing beside remains. Round the decay
Of that colossal wreck, boundless and bare,
The lone and level sands stretch far away.
It's fine to think that we're in a bubble and to post a comment explaining your thoughts about it. But a comment like this is a low-effort, drive-by shoot-down of a comment that took at least a bit of thought and effort, and that's exactly what we don't want on HN.
Various BigCo-s have been reporting good results recently and highlighted significant AI role in that. That may be a BS of course, yet even if it is half-true we're talking about tens/hundreds of billions of revenues. With 10x multiple it supports a trillion like generic valuation of AI in business right now.
Zuckerberg had a lot to say about AI in his part of Meta's Q2 earnings statement, but the follow-up earnings call [0] revealed the rather limited scope of AI in their ad business so far:
>"The first is enabling business AIs within message threads ... We’re expanding business AIs to more businesses in Mexico and the Philippines. And we expect to broaden availability later this year as we keep refining the product."
>"The second area of business AI development is within ads ... We’re currently testing this with a small number of businesses across Feed and Reels on Facebook and Instagram as well as Instagram Stories."
>"And then the final area that we are exploring is business AIs on business websites to help better support businesses across all platforms ... and we’re starting to test that with a few businesses in the US."
So it's just very small scale tests so far - not the sort of thing that would have any measurable impact on their revenue.
I agree on all points. However, if he already had several millions like Mira and Ilya, his choice to work for Zuckerberg would likely be different. Where is the glory in bending the knee to Meta and Zuckerbeg?
This is such a weird sentiment to me, comparing taking one of the highest paying corporate jobs in the history of humanity to bowing down to some dictator.
This is IMO a comical, absurd, Beeple NFT type situation, which should point us to roughly where we are in the bubble.
But if he's getting real, non-returnable actual money from Meta on the basis of a back of envelope calculation for his own startup, from Meta's need to satiate Mark Zuckerberg's FOMO, then good for him.
This bubble cannot burst soon enough, but I hope he gets to keep some of this; he deserves it simply for the absurd comedy it has created.
Professional athletes get paid on that scale, CEOs get paid on that scale. A top researcher in a burgeoning technology should get paid that much. Because bubbles dont mean every company fails, it means most of them do and the winner takes all, and if someone thinks hiring this guy will make them the winner than it's not remotely unusual.
I'm not a conspiracy person, but it's hard not to believe that some cruel god sent us crypto just a few years before we accidentally achieved AGI just to mess with us. So many people are confident that AGI is impossible and LLMs are a passing fad based to a large degree on the idea that SV isn't trustworthy -- I'd probably be there too, if I wasn't in the field myself. It's a hard pattern not to recognize, even if n~=2.5 at most!
I hope for all of our sake's that you're right. I feel confident that you're not :(
Woah, a whopping 0.5%. That's like working 12 minutes more every week. I waste much more time every day because of how slow and sluggish Windows 11 is.
There is no guarantee that Meta or OpenAI would capture that increase in productivity as opposed to open models or otherwise driving the profits on the AI itself to zero.
If you agree it is a bubble, you are agreeing it is going to burst. Because that is what defines a bubble.
I have two questions about this, really:
- is he going to be the last guy getting this kind of value out of a couple of research papers and some intimidated CEO's FOMO?
- are we now entering a world where people are effectively hypothetical acquihires?
That is, instead of hiring someone because they have a successful early stage startup that is shaking the market, you hire someone because people are whispering/worried that they could soon have a successful early stage startup?
The latter of these is particularly worrisomely "bubbly" because of something that people don't really recognise about bubbles unless they worked in one. In a bubble, people suspend their disbelief about such claims and they start throwing money around. They hire people without credentials who can talk the talk. And they burn money on impossible ideas.
The bubble itself becomes increasingly intellectually dishonest, increasingly unserious, as it inflates. People who would be written off as fraudsters at any other time are taken seriously as if they are visionaries and ultra-productive people, because everyone's tolerance for risk increases as they become more and more desperate to ride the train. People start urgently taking impossible things at face value, weird ideas get much further advanced much more quickly, and grifters get closer to the target -- the human source of the cash -- faster than due dilligence would ordinarily allow them.
"This guy is so smart he could have a $1bn startup just like that" is an obvious target for con artists and grifters. And they will come.
For clarity I am ABSOLUTELY NOT saying that the subject of this article is such a person. I am perfectly happy to stipulate that he's the real deal.
But he is now the template for a future grift that is essentially guaranteed to happen. Maybe it'll be a team of four or five people who get themselves acquihired because there's a rumour they are going to have billions of dollars of funding for an idea. They will publish papers that in a few months will be ridiculed. And they will disappear with a lot of money.
> The bubble itself becomes increasingly intellectually dishonest, increasingly unserious, as it inflates.
You started to sound like Dario, who likes to accuse others as intellectually dishonest and unserious. Anyway, perhaps the strict wage structure of Anthropic will be its downfall in this crazy bubble?
I am accusing no one individually or particularly. I am observing that the problem is that within a bubble, people collectively become increasingly unserious and less intellectually honest as their appetite for risk increases with their desire to get a slice of the action. Indeed, it gets worse as people begin to think it might not last forever.
The same thing happened in the dotcom era, the same thing happened in the run-up to the subprime mortgage crisis. Every single bubble displays these characteristics.
It's also possible, based on what happens to those who win the lottery, that his life could become a lot harder. It's not great to have the fact that you're making $2M a week plastered all over the Internet.
This is the result of the winner-take-all (most) economy. If the very best LLM is 1.5x as good as good as the next-best, then pretty much everyone in the world will want to use the best one. That means billions of dollars of profit hang in the balance, so companies want to make sure they get the very best people (even if they have to pay hundreds of millions to get it).
It's the same reason that sports stars, musicians, and other entertainers that operate on a global scale make so much more money now than they did 100 years ago. They are serving a market that is thousands of times larger than their predecessors did, and the pay is commensurately larger.
I don't think AI will be a winner-take-all scenario. If that is to happen, I think the following assumptions must hold:
1) The winner immediately becomes a monopoly
2) All investments are directed from competitors, to the winner
3) Research on AGI/ASI ceases
I don't see how any of these would be viable. Right now there's an incremental model arms race, with no companies holding a secret sauce so powerful that they're miles above the rest.
I think it will continue like it does today. Some company will break through with some sort of AGI model, and the competitors will follow. Then open source models will be released. Same with ASI.
The things that will be important and guarded are: data and compute.
Yeah, this is why I said "(most)". But regardless, I think it's pretty uncontroversial that not all companies currently pursuing AI will ultimately succeed. Some will give up because they aren't in the top few contenders, who will be the only ones that survive in the long run.
So maybe the issue is more about staying in the top N, and being willing to pay tons to make sure that happens.
>I think it's pretty uncontroversial that not all companies currently pursuing AI will ultimately succeed.
That's probably true, but at the moment the only thing that creates something resembling a moat is the fact that progress is rapid (i.e. the top players are ~6-12 months ahead of the already commoditized options, but the gap in capabilities is quite large): if progress plateaus at all, the barrier to be competitive with the top dogs is going to drop a lot, and anyone trying to extra value out of their position is going to attract a ton of competition even from new players.
I agree with you, and think we are in the heady days where moat building hasn't quite begun. Regarding 1) and 3), most models have API access to facilitate quick switching and agentic AI middleware reaps the benefits of new models being better at some specific use-case than a competitor. In the not-so-distant future, I can see the walls coming up, with some version of white-listed user-agent access only. At the moment, model improvement hype and priority access are the product, but at some point capability and general access will be the product.
We are already seeing diminishing returns from compute and training costs going up, but as more and more AI is used in the wild and pollutes training data, having validated data becomes the moat.
Most likely won't be a winner-take-all, but something like it is right now, a never ending treadmill where the same 3 or 4 players release a SOTA model every year or so.
If the next best model is 0.5x as expensive, then many might opt for that in use cases where the results are already good enough.
At work we are optimising cost by switching in different models for different agents based on use case, and where testing has demonstrated a particular model's output is sufficient.
The actual OpenRouter data says otherwise.[1] Right now, Google leads with only 28.4% marketshare. Anthropic (24.7%), Deepseek (15.4%), and Qwen (10.8%) are the runners-up.
If this were winner-take-all market with low switching costs, we'd be seeing instant majority market domination whenever a new SOTA model comes out every few weeks. But this isn't happening in practice, even though it's much easier to switch models on OpenRouter than many other inference providers.
I get the perception of "winner-take-all" is why the salaries are shooting up, but it's at-odds with the reality.
I don't think there's a consensus on this. I have found Gemini to be so-so, and the UX is super annoying when you run out of your pro usage. IME, there's no way to have continuity to a lower-tier model, which makes is a huge hassle. I basically never use it anymore.
If the Google model was 50% better than OpenAI I would have bought a subscription, which would moot the UX issue. But IME it isn't discernibly better at all, let alone 50% better.
The hack I found to “get around” the secret limits that pop out of nowhere is to you export the chat, then import it with another account. So you don’t need to pay 200, just 40 (and only when you actually need that much).
It's multivariate; better for what? None of them are best across the board.
I think what we're seeing here is superstar economics, where the market believes the top players are disproportionately more valuable than average. Typically this is bad, because it leads to low median compensation but in this rare case it is working out.
I don’t see a winner takes all moat forming. If anything, the model providers are almost hot-swappable. And it seems the lifespan for being the best SOTA model is now measured in weeks.
It's true they are currently quite interchangeable these days. But the point is that if one can pull far enough ahead, it will get a much bigger share of the market.
> If the very best LLM is 1.5x as good as good as the next-best, then pretty much everyone in the world will want to use the best one.
Well only if the price is the same. Otherwise people will value price over quality, or quality over price. Like they do for literally every other product they select...
That is exactly how all of this has played out so far (beep, not at fucking all!)
You are not one random hyperparameter away from the SciFi singularity. You are making iterative improvements and throwing more compute at the problem, as are all your competitors, all of which are to some degree utterly exchangeable.
These figures are for a very small number of potential people. This leaves out that frontier AI is being developed by an incredibly small number of extremely smart people who have migrated between big tech, frontier AI, and others.
Yes, the figures are nuts. But compare them to F1 or soccer salaries for top athletes. A single big name can drive billions in that context at least, and much more in the context of AI. $50M-$100M/year, particularly when some or most is stock, is rational.
It’s just a matter of taste, but I am pleased to see publicity on people with compensation packages that greatly exceed actors and athletes. It’s about time the nerds got some recognition. My hope is that researchers get the level of celebrity that they deserve and inspire young people to put their minds to building great things.
I think I'm mostly with you but it also depends how it exactly plays out.
Like I definitely think it is better for society if the economic forces are incentivizing pursuit of knowledge more than pursuit of pure entertainment[0]. But I think we also need to be a bit careful here. You need some celebrities to be the embodiment of an idea but the distribution can be too sharp and undermine, what I think we both agree on is, the goal.
Yeah, I think, on average, a $100M researcher is generating more net good for a society (and world) than a $100M sports player or actor. Maybe not in every instance, but I feel pretty confident about this on average. But at the same time, do we get more with one $100M researcher or 100 $1M researchers? It's important to recognize that we're talking about such large sums of money that at any of these levels people would be living in extreme luxury. Even in SV the per capita income is <$150k/yr, while the median income is medium income is like half that. You'd be easily in the top 1%. (The top 10% for San Jose is $275k/yr)
I think we also need to be a bit careful in recognizing how motivation can misalign incentives and goals. Is the money encouraging more to do research and push humanity's knowledge forward? Or is the money now just another means for people that just want money to exploit, who have no interest in advancing humanity's knowledge? Obviously it is a lot more complicated and both are happening but I think it is worth recognizing that if things shift towards the latter than they actually make it harder to achieve the original goals.
So on paper, I'm 100% with you. But I'm not exactly sure the paper is matching reality.
[0] To be clear, I don't think entertainment has no value. It has a lot and it plays a critical role in society.
I think it's pretty funny because, for example, Katalin Karikó was thought to be working in some backwater, on this "mRNA" thing, that could barely get published before COVID...and, the original LLM/transformer people were well qualified but not pulling quarter billion dollars kicking around trying to improve machine translation of languages, a time-honored AI endeavor going back to the 1950s. The came upon something with outstanding empirical properties.
For whatever reason, remuneration seems more concentrated than fundamentals. I don't begrudge those involved their good luck, though: I've had more than my fair share of good luck in my life, it wouldn't be me with the standing to complain.
I don’t think this distinction actually exists. At that salary this person is moving from being a founder of his own company to being a founder of his own business unit inside Facebook.
It’s closer to actors and athletes than we’d all hope, in that most people get a pittance or are out of work while a select few make figures that hit newspapers.
The money these millions are coming from is already based on nerds having gotten incredibly rich (i.e. big tech). The recognition is arguably yet to follow.
Not really the same, is it? Actors are hired to act. Athletes get paid to improve the sport. It's not like nerds are poached to do academic research or nerd out at their hearts desire. This is a business transaction that Zuck intends to make money from.
Locking up more of the world's information behind their login wall, or increase their ad sales slightly is not enough to make that kind of money. We can only speculate, of course, but at the same time I think the general idea is pretty clear: AI will soon have a lot of power, and control over that power is thought to be valuable.
The bit about "building great things" certainly rings true. Just not in the same way artists or scientists do.
What I don't understand in this AI race is that the #2 or #3 is not years behind #1, I understand it is months behind at worst. Does that headstart really matter to justify those crazy comps? Will takes years for large corporations to integrate those things. Also takes years for the general public to change their habits. And if the .com era taught us anything, it is that none of the ultimate winners were the first to market.
There is a group of wealthy individuals who have bought in to the idea that the singularity (AIs improving themselves faster than humans can) is months away. Whoever gets there first will get compound growth first, and no one will be able to catch up.
If you do not believe this narrative, then your .com era comment is a pretty good analysis.
> There is a group of wealthy individuals who have bought in to the idea that the singularity is months away.
My question is "how many months need to pass until they realize it isn't months away?"
What, it used to be 2025? Then 2027? Now 2030? I know these are not all the same people but there are trends of to keep pushing it back. I guess Elon has been saying full self-driving is a year away since 2016 so maybe this belief can sustain itself for quite some time.
So my second question is: does the expectation of achievements being so close lengthen the time to make such achievements?
I don't think it is insane to think it could. If you think it is really close you'd underestimate the size of certain problems. Claim people are making mountains out of molehills. So you put efforts elsewhere, only to find that those things weren't molehills after all.
Predictions are hard and I think a lot of people confuse critiques with lack of motivation. Some people do find flaws and use them as excuses to claim everything is fruitless. But I think most people that find flaws are doing so in an effort to actually push things forward. I mean isn't that the job of any engineer or scientist? You can't solve problems if you can't identify problems. Triaging and prioritizing problems is a whole other mess, but it is harder to do when you're working at the edge of known knowledge. Little details are often not so little.
> My question is "how many months need to pass until they realize it isn't months away?"
It's going to persist until shareholders punish them for it. My guess is it's going to be some near-random-trigger, such as a little-known AI company declaring bankruptcy, but becoming widely reported. Suddenly, investing in AI with no roadmap to profitability will become unfashionable, budget cuts, down-rounds, bankruptcies and consolidation will follow. But there's no telling when this will be, as there's elite convergence to keep the hype going for now.
Indeed, this will continue as long as the market allows it to. There is a well known quote about how long markets can stay irrational, but I would like to remind where we are right now:
Telco capex was $100 billion at the peak of the IT bubble, give or take. There's going to be $400 billion investments in AI in 2025.
What I don't understand is with such small of a gap why this isn't a huge boon for research.
While there's a lot of money going towards research, there's less than there was years ago. There's been a shift towards engineering research and ML Engineer hiring. Fewer positions for lower level research than there were just a few years ago. I'm not saying don't do the higher level research, just that it seems weird to not do the lower level when the gap is so small.
I really suspect that the winner is going to be the one that isn't putting speed above all else. Like you said, first to market isn't everything. But if first to market is all the matters then you're also more likely to just be responding to noise in the system. The noisy signal of figuring out what that market is in the first place. It's really easy to get off track with that and lose sight of the actual directions you need to pursue.
LLaMA 4 is barely better than LLaMA 3.3 so a year of development didn't bring any worthy gains for Meta, and execs are likely panicking in order not to slip further given what even a resource-constrained DeepSeek did to them.
> given what even a resource-constrained DeepSeek did to them.
I think a lot of people have a grave misunderstanding of DeepSeek. The conversation is usually framed comparing to OpenAI. But this would be like comparing how much it cost to make the first iPhone (the literal first working one, not how much each Gen 1 iPhone cost to make) with the cost to make any smartphone a few years later. It's a lot easier and cheaper to make something when you have an example in hand. Just like it is a lot easier to learn Calculus than it is to invent calculus.
Which that framing weirdly undermines DeepSeek's own accomplishments. They did do some impressive stuff. But that's much more technical and less exciting of a story (at least to the average person. It definitely is exciting to other AI researchers).
Yeah this makes zero sense. Also unlike a pop star or even a footballer who are at least reasonably reliable, AI research is like 95% luck. It's very unlikely that any AI researcher that has had a big breakthrough will have a second one.
Hm, I thought that these salaries were offered to actual "giants" like Jeff Dean or someone extremely knowledgeable in the specifics of how the "business side" of AI might look like (CEOs, etc). Can someone clarify what is so special about this specific person? He is not a "top tier athlete" - I looked at his academic profile and it does not seem impressive to me by any measure. He'd make an alright (not even particularly great) assistant professor in a second tier university - which is impressive, but is by no means unique enough to explain this compensation.
I think the key was multimodality. Meta made a big move in combining texts, audio, images. I remember imagebind was pretty cool. Allen AI has published some notable models, and Matt seems to have expertise in multimodal models. Molmo looks really cool.
A PhD dropout with an alright (passable) academic record, who worked in a 1.5-tier lab on a fairly pedestrian project (multimodal llms and agents, sure), and started a startup.. Reallyttrying to not sound bitter, good for him, I guess, but does it indicate that there's something really fucked up with how talent is being acquired?
You bring up the only relevant data point at the end, as a throw in. Nobody outside of academia cares about your PhD and work history if you have a startup that is impressive to them. That's the only reason he's being paid.
Frontier AI that scales – these people all have extensive experience with developing systems that operate with hundreds of millions of users.
Don’t get me wrong, they are smart people - but so are thousands of other researchers you find in academia etc. - difference here is scale of the operation.
Yeah, I guess if you have a datacenter that costs $100B, even hiring a humble CUDA assembly wizard that can optimize your code to run 10% faster is worth $10B to the company.
Yeah but then you factor in the costs of building and running the machines vs the revenue and realize they are actually burning money for the blind hope of major breakthroughs in cognitive understanding that could be centuries away.
Top athletes they have stats to measure. I guess for these researchers I guess there are papers? How do you know who did what with multiple authors? How do you figure out who is Jordan vs Steve Kerr?
I can print jersey with Neymars name on it and drive revenue. i can't do that with some ai researcher. they have to actually deliver and i don't see how a person with $100M net-worth will do anything other than coast.
A very major difference is that top athletes bring in real tangible money via ticket / merch sales and sponsorships, whereas top AI researchers bring in pseudo-money via investor speculation. The AI money is far more likely to vanish.
It's best to look at this as expected value. A top AI research has the potential to bring in a lot more $$ than a top athlete, but of course there is a big risk factor on top of that.
The expected value is itself a random variable, there is always a chance you mischaracterized the underlying distribution. For sports stars the variance in the expected value is extremely small, even if the variance in the sample value is quite large - it might be hard to predict how an individual sports star will do, but there is enough data to get a sense of the overall distribution and identify potential outliers.
For AI researchers pursuing AGI, this variance between distributions is arguably even worse than the distribution between samples - there's no past data whatsoever to build estimates, it's all vibes.
The distribution is merely tricky to pin down when looking at overall AI spend, i.e. these "$T+ scale impacts."
But the distribution for individual researcher salaries really is pure guesswork. How does the datapoint of "Attention Is All You Need?" fit in to this distribution? The authors had very comfortable Google salaries but certainly not 9-figure contracts. And OpenAI and Anthropic (along with NVIDIA's elevated valuation) are founded on their work.
When Attention is All You Need was published, the market as it stands didn't exist. It's like comparing the pre-Jordan NBA to post. Same game, different league.
I'd argue the top individual researchers figure into the overall AI spend. They are the people leading teams/labs and are a marketable asset in a number of ways. Extrapolate this further outward - why does Jony Ive deserve to be part of a $6B aquihire? Why does Mira Murati deserve to be leading a 5 month old company valued at $12B with only 50 employees? Neither contributed fundamental research leading to where we are today.
Seriously. The transformer coupled with tons of compute is why we got here. When that paper came out and people (AI researchers) saw the results many were confused or unconvinced. No one has any clue such an architecture would yield the results it has. AI systems has always been far more art than science and we still don’t even really know why it works. I feel like that idea being stumbled upon was sort of more luck than anything…
Sure, but the idea these hires could pay out big is within the realm of actual reality, even if AGI itself remains a pipe dream. It’s not like AI hasn’t already had a massive impact on global commerce and markets.
My understanding is that the bulk of revenue comes from television contracts. There has been speculation that that could easily shrink in the future if the charges become more granular and non-sports watching people stop subsidizing the sports watching people. That seems analogous to AI money.
Wonder what their contracts look like. Are these people gonna be grinding their ass off at the Meta offices working crazy hours? Does Zucc have a strong vision, leadership, and management skills to actually push and enable these people to achieve maximum success? And if so, what does that form of success look like? So far the vision that Zucc has outlined has been rather underwhelming, but maybe the vision which he shares with insiders is different from his public persona.
I can't help but think that the structure of this kinda hints at there being a bit of a scam-y element, where a bunch of smart people are trying to pump some rich people out of as much money as possible, with questionable chances at making it back. Imagine that the people on The List had all the keys needed to build AGI already if they put their knowledge together, what action do you think they would take?
What I most would like to understand is how you intend to motivate someone you just gave a quarter of a billion dollars to? Especially a young person. They never have to work again, and neither do their grandchildren.
You can just doodle away with whatever research interests you the most, there's no need to deliver a god mode AI to the great leader even if you had the ability to.
I'm sure a very small number of these AI researchers will be worth the pay (and then some), but I imagine the marjority of them will only manage to make marginal gains in the projects they work on. I guess it's a little like venture capital, where the majority of the startups that you fund end up flopping, but a small number of them provide returns that make up for all of the losses.
I don't think I've ever understood the motivation behind working for so much money. If I got paid $250M a year, I'd work a year and then live comfortably for the rest of my life pursuing my passions. Even if the thing I was doing for work was my passion, I'm sure I'd prefer to do it without ownership of that work going to someone else.
These aren't annual pay packages. It's some "can't retire on that" base salary plus a promise of gradually vesting equity on a multi-year schedule. For public companies, you'll get that amount if you hang around for x years and there is no sudden decline in market price. For non-public companies (OpenAI), the equity is more pie-in-the-sky.
Eh, depending on the stress of the work, how much I enjoyed it, etc, $250M can buy a lot of convenience in life that lets you do it for as long as you want and that can be truly transformational generational wealth.
Am I reading this correctly: an AI researcher might get paid roughly the same amount of money as the largest transfer of a soccer player in history (Neymar at €220M)?
Based on the productivity gains in the last 50 years, there are certainly engineers worth $100,000,000 that had no idea the impact they were going to have on the world.
We are in a time where the impact can be measured more quickly, so good for the engineers taking advantage of this.
Good for those involved being offered such packages, but it really does raise the question of what exactly those offering them are so afraid of.
For example, Meta seem to be spending so much so they don't later have to fight a war against an external Facebook-as-chatbot style competitor, but it's hard to see how such a thing could emerge from the current social media landscape.
It has nothing to do with Meta's social media business. Zuckerberg, like many other top tech executives, has concluded AGI/ASI is in striking distance. If he could somehow win the race, he becomes god (or so he thinks, anyway). And from the perspective of a man whose idol is Julius Caesar, what wouldn't you spend for that chance?
This seems like it lands in the "most uncharitable" side of the "guess why someone is doing something I don't understand" spectrum. My razors tell me this is usually not the most plausible answer.
They just want the best, and they’re afraid of having second rates, B-players, etc., causing a bozo explosion. That seems like all the motivation that’s needed.
Why why would they need fears about a quasi-facebook chatbot?
Coming from Meta, I have to wonder if the reason for this isn't more down to Zuck's ego and history. He seems to have somewhat lost interest in FaceBook, and was previously all-in on the Metaverse as the next big thing, which has failed to take off as a concept, and now wants to go all-in on "super-intelligence" (seems to lack ambition - why not "super-duper extra special intelligence"?) with his new vision being smart glasses as the universal AI interface. He can't seem to get past the notion that people want to wear tech on their head and live in augmented reality.
Anyhow, with the Metaverse as a flop, and apparently having self-assessed Meta's current LLM efforts as unsatisfactory, it seems Zuck may want to rescue his reputation by throwing money at it to try to make his next big gamble a winner. It seems a bit irrational given that other companies, and countries, have built SOTA LLMs without needing to throw NBA/NFL/rockstar money around.
Zuckerberg is one of the reasons I think AI is a bubble and overhyped. He lacks vision. Remember when they renamed the company Meta and the metaverse was the whole future of the company?
This is the same thing. It is the new shiny tech demo that is really cool. And technically works really, really well and has some real uses, but that doesn’t make a multi billion dollar business.
I don't think he gave up on the metaverse. Isn't AR glasses a stepping stone towards that? Or rather LLM voice assistant a stepping stone towards AR glasses? And the metaverse being a stepping stone towards a holodeck?
I mean I'm with you, I think these things are pretty far away and are going to cost a lot of money to make and require a lot of failure in the mean time. But then again, it looks like they spent ~$18bn on Reality Labs last year. So if he was funding it all on his own dime, his current $260bn of wealth would give him a good 14 years runway if we ignore interest. It would be effectively indefinite if he earns about a 5% interest on that money.
I guess I'm just trying to say, it's hard to think about these things when we're talking about such scales of wealth. I mean at those scales, I'm pretty sure the money is meaningless, that money (and the ability to throw it around) is more a proxy for ego.
This rings true. Zuck wants to go down in the history books like Jobs—as a visionary who introduced technology that changed the world.
He's not there yet, and he knows it. Jobs gave us GUIs and smartphones. Facebook is not even in the same universe, and Instagram is just something he bought. He went all in on the metaverse, but the technology still needs at least 10-15 years to fully bake. In the meantime, there's AGI/super-intelligence. He needs to beat Sam Altman.
The sad thing is, even if he does beat Sam to AGI, Sam will still probably get the credit as the visionary.
Lmao right!? Dude stole all that from Xerox and MS came out with palm pilots early 2000s then you had black berry. Amazing how many people think CEOs actually did the work they get credit for when they almost virtually all were in the right spot with the right people. Notice none of them can reproduce or start another ultra successful startup… Zuckerberg is a perfect example of one hit wonder and he wasn’t even the first to create social sites.. You had MySpace and a ton of others..
That just shows you how warped the minds of the general public are. They fail to realize the only thing Jobs did was know the right people then take all the credit…
Just like in football, buying all the best players pretty much guarantees failure as egos and personal styles clash and take precedence over team achievement. The only reasons one would do that are fear, vanity, and stupidity, and those have to be more important than getting value for the extraordinary amounts of money invested.
The only case where this may have made sense - but more for an individual rather than a team - is Google's aqui-rehire of Noam Shazeer for $1B. He was the original creator of the transformer architecture, had made a number of architectural improvements while at Character.ai, and thus had a track record of being able to wring performance out of it, which at Google-scale may be worth that kind of money.
Noam was already one of Google's top AI researchers and a personal friend of Jeff Dean (head of Google AI, at least in title). He worked on some of the early (~2002) search systems at Google and patented some of their most powerful technoloigies at the time- which were critical in making Google Search a product that was popular, and highly profitable.
First rate A-players are beyond petty ego clashes, practically by definition… otherwise they wouldn’t be considered so highly (and thus fall into the bozo category).
Here is the uncomfortable truth. Only a small group of people are capable of operating at an elite level. The talent pool is extremely small and the companies want the absolute best.
It is the same thing in sports as well. There will only ever be one Michael Jordan one Lionel Messi one Tiger Woods one Magnus Carlsen. And they are paid a lot because they are worth it.
>> Meta seem to be spending so much so they don't later have to fight a war against an external Facebook-as-chatbot style competitor
Meta moved on from facebook a while back.It has been years since I last logged into facebook and hardly anybody I know actually post anything there. Its a relic of the past.
> Here is the uncomfortable truth. Only a small group of people are capable of operating at an elite level. […] It is the same thing in sports as well.
It’s not just uncomfortable but might not be true at all. Sports is practically the opposite type of skills: easy to measure, known rules, enormous amount of repetition. Research is unknown. A researcher that guarantees result is not doing research. (Coincidentally, the increasing rewards in academia for incrementalist result driven work is a big factor in the declining overall quality, imo.)
I think what’s happening is kind of what happened in Wall Street. Those with a few documented successes got disproportionately more business based to a large part on initial conditions and timing.
Not to take away from AI researchers specifically, I’m sure they’re a smart bunch. But I see no reason to think they stand out against other academic fields.
Occam’s razor says it’s panic in the C-suites and they perceive it as an existential race. It’s not important whether it actually is, but rather that’s how they feel. And they have such enormous amount of cash that they’re willing to play many risky bets at the same time. One of them being to hire/poach the hottest names.
Hot fucking take - but if these 100 (or whatever small number is being thrown around these days) elite researchers disappeared overnight, the world would go on and little of it would be noticed. New people in the field would catch up, and things would be up to speed quick enough.
It is not a question of exquisitely rare intellect, but rather the opportunity and funding/resources to prosper.
Hmmmm, I think only assuming those 100 have not been accurately identified. In pretty much all fields I am familiar with, the ability distribution seems to approximate a power law near the top: the gap between the best and the 20th best can be absolutely gigantic.
(And while there are certainly those who could have been the best who did not have the opportunity to succeed, or just didn't actually want to pursue it, I think usually this is way at the edges, i.e. removing the top would not make room for these people, because they're probably not even on anyone's radar at all, like the 'Einstein toiling in a field')
While I don’t doubt that these people have great experience and skills what they really have that others don’t is connections and the ability to market themselves well.
All you need is to publish a couple of right papers and/or significantly contribute to a couple of right projects. If you have brains for that you’ll be noticed.
why the negativity? no one bats an eye when ronaldo/messi or steph curry or other top athletes get insane salaries.
These AI researchers will probably have far more impact on society (good or bad I dont know) than the athletes, and the people who pay them (ie zuck et al) certainly thinks its worth paying them this much because they provide value.
Sports teams pay Ronaldo, Messi, and Curry because they win games and that puts fans in seats and attracts sponsors that pay those teams money and turn a profit.
When someone had a successful business model that offsets the incredible costs let me know, but it is all hypothetical.
I'm going with envy. Athletics is a completely different skill from software, and one that is looked down on by posters here, judging by the frequent use of "sportsball". "Sportsball" players make huge salaries? Whatever, not my thing, that's for normies. But when software researchers make 1000x my salary? Now it's more personal. Surely they are not 1000x as good as me. It seems unlikely that this guy is 1000x as skilled as the average senior developer, so there's some perceived unfairness, too.
But I counsel a different perspective: it's quite remunerative to be selling tulips when there's a mania on!
It may be envy, but I’m still not sure a direct comparison makes much sense, given how much of a different creature engineering LLMs is from what most devs are doing.
I think negative feelings are coming from more of a “why are they getting paid so much to build a machine that’s going to wreck everything” sort of angle, which I find understandable.
My personal negativity stems from Meta in particular having a negative net impact on society. And no small one either. Everything Zuckerberg touches turns to poison (basically King Midas in reverse). And all that money, all that progress, is directed towards the detriment of everyone but a few.
In contrast, a skilled football player lands somewhere between neutral and positive, as at the very least they entertain millions of people. And I'm saying that as someone who finds football painfully dull.
You must not follow sports very close. Every time a young supports signs his first big deal, people freak out and compare it to the last superstar's deal. "Young players getting too much money before they earned it" is a trope at this point.
Salary caps are more about keeping smaller clubs competitive. Is it really the case here? I think if this guy's company was acquired for $1B and he made $250M from the sale, people wouldn't be surprised at all.
Ronaldo competes in a sport that has 250 million players (mostly for leisure purposes) worldwide, who often practice daily since childhood, and still comes out on top.
Are there 250 million AI specialists and the ones hired by Meta still come out on top?
Huh the pool being so small is exactly why they’re fought over. Theres tiering in research through papers and products built. Even if the tiering is wrong, if you can monopolize the talent you strike a blow to competitors.
Crab mentality, the closer proximity to your profession / place in society the more resentment/envy. This is a win for some of us in tech, it's just not us, so we cannot allow it! Article even mentions the age of "24" as if someone of that age is inherently undeserving.
It's good to at least see them call out wealth concentration as a driving factor here. The reason companies are paying insane amounts of money is that companies have insane amounts of money.
If you think of it, what is Meta going to do with AI? Their business model is ads. Maybe AI can improve ads some. For Meta, how does the billions spent on AI impact their bottom line? The reality is that if AI training requirements keep scaling based on Chinchilla scaling, there is going to be massive consolidation in training due to the scale that’s going to be required. Not everyone is going to be comfortable with Zuck running nuclear reactors. Already AI models are the fastest depreciating assets ever created. Moreover Meta is behind the AI curve so they are desperate to catch up. But desperate for what?
My mental model is looking at all of these situations as pre-emptive aquihires.
Meta can make 40 of these hires (over a number of years) and still be in a better place than feeling like they have to make a single $10B acquisition (if they could even make it at that point)
Even if what you say is true, people don't add in this way. They still need to be managed, motivated, and somehow made to work together toward something of value.
Microsoft Research had hundreds of big brains for decades that all worked independently and added little of value to the business.
this is the nature of capitalism, capital begets more capital and the returns are exponential, however our societies, economies, and tax systems remain linear. We never really adjusted because it's complicated.
To me it's obvious that these extremes create perverse incentives, so the people who will take those jobs won't amount to much. I m willing to bet that Meta's AI efforts are doomed from now on.
Money itself amounts to a lot. At $250M you're already able to influence elections. So we might expect American politics for the rest of the 2020s to be broadly accelerationist and pro Big Token, even more so than it is currently. SV being the keystone of growth in America means SV ideals will have massive power in Washington.
Funding is so plentiful right now that they are really competing with acquihire rates. That amount might sound crazy as straight salary, it comes with multi-year golden handcuffs and avoids having to buy them out for billions if they go start their own endeavor.
For this one, it appears to be something along the lines of $250M in RSUs vesting over 4 years with $100M of it in the first year (almost a seed round per week!)
I am sure people here will disagree with me, but I do not think that the 250M$ packages makes sense. In my opinion nobody is is worth 1000s times more the other people in the same field. A way to deal with this is through the tax system that would make it economically inefficient to have insane pay packages. Obviously that will not happen (especially in the US).
So what happens when they achieve AGI? Will a benevolent network of vastly smarter-than-human intelligences insist on maintaining the wealth hierarchies that humans had before AGI arrived? Isn't the point of AGI removing scarcity?
I worry that those who became billionaires in the AI boom won't want the relative status of their wealth to become moot once AGI hits. Most likely this will come in the form of artificial barriers to using AI that, for ostensible safety reasons, makes it prohibitively difficult for all but the wealthiest or AGI-lab adjacent social circles to use.
This will cause a natural exacerbation of the existing wealth disparities, as if you have access to a smarter AI than everyone else, you can leverage your compute to be tactically superior in any domain with a reward.
All we can hope for is a general benevolence and popular consensus that avoids a runaway race to the bottom effect as a result of all this.
I can't believe this is so unpopular here. Maybe it's the tone, but come on, how do people rationally extrapolate from LLMs or even large multimodal generative models to "general intelligence"? Sure, they might do a better job than the average person on a range of tasks, but they're always prone to funny failures pretty much by design (train vs test distribution mismatch). They might combine data in interesting ways you hadn't thought of; that doesn't mean you can actually rely on them in the way you do on a truly intelligent human.
I wouldn't call 7-10 years a scam, but I would call it low odds. It is pretty hard to be accurate on predictions of a 10 year window. But I definitely think 2027 and 2030 predictions are a scam. Majority of researchers think it is further away than 10 years, if you are looking at surveys from the AI conferences rather than predictions in the news.
>One way to reduce selection effects is to look at a wider group of AI researchers than those working on AGI directly, including in academia. This is what Katja Grace did with a survey of thousands of recent AI publication authors.
>In 2022, they thought AI wouldn’t be able to write simple Python code until around 2027.
>In 2023, they reduced that to 2025, but AI could maybe already meet that condition in 2023 (and definitely by 2024).
>Most of their other estimates declined significantly between 2023 and 2022.
>The median estimate for achieving ‘high-level machine intelligence’ shortened by 13 years.
Basically every median timeline estimate has shrunk like clockwork every year. Back in 2021 people thought it wouldn't be until 2040 or so when AI models could look at a photo and give a human-level textual description of its contents. I think is reasonable to expect that the pace of "prediction error" won't change significantly since it's been on a straight downward trend over the past 4 years, and if it continues as such, AGI around 2028-2030 is a median estimate.
> "Back in 2021 people thought it wouldn't be until 2040 or so when AI models could look at a photo and give a human-level textual description of its contents."
Claim doesn't check out; here's a YouTube video from Apple uploaded in 2021, explaining how to enable and use the iPhone feature to speak a high level human description of what the camera is pointed at: https://www.youtube.com/watch?v=UnoeaUpHKxY
Exactly. There’s one guy - Ray Kurzweil - who predicted in late 90s that AGI will happen in 2029 (yes, the exact year, based on his extrapolations of Moore’s law). Everybody laughed at him, but it’s increasingly likely he’ll be right on the money with that prediction.
> The thing is, AI researchers have continually underestimated the pace of AI progress
What's your argument?
That because experts aren't good at making predictions that non-experts must be BETTER at making predictions?
Let me ask you this: who do you think is going to make a less accurate prediction?
Assuming no one is accurate here, everybody is wrong. So the question is who is more or less accurate. Because there is a thing as "more accurate" right?
>> In 2022, they thought AI wouldn’t be able to write simple Python code until around 2027.
Go look at the referenced paper[0]. It is on page 3, last item in Figure 1, labeled "Simple Python code given spec and examples". That line is just after 2023 and goes to just after 2028. There's a dot representing the median opinion that's left of the vertical line half way between 2023 and 2028. Last I checked, 8-3 = 5, and 2025 < 2027.
And just look at the line that follows
> In 2023, they reduced that to 2025, but AI could maybe already meet that condition in 2023
Something doesn't add up here... My guess, as someone who literally took that survey, is what's being referred to as "a simple program" has a different threshold.
Here's the actual question from the survey
Write concise, efficient, human-readable Python code to implement simple algorithms like quicksort. That is, the system should write code that sorts a list, rather than just being able to sort lists.
Suppose the system is given only:
A specification of what counts as a sorted list
Several examples of lists undergoing sorting by quicksort
Is the answer to this question clear? Place your bets now!
Here, I asked ChatGPT the question[1], it got it wrong. Yeah, I know it isn't very wrong, but it is still wrong. Here's an example of a correct solution[2] which shows the (at least) two missing lines. Can we get there with another iteration? Sure! But that's not what the question was asking.
I'm sure some people will say that GPT gave the right solution. So what that it ignored the case of a singular array and assumed all inputs are arrays. I didn't give it an example of a singular array or non-array inputs, but it did just assume. I mean leetcode questions pull out way more edge cases than I'm griping on here.
So maybe you're just cherry-picking. Maybe the author is just cherry-picking. Because their assertion that "AI could maybe already meet that condition in 2023" is not unobjectively true. It's not clear that this is true in 2025!
>Go look at the referenced paper[0]. It is on page 3, last item in Figure 1, labeled "Simple Python code given spec and examples". That line is just after 2023 and goes to just after 2028. There's a dot representing the median opinion that's left of the vertical line half way between 2023 and 2028. Last I checked, 8-3 = 5, and 2025 < 2027.
The graph you're looking at is of the 2023 survey, not the 2022 one
As for your question, I don't see what it proves. You described the desired conditions for an a sorting algorithm and chatGPT implemented a sorting algorithm. In the case of an array with one element, it bypasses the for loop automatically and just returns the array. It is reasonable for it to assume all inputs are arrays because your question told it that its requirements were to create a program that " turn any list of numbers into a foobar."
Of course I'm not any one of the researchers asked about their predictions in the survey, but I'm sure if you told them "a SOTA AI in 2025 produced working human readable code based on a list of specifications, and is only incorrect by a broad characterization of what counts as an edge case that would trip up a reasonable human coder on the first try", I'm sure the 2022 or 2023 respondents would say that it meets their criteria for their threshold.
I never said it was sufficient for AGI, just that it was a milestone in AI that people thought was farther off than it turned out to be. This is applying to all subsets of intelligence AI is reaching earlier than experts initially predicted, giving good reason AGI (perhaps a synthesis of these elements coming together in a single model, or a suite of models) is likely closer than standard expert consensus.
The milestones your citing are all milestones of transformers that were underestimated.
If you think an incremental improvement in transformers are what's needed for AGI, I see your angle. However, IMO, transformers haven't shown any evidence of that capability. I see no reason to believe that they'd develop that with a bit more compute or a bit more data.
It's also worth pointing out that in the same survey it was well agreed upon that success would come sooner if there was more funding. The question was a counterfactual prediction of how much less progress would be made if there was 50% less funding. The response was about 50% less progress.
So honestly, it doesn't seem like many of the predictions are that far off with this in context. That things sped up as funding did too? That was part of the prediction! The other big player here was falling cost of compute. There was pretty strong agreement that if compute was 50% more expensive that this would result in a decrease in progress by >50%.
I think uncontextualized, the predictions don't seem that inaccurate. They're reasonably close. Contextualized, they seem pretty accurate.
This strikes me as "end game" type behavior. These companies see the writing on the wall, and are willing to throw everything they have left to retain relevance in the coming post-AGI world. To me I'm more alarmed than I am shocked at the pay packages.
As far as I know it's only one guy that got this offer, https://mattdeitke.com/ (aside from the others who had the mythical 100 million dollar poaching package).
they are executive roles in the sense that you are required to profitably allocate a scarce perishable resource (gpu time) way more expensive than any regular engineer’s time.
Yeah, you could definitely look at it that way. They are IC roles in the sense that their job is to tell computer computers what to do but maybe that’s old-fashioned thinking at this point.
Is there anything one can do to get in on this? Did I have to be at Stanford getting a PhD 10 years ago, or can I somehow still get on the frontier now as a generic software engineer who's pretty good at learning things, and end up working at one of these labs? Or is it impossible to guess exactly what is going to be desirable a few years from now that might get you in the game at that caliber?
If it were possible to guess, enough people would do it to drive the price to down to reasonable levels. Unless maybe you believe you are in the top 100 or so in the world able to do what it takes.
I'll give you two completely different and conflicting opinions!
Bear case: No, there's nothing you can do. These are exceptionally rare hires driven by FOMO at the peak of AI froth. If any of these engineers are successful at creating AGI/superintelligence within five years, then the market for human AI engineers will essentially vanish overnight. If they are NOT successful at creating AGI within five years, the ultra high-end market for human AI engineers will also vanish, because companies will no longer trust that talent is the key.
Bull case: Yes, you should go all in and rebrand as a self-proclaimed AI genius. Don't focus on commanding $250M in compensation (although 24, Matt Deitke has been doing AI/ML since high school). Instead, focus on optimizing or changing any random part of the transformer architecture and publishing an absolutely inscrutable paper about the results. Make a glossy startup page that makes some bold claims about how you'll utilize your research to change the game. If you're quick, you can ride the wave of FOMO and start leveling up. Although AGI will never happen, the opportunities will remain as we head into the "plateau of productivity."
Alright you twisted my arm im in. Already did a couple AI centric projects. HMU let's do this. Personally I want a bazaar for AI. not sure I like the future being decided by the current crop of billionaires.
Honestly, I think a lot of this is as much marketing as it is about actual value. This helps the industry narrative about how transformative the tech is. These inflated comp packages perfectly match the inflated claims around the tech. "See this tech is so incredible we are paying people 1 BILLION dollars!"
These types of comp packages also seem designed to create a kind of indentured servitude for the researchers. Instead of forming their own rival companies that might actually compete with facebook, facebook is trying to foreclose that possibility. The researchers get the money, but they are also giving up autonomy. Personally, no amount of money would induce me to work for Zuckerberg.
These are not just people with credentials, but are literally some of the smartest people on earth. Us normal people cannot and should not think we were just a few decisions away from being there.
There are millions of people with PhDs in math or computer science, and none of them earn that kind of salary. Just like there are Usain Bolts and Michael Phelpses in the world of sports, there are similarly exceptional individuals in every field.
I take this as a contrarian signal that Meta has hit serious roadblocks improving their AI despite massive data advantages and are throwing a bunch of "Hail Mary" desperation passes to achieve meaningful further progress.
>
I take this as a contrarian signal that Meta has hit serious roadblocks improving their AI despite massive data advantages
Just a thought:
Assuming that Meta's AI is actually good. Could it rather be that having access to a massive amount of data does not bring that much of a business value (in this case particularly for training AIs)?
Evidence for my hypothesis: if you want to gain a deep knowledge about some complicated specific scientific topic, you typically don't want to read a lot of shallow texts tangentially related to this topic, but the few breakthrough papers and books of the smartest mind who moved the state of art in the respective area. Or some of the few survey monographs of also highly smart people who work in the respective area who have a vast overview about how these deep research breakthroughs fit into the grander scheme of things.
There’s been a lot of research on the necessity of singular geniuses. The general consensus (from studies on Nobel Prizes and simultaneous patent rates) is that advances tend to be moved by the research community as a whole.
You can get that technical or scientific context for a lot less than $250 million per head.
250 million probably gets you a couple of research labs and incremental field advances per year?
Assuming a lab has 20 phds/postdocs and a few professors, call it 25 people per lab, and you're compute / equipment heavy, getting you up to an average of 1M per person per year in total fully loaded costs (including facilities overhead and GPUs and conferences and whatnot), then you're looking at 200 PhD researchers. Assuming that each PhD makes one contribution per 4 years, then that's 50 advances in the field per year from your lab. if only 10% are notable, that's 5 things you've gotten that people are going to get excited about in the field. You need 2% of these contributions to be groundbreaking to get a single major contribution per year.
So 250M for a single person is a lot, but if that person is really really good, then that may be only expensive and not insane.
There has to be more at play here. Was this some kind of acquihire? No 24 year old in the history of 24 year olds has been worth $250 million on the basis of their intellectual merit. Even granting that they were some kind of one-off super genius, no single human is that smart or productive, to be worth the bankroll of a literal army of PhDs. He has to be bringing more to the table.
Just glancing through the article, it seems like this person is a doctor of philosophy (hardly a "kid") and their doctorate is literally in the exact thing that everyone is throwing gobs and gobs of cash at. And I guess Meta (et al) sense that literal empires are at stake here, so this is probably just how much money that's worth to them.
Media has this strange need for fully-grown responsible adults to be thought of as children. Not only for the amazing stories of "this (mid-30s career professional) kid did something", but also helpful to try and shirk responsibility.
Thinking about attempts to frame SBF as a wee smol bean kid in over his head while actively committing fraud.
For almost every Doctorate except for a few who really want to become postdocs or somehow win the tenure lottery, there is a generally an economic disincentive to completing it.
Taking immediately available cash instead of finishing a PhD is almost always a good economic decision (we'll leave aside the fact that a PhD is almost always a disastrously bad economic decision).
The 250:1 substitution doesn't work because breakthrough AI research follows power law distributions where top researchers produce orders of magnitude more value through novel insights that can't be replicated by simply adding more average contributors.
I thought that when Apple reached a market cap of 1 trillion, but here we are today.... I since then abandoned any such prediction, even if i share your feeling
Hard numbers for market cap is a difficult measure - Apples price earnings is 33 currently, which is high but not over high. Ie. Apple has revenue to back their market cap.
The issue with high salaries is that there is a latent assumption that these people provide the multiples in additional value. That they are so smarter than everyone else.
This is simply not true, and will lead to a competitive disadvantage.
I guess there’s a lot of loaded language it’s not really worth debating. But I would never claim they’re ALL smarter than EVERYONE else.
But I would expect them to be smart and have relevant experience that everyone else doesn’t have, and I expect the companies offering these salaries aren’t doing it for fun but because they believe their IP or ability to generate IP is very hard to come by, and it’s better to monopolize that talent than let competitors do so. If they could hire 10 people equally as good for 1/10 the price then they would do so. But I’m sure there’s also a large dose of gambling too; even in sports highly anticipated freshman drafts can turn into duds.
The fact is that the incumbents with all their money are in a good position to defend against anything and counterattack.
When OpenAI was making waves the first time, then Google launched their neutered incapable competitor, I thought it is “over” for Google because why would anyone use search anymore (apart from the 1% of use cases where it gives better results faster), and clearly they are incapable of building good new products anymore…
and now they are there with the best LLMs and they are at the top of the pack again.
Billions of dollars in the bank, great developers, good connections to politicians and institutions mean that you are hard to replace even if you fumble it a couple of times.
It is indeed; those people hired at those salaries are not going to "produce" more than the people hired at normal salaries.
Because what we have now is a "good enough" so getting a 10x better LLM isn't going to produce a 10x increase in revenue (nevermind profit).
The problem is not "We need a better LLM" or "We need cheaper/faster generation". It's "We don't know how to make money of this".
That doesn't require engineers who can creat the next generation SOTA in AI, that requires business people who can spot solutions which simply needs tokens.
Before an imminent recession you might want to focus on funds that primarily cover sectors that enjoy steady demand even during crisis, like utilities, consumer staples, healthcare, maybe some hedge against inflation like precious metals. I would avoid tech and luxuries and would definitely avoid crypto also. There is no historical data to show how it would perform during a serious recession (Bitcoin was basically born during the last one) but I doubt it would be pretty.
Stock buybacks and cryptocurrency are ways to circumvent the Fed's monopoly on currency. The US is not a single monetary economy anymore, it's several. None of the economic analysis institutions know work anymore.
Combined with the trump economy its going to be interesting. I pulled out in end of January when they were actually going forward with tariffs in the most stupid way possible.
Funny there's trillions of dollars in the span of two years literally pointing to the writing on the wall and you're so arrogant and blinded by cope that you can't see it. You legacy engineers really are something else.
You have exactly the same level of conviction toward an unknowable outcome, I think both of you would be better served by reading the middle ground instead of subscribing to a false dichotomy of boom or bust.
I think the biggest confuser here is that there are really two games being played, the money game and the technology game. Investments in AI are going to be largely driven by speculation on their monetary outcome, not technological outcome. Whether or not the technology survives the Venture Capital Gauntlet, the investment bubble could still pop, and only the businesses that have real business models survive. Heaps of people lose their shirt to the tune of billions, yet we still have an AI powered future of some kind.
All this to say, you can both be certain AI is a valuable technology and also believe the economics around it right now are not founded in a clear reality. These are all bets on a future none of us can be sure of.
You can absolutely be sure of market forces not destroying established behemoths. It simply doesn't happen frequently. Inertia is a real thing. Look at Uber, Tesla, etc. I dont think there necessarily won't be a bust for many fledgeling AI companies though, in fact I'm certain there will be.
But thinking Tech Giants are going to crash is woefully ignorant of how the market works and indicates a clear wearing of blinders. And it's a common one among coders who feel the noose tightening and who are the types of people led by their own fear. And i find that when you mix that with arrogance, these three traits often correlate with older generations of software engineers who are poor at adapting to the new technology. The ones who constantly harp on how AI is full of mistakes and disregard that humans are as well. The ones who insist on writing even more than 70% of their own code rather than learning to guide new tools granularly. It's a take that nobody should entertain or respect.
As for your point on 'future none of us can be sure of.' I'll push back on that:
It is not clear how AGI or ASI will come about, ie. what architecture will underpin it.
However - it is absolutely clear that AI powered coding will continue to improve, and that algorithmic progress can and will be driven by AI coders, and that that will lead to ASI.
The only way to not believe that is to think there is a special sauce behind consciousness. And I tend to believe in scientific theory, not magic.
That is why there is so much VC. That is why tech giants are all racing. It isn't a bet. It is a race to a visible, clear goal of ASI that again, it takes blinders to not see.
So while AI is absolutely a bubble, this bubble will mark the transition to an entirely new economic system, society, world, etc. (and flip a coin on whether any of us survive it lol, but that's a whole separate conversation)
Just like few years ago “blockchain contract auditors”, and before that “big data bla bla”, and before that “cybersecurity xyz”, you always have people who try to grift as much as possible from the ${current bubble}.
Lol. I was leading development of a project that did everything his project Vy does and much more, before my company experienced a hostile takeover and I was squeezed out so they could pivot to a shitass AI sex bot company that ultimately ran through our warchest and failed. That was back in 2022-2023.
Maybe I need to get one of these recruitment agents.
It's still peanuts compared to what owners make when their startup goes big. Seems reasonable that there's still room for small startups in AI with smarter approaches that don't require Manhattan project scale at a big company. Whether successful startups should sell out to big companies or become one themselves is the 64 billion question.
Mr. Deitke, who recently dropped out of a computer science Ph.D. program at the University of Washington, had moonlighted at a Seattle A.I. lab, the Allen Institute for Artificial Intelligence. There, he led the development of a project called Molmo, an A.I. chatbot that juggles images, sounds and text — the kind of system that Meta is trying to build.
Probably Zuck is trying to prop up his failed Metaverse with "AI". $250 million is nothing compared to what has already been sunk into that Spruce Goose.
What a sensationalized article. NY Times should be embarrassed for publishing this drivel. One superstar researcher does not equate an industry. Perhaps NY Times should consider paying its journalists the same wage as Pulitzer prize winners.
I think Meta has a problem of none of their users wanting any more of their services and they have a very distinct brand taint
Paying 250m to a genius to more deeply entrap user time and attention is going to look diabolical unless there are measurable user life improvement outcome measurements... if metas more slop addiction that 250m is a diabolical contract
Not to make less of the guy, but aside from being a winner of a paper contest, the other ventures do not seem very novel: a startup to create AI agents that can use the Internet? Seems…common.
Good for him. Unfortunately, though, what I have seen is that luminaries like this never match their external accomplishment once inside. I have names I saw firsthand but it would be rude to share.
A couple of exceptions come to mind. It seems Marc Levoy has been as effective pushing imaging technology inside BigCo's as he was at Stanford Research, e.g. But more often it's one-hit wonders.
As the margins shrink between the capabilities of each of these models, those who specialize in retrieval / context engineering will be the next frontier. Those who provide the most relevant information to a model will win the day.
At those prices they have to be hiring god gifted talent. I can’t imagine that being just a regular academic grinder with top grades. Arod made $250 million and it was considered huge news.
This is all about industrial robotics. In order to train robotics AI, Zuckyrberg must create realistic "embodied" farmvilles for users to play. This is likely the only path to robotics for facebook, hence the ballistic spending.
Of course, their job is to make their own job redundant. If they are true believers, this is the last paycheck they might ever get.
After that, it's manual labor like the plebs or having enough savings to ~~last them the rest of their lives~~ invest and "earn" passive income by taking a portion of the value produced by people who still do actual work.
When more than 1 company has "AGI", or whatever we're calling it, and people realise it is not just a license to print money.
Some people are rightly pointing out that for quite a lot of things right now we probably already have AGI to a certain extent. Your average AI is way better than the average schmuck on the street in basically anything you can think of - maths, programming, writing poetry, world languages, music theory. Sure there are outliers where AI is not as good as a skilled practitioner in foo, but I think the AGI bar is about being "about as good as the average human" and not showing complete supremacy in every niche. So far the world has been disrupted sure, but not ended.
ASI of course is the next thing, but that's different.
I think the AI is only as good as the person wrangling it a lot of the time. I think it's easy for really competent people to get an inflated sense of how good the AI is in the same way that a junior engineer is often only as good as the senior leading them along and feeding them small chunks of work. When led with great foresight, careful calibration, and frequent feedback and mentorship, a mediocre junior engineer can be made to look pretty good too. But take away the competent senior and youre left pretty lacking.
I've gotten some great results out of LLM's, but thats often because the prompt was well crafted, and numerous iterations were performed based on my expertise.
You couldn't get that out of the LLM without that person most of the time.
> I think the AI is only as good as the person wrangling it a lot of the time.
To highlight the inverse: If someone truly has an "AGI" system (the acronym the goalposts have been moved-to) then it wouldn't matter who was wrangling it.
Nah. The models are great, but the models can also write a story where characters who in the prompt are clearly specified as never having met are immediately addressing each other by name.
These models don't understand anything similar to reality and they can be confused by all sorts of things.
This can obviously be managed and people have achieved great things with them, including this IMO stuff, but the models are despite their capability very, very far from AGI. They've also got atrocious performance on things like IQ tests.
Yeah, that framing for LLMs is one of my pet-causes: It's document generation, some documents resemble stories with characters, and everything else (e.g. "chatting" with an LLM) is an illusion, albeit an impressive and sometimes-useful one.
Being able to generate a document where humans perceive plausible statements from Santa Claus does not mean Santa Claus now lives inside the electronic box, that flying sleighs are real, etc. The principle still holds even if the character is described as "an intelligent AI assistant named [Product Name]".
“AGI” will be whatever state of the art we have at the time the money runs out. The investors will never admit that they built on sand but declare victory by any means necessary, even if it's hollow and meaningless.
Perhaps when society balances benefits of AI against energy and environmental costs? I have worked through two ‘AI winters’ when funding dried up. This might happen again.
I think a possible scenario is that we see huge open source advances in training and inference efficiency that ends up making some of the mega-investments in AI infrastructure look silly.
What will probably ‘save’ the mega-spending is (unfortunately!) the application of AI to the Forever Wars for profit.
I just don’t think the industry is moatless. Where there is a moat in my opinion is airgap because few are pursuing this and not everyone wants their data in the Cloud.
There is definitely a bubble though. Tesla has 28 times larger market cap than other well-run competitors, for example, and there's a bunch of other firms with similarly crazy numbers.
AI is great and it's the future, and a bunch of people will probably eventually turn it into very powerful systems able to solve industrially important maths and software development problems, but that doesn't meant they'll make huge money from that.
Given that $5k in nVidia in 2015 when their stock was trading at $0.75/share would be $1.1M today at $173.72/share, that's very principled of you to have the winning pick ready, and not do it.
People are focused on the skills these people must possess or the experience.
Chances are good that while they’re competitive for sure, what they really have that landed them these positions is connections and the ability to market themselves well.
It's similar to how, near the end of a Monopoly game, a player might indiscriminately hand over a stash of $100 bills to acquire Mediterranean Avenue, even though the property is mortgaged.
Which analogy(s) are you going for? The world is about to end so money is essentially worthless? The players with all the money are going to move on to something else soon? The game ceased to be fun for anyone so they all want to find other things to do?
I assume you are going for “there are no more useful resources to acquire so those with all the resources overpay just to feel like they own those last few they don’t yet own”.
I saw the ‘forgetting about money, moving on to other challenges’ thing happen about 30 years ago. A childhood friend sold his company for about 300 million (a billion in today’s dollar devaluation?). My friend and his wife continued to live in their same house. The only thing he did was to purchase eight houses for extended family members who didn’t own their own homes, he also got his daughter expensive horse back riding lessons and a horse, and he said he and his wife drank more expensive wine. He did continue to play “The Infinite Game” by staying in the tech industry - it seemed like he loved the game, the money was only to help other people in his life.
Yes but countries are run by governments, which are composed of people, who can be bribed. If you believe that AI will make you the richest person in human history, you presumably can see that the problem of government can be solved with enough money.
Presumably they think that, whatever chance they have of becoming kings if they get there first is more than the chance if someone else does. In we get AGI, we is doing all the work.
If capitalism breaks it will be to the benefit of very few.
Granted, capitalism needs maintenance.
Externalities need to be consistently reflected, so capitalism can optimize real value creation, instead of profitable value destruction. It is a tool that can be very good at either.
Capitalism also needs to be protected from corrupted government by, ironically, shoring up the decentralization of power so critical for democracy, including protecting democracy from capitalism's big money.
(Democracy and capitalism complement each other, in good ways when both operating independently in terms of power, and supportively in terms of different roles. And, ironically, also complement each other when they each corrupt the other.)
Imagine if any one of these tech companies decided the future was in solving problems for humanity rather than how to serve adverts in a future where content was autogenerated.
The money and resources they have available is astronomical.
Instead they spend it on future proofing their profits.
For a few years it seemed like Tesla and SpaceX were those companies - reducing our dependence on fossil fuels, boosting clean transportation and solar, pushing forward space exploration.
But the promises turned into stock boosting lies; the environmental good into vote buying for climate change deniers, and space exploration into low earth cell-towers.
Those years were a long time ago for me. I’ve been arguing musk is a snake oil salesman since at least 2014. I lost friends over it at the time, people who were very heavily invested into musk, both financially and for some reason, emotionally.
how is he snake oil s. since that time, he with his several teams, actually made electric cars a market wide reality, cheap orbit rockets and with starlink internet almost everywhere possible on earth? snake oil would be over without actually changing the history.
> he with his several teams, actually made electric cars a market wide reality
Electric cars? That would be Martin Eberhard and Marc Tarpenning, Tesla’s actual founders. They created the Roadster and brought the vision. Musk came in with money, staged a hostile takeover, and then rewrote the company’s history to fit his inflated ego, like the sad little man he is. It's honestly cringe.
> cheap orbit rockets and with starlink internet almost everywhere possible on earth
Amazing what billions in government contracts and management smart enough to keep Elon out of the way can accomplish. SpaceX deserves praise; spinning it into a Elon is a genius narrative? Not so much.
As for the snake oil, just a few of Elon's greatest hits:
1. Hyperloop. Old idea's wrapped in new buzzwords. Never viable. He didn’t invent it, but he sure wants you to think he did, just like with Telsa.
2. FSD “next year” since forever. Still not here. Still being marketed like it's solved. And still charging like a wounded bull for it.
3. Robotaxis and appreciation hype. Musk literally claimed Teslas would go up in value and earn passive income as robotaxis. It doesnt get much more snake oil than this.
"We’re confident the cars will be worth more than what you pay for them today." – July 2019
"It’s financially insane to buy anything other than a Tesla." – April 2019
Absolutely laughable. Show me one consumer owned Tesla that’s worth more today than it was in 2019. I’ll wait. If you can't, we'll mark it down as snake oil bullshit.
4. Optimus. Elon hyped this like Tesla had cracked general purpose humanoid robotics out of nowhere, leapfrogging companies that have been grinding on this for decades. The first reveal? A guy in a suit dancing. The follow ups? Stiff prototypes doing slow, assisted movements and following that, remotely controlled animatronics and so on. Meanwhile, Musk is on stage talking about replacing human labor, reshaping the economy, and bots becoming more valuable than cars. None of it is remotely close. But it worked, stock popped, headlines flooded in, and the fantasy sold.
5. SolarCity. An overhyped, underdelivered money pit that Tesla had to bail out. Just another Elon tyre fire.
6. "Funding secured." Flat out lied about taking Tesla private at $420. SEC slapped him, but the stock soared. Mission accomplished.
And that’s just scratching the surface of his bullshit. It ignores all the other missed deadlines, quality issues, inflated delivery claims, etc etc etc. Here is some more of his bullshit, also I am sure not exhaustive:
Yes, he’s had wins. But wins don’t erase the mountain of bullshit. Elon’s biggest output isn’t cars or rockets. It’s hype. His true skill is selling fantasy to retail investors and tech worshipping middled aged white dudes who still think he’s some genius messiah. Strip the PR away, and you’ve got a guy who overpromises, underdelivers, and never stops running his mouth.
man I'm so sorry for you. Like if you can't understand what some people lead or achieve, which is real with rockets and such. You just write long BS for you bias. Have a good day
"In the real world, this has led to a pathology where the tech sector maximizes its own comfort. You don't have to go far to see this. Hop on BART after the conference and take a look at Oakland, or take a stroll through downtown San Francisco and try to persuade yourself you're in the heart of a boom that has lasted for forty years. You'll see a residential theme park for tech workers, surrounded by areas of poverty and misery that have seen no benefit and ample harm from our presence. We pretend that by maximizing our convenience and productivity, we're hastening the day when we finally make life better for all those other people.
We should not listen to people who promise to make Mars safe for human habitation, until we have seen them make Oakland safe for human habitation. We should be skeptical of promises to revolutionize transportation from people who can't fix BART, or have never taken BART."
"Living standards in Poland in 2010 had more than doubled from 1990. In the same time period, in the United States, I’ve seen a whole lot of nothing. Despite fabulous technical progress, practically all of it pioneered in our country, there’s been a singular failure to connect our fabulous prosperity with the average person.
A study just out shows that for the median male worker in the United States, the highest lifetime wages came if you entered the workforce in 1967. That is astonishing. People born in 1942 had better lifetime earnings prospects than people entering the workforce today.
You can see this failure to connect with your own eyes even in a rich place like Silicon Valley. There are homeless encampments across the street from Facebook headquarters. California has a larger GDP than France, and at the same time has the highest poverty rate in America, adjusted for cost of living. Not only did the tech sector fail to build up the communities around it, but it’s left people worse off than before, by pricing them out of the places they grew up."
At the same time, asking them to solve social problems with money and technology and dubious morality doesn't look like the way forward either.
Very aptly, the Manhattan Project or Space Race weren't aimed at the improvement of mankind per se. Motivation was a lot more specific and down to earth.
There are sports stars who are paid similarly - rare talent that is in demand. Luckily there aren’t “software unions” like there are players’ unions to cap the max payment.
Any left wing / socialist person on HN should be ecstatic - literally applauding with grins on their faces - that workers are extracting such sums out of the capitalist class. The hate for these salaries is mind boggling to me, and shows a lot of opposition to labor being paid what they are due is more about envy than class consciousness
Well I applaud their ability to get that bag. But in terms of raising the floor for a lot of people, this is not that.
I don't feel strongly about these salaries beyond them being an indication of deep dysfunction in the system. This is not healthy, for a market or for a society. No-one should be paid these amounts but I don't care about these developers because they don't run the system.
I've benefited from devs being paid well. Not that well. But same thing in concept.
Would you say that same thing about executives and CEOs?
I'm guessing not, but both the AI expert and the CEO are agents for the owner class: it is owners like Elon and Sam Altman that are deciding to pay these huge salaries and they are doing it for the same reason that corporate boards of directors pay CEOs huge salaries: namely, to help the owners accumulate more capital.
I appreciate the sentiment but the issue is still really clear. This guy getting so much money hasn't made anything more equal, it's just added another individual to an elite class of wealth. Had these salaries been distributed across everyone as it is clearly affordable to do, it would be a different story.
This gentleman now has an entirely different set of problems to everyone else. Do you think he will now go on to advocate for wealth equality, housing affordability, healthcare etc, or do you think he'll go buy some place nice away from his former problems and enjoy his (earned) compensation in peace?
People also complain about the high salaries of CEOs. A lot of opposition to labor being paid what they are due is more about envy than class consciousness.
Yea because everyone knows CEOs just take credit for the work the real engineers and others do… I’d far prefer researchers or developers getting this kind of money instead of a CEO…
I don't get the down votes. Any good leftist likes seeing skilled workers having unskilled rentiers over the barrel.
Personal anecdote time. One of the people named in the press as having turned down one of these hyper-offers used to work in an adjacent team, same "pod" maybe, whatever adjacent. That person is crazy smart, stands out even among elite glory days FAANG types. Anyways they left and when back on the market I was part of the lobby to get them back at any price, had to run it fairly high up the flagpole (might have been Sheryl who had to sign off, maybe it was Mark).
Went on to make it back for the company a hundred fold the first year. Clearly a good choice to "pay over market".
Now it's a little comical for it to be a billion or whatever, that person was part of a clique of people at that level and there's a lot of "brand" going into a price tag like that: the people out of our little set who did compilers or whatever instead of FAIR are just as good and what is called "AI" now is frankly not that differentiated (the person in question maintained as much back in the day).
But a luck and ruthlessness hire like Zuckerberg on bended knee to a legitimate monster hacker and still getting dissed? Applause. I had Claude write a greentext for the amusement of my chums. I recommend it kek.
You didn't read marx and the person above you clearly did.
Marx hated the bourgeoisie (business owners, including petite-bourgeoisie AKA small business owners) and loved the proletariat - including the extremely skilled or well paid proletarians.
Marx also hated the lumpen-proletariet - AKA prostitutes, homeless, etc.
One of my favourite Marx reminiscences is how his colleagues tried to buy him some IPR to provide for his wellbeing in later life: patent rights. Literally rent seeking on innovation. I'm not sure if it's in Emile Burns biography.
What I did or didn't read is alas occluded from you. The Masereel illustrated woodcuts on a recent edition of the manifesto are wonderful.
wait-wait-wait. So a SWE investing in VT is just a well-skilled proletarian owning a share of the global means of production? is this communism already?
it was never about rising salaries, it was always about upper middle class urbanites showing fake concern towards the lower class by disparaging people who earn more than them.
one would think that a talented academic/researcher getting a 1B salary would impress the socialist people but it doesn't because it was never about that. it was about bringing rich people down and not much else.
When I was a kid in the 80s I read the book "Hackers" and it describes the most successful people in the industry as having "Croesus" wealth: counted in the tens of millions of dollars.
Zuck made him and offer that couldn't be refused. But neither salaries or hype or hope are what AI should be measured against. LLM based AI should be measured against previous technological revolutions, in terms of sustained real income growth and ideally real income growth per person.
Right now capital expenses are responsible for most of AI's economic impacts, as seen by the infrastructure spend contributing more to GDP than consumer spending this year.
And yet this one guy's deal possibly represents 0.5% of the total profit that everyone except Nvidia is making out of this wave of AI. Maybe even more.
- He's on track to becoming a top-tier AI researcher. Despite having only one year of a PhD under his belt, he already received two top awards as a first-author at major AI conferences [1]. Typically, it takes many more years of experience to do research that receives this level of recognition. Most PhDs never get there.
- Molmo, the slate of open vision-language models that he built & released as an academic [2], has direct bearing on Zuck's vision for personalized, multimodal AI at Meta.
- He had to be poached from something, in this case, his own startup, where in the best case, his equity could be worth a large multiple of his Meta offer. $250M likely exceeded the expected value of success, in his view, at the startup. There was also probably a large premium required to convince him to leave his own thing (which he left his PhD to start) to become a hired hand for Meta.
Sources:
[1] https://mattdeitke.com/
[2] https://allenai.org/blog/molmo
Exactly. What's the likelihood of that?
Zuck's advantage over Sir Isaac (Newton) is that the market for top AI researchers is much more volatile than in South Sea tradeables pre-bubble burst?
Either that or 250M is cheap for cognitive behavior therapy
Sufficiently high that Meta is willing to pay such an amount of money. :-)
I'd forget the word shareholder even exists.
- Percy Bysshe Shelley
It's fine to think that we're in a bubble and to post a comment explaining your thoughts about it. But a comment like this is a low-effort, drive-by shoot-down of a comment that took at least a bit of thought and effort, and that's exactly what we don't want on HN.
>"The first is enabling business AIs within message threads ... We’re expanding business AIs to more businesses in Mexico and the Philippines. And we expect to broaden availability later this year as we keep refining the product."
>"The second area of business AI development is within ads ... We’re currently testing this with a small number of businesses across Feed and Reels on Facebook and Instagram as well as Instagram Stories."
>"And then the final area that we are exploring is business AIs on business websites to help better support businesses across all platforms ... and we’re starting to test that with a few businesses in the US."
So it's just very small scale tests so far - not the sort of thing that would have any measurable impact on their revenue.
[0]: https://s21.q4cdn.com/399680738/files/doc_financials/2025/q2...
Hitmen get what, $5-50k? And that’s for murder.
Mine is a hell of a lot lower than $250M, and I would bet half of that that yours is too.
Meta will have more AI-compute than he ever hoped to get at his - and most other - startups.
But if he's getting real, non-returnable actual money from Meta on the basis of a back of envelope calculation for his own startup, from Meta's need to satiate Mark Zuckerberg's FOMO, then good for him.
This bubble cannot burst soon enough, but I hope he gets to keep some of this; he deserves it simply for the absurd comedy it has created.
I hope for all of our sake's that you're right. I feel confident that you're not :(
I have two questions about this, really:
- is he going to be the last guy getting this kind of value out of a couple of research papers and some intimidated CEO's FOMO?
- are we now entering a world where people are effectively hypothetical acquihires?
That is, instead of hiring someone because they have a successful early stage startup that is shaking the market, you hire someone because people are whispering/worried that they could soon have a successful early stage startup?
The latter of these is particularly worrisomely "bubbly" because of something that people don't really recognise about bubbles unless they worked in one. In a bubble, people suspend their disbelief about such claims and they start throwing money around. They hire people without credentials who can talk the talk. And they burn money on impossible ideas.
The bubble itself becomes increasingly intellectually dishonest, increasingly unserious, as it inflates. People who would be written off as fraudsters at any other time are taken seriously as if they are visionaries and ultra-productive people, because everyone's tolerance for risk increases as they become more and more desperate to ride the train. People start urgently taking impossible things at face value, weird ideas get much further advanced much more quickly, and grifters get closer to the target -- the human source of the cash -- faster than due dilligence would ordinarily allow them.
"This guy is so smart he could have a $1bn startup just like that" is an obvious target for con artists and grifters. And they will come.
For clarity I am ABSOLUTELY NOT saying that the subject of this article is such a person. I am perfectly happy to stipulate that he's the real deal.
But he is now the template for a future grift that is essentially guaranteed to happen. Maybe it'll be a team of four or five people who get themselves acquihired because there's a rumour they are going to have billions of dollars of funding for an idea. They will publish papers that in a few months will be ridiculed. And they will disappear with a lot of money.
And that could burst your bubble.
You started to sound like Dario, who likes to accuse others as intellectually dishonest and unserious. Anyway, perhaps the strict wage structure of Anthropic will be its downfall in this crazy bubble?
The same thing happened in the dotcom era, the same thing happened in the run-up to the subprime mortgage crisis. Every single bubble displays these characteristics.
Nightmare Future!
It's the same reason that sports stars, musicians, and other entertainers that operate on a global scale make so much more money now than they did 100 years ago. They are serving a market that is thousands of times larger than their predecessors did, and the pay is commensurately larger.
1) The winner immediately becomes a monopoly
2) All investments are directed from competitors, to the winner
3) Research on AGI/ASI ceases
I don't see how any of these would be viable. Right now there's an incremental model arms race, with no companies holding a secret sauce so powerful that they're miles above the rest.
I think it will continue like it does today. Some company will break through with some sort of AGI model, and the competitors will follow. Then open source models will be released. Same with ASI.
The things that will be important and guarded are: data and compute.
So maybe the issue is more about staying in the top N, and being willing to pay tons to make sure that happens.
That's probably true, but at the moment the only thing that creates something resembling a moat is the fact that progress is rapid (i.e. the top players are ~6-12 months ahead of the already commoditized options, but the gap in capabilities is quite large): if progress plateaus at all, the barrier to be competitive with the top dogs is going to drop a lot, and anyone trying to extra value out of their position is going to attract a ton of competition even from new players.
We are already seeing diminishing returns from compute and training costs going up, but as more and more AI is used in the wild and pollutes training data, having validated data becomes the moat.
At work we are optimising cost by switching in different models for different agents based on use case, and where testing has demonstrated a particular model's output is sufficient.
If this were winner-take-all market with low switching costs, we'd be seeing instant majority market domination whenever a new SOTA model comes out every few weeks. But this isn't happening in practice, even though it's much easier to switch models on OpenRouter than many other inference providers.
I get the perception of "winner-take-all" is why the salaries are shooting up, but it's at-odds with the reality.
[1] https://openrouter.ai/rankings
> If the very best LLM is 1.5x as good as good as the next-best, then pretty much everyone in the world will want to use the best one
Is it? Gemini is arguably better than OAI in most cases but I'm not sure it's as popular among general public
I think what we're seeing here is superstar economics, where the market believes the top players are disproportionately more valuable than average. Typically this is bad, because it leads to low median compensation but in this rare case it is working out.
It would be unfortunate if something like Grok takes the cake here.
Well only if the price is the same. Otherwise people will value price over quality, or quality over price. Like they do for literally every other product they select...
You are not one random hyperparameter away from the SciFi singularity. You are making iterative improvements and throwing more compute at the problem, as are all your competitors, all of which are to some degree utterly exchangeable.
Yes, the figures are nuts. But compare them to F1 or soccer salaries for top athletes. A single big name can drive billions in that context at least, and much more in the context of AI. $50M-$100M/year, particularly when some or most is stock, is rational.
Like I definitely think it is better for society if the economic forces are incentivizing pursuit of knowledge more than pursuit of pure entertainment[0]. But I think we also need to be a bit careful here. You need some celebrities to be the embodiment of an idea but the distribution can be too sharp and undermine, what I think we both agree on is, the goal.
Yeah, I think, on average, a $100M researcher is generating more net good for a society (and world) than a $100M sports player or actor. Maybe not in every instance, but I feel pretty confident about this on average. But at the same time, do we get more with one $100M researcher or 100 $1M researchers? It's important to recognize that we're talking about such large sums of money that at any of these levels people would be living in extreme luxury. Even in SV the per capita income is <$150k/yr, while the median income is medium income is like half that. You'd be easily in the top 1%. (The top 10% for San Jose is $275k/yr)
I think we also need to be a bit careful in recognizing how motivation can misalign incentives and goals. Is the money encouraging more to do research and push humanity's knowledge forward? Or is the money now just another means for people that just want money to exploit, who have no interest in advancing humanity's knowledge? Obviously it is a lot more complicated and both are happening but I think it is worth recognizing that if things shift towards the latter than they actually make it harder to achieve the original goals.
So on paper, I'm 100% with you. But I'm not exactly sure the paper is matching reality.
[0] To be clear, I don't think entertainment has no value. It has a lot and it plays a critical role in society.
For whatever reason, remuneration seems more concentrated than fundamentals. I don't begrudge those involved their good luck, though: I've had more than my fair share of good luck in my life, it wouldn't be me with the standing to complain.
“Our Rock Stars Aren't Like Your Rock Stars”
https://youtu.be/7l_oTgKMi-s
Locking up more of the world's information behind their login wall, or increase their ad sales slightly is not enough to make that kind of money. We can only speculate, of course, but at the same time I think the general idea is pretty clear: AI will soon have a lot of power, and control over that power is thought to be valuable.
The bit about "building great things" certainly rings true. Just not in the same way artists or scientists do.
If you do not believe this narrative, then your .com era comment is a pretty good analysis.
What, it used to be 2025? Then 2027? Now 2030? I know these are not all the same people but there are trends of to keep pushing it back. I guess Elon has been saying full self-driving is a year away since 2016 so maybe this belief can sustain itself for quite some time.
So my second question is: does the expectation of achievements being so close lengthen the time to make such achievements?
I don't think it is insane to think it could. If you think it is really close you'd underestimate the size of certain problems. Claim people are making mountains out of molehills. So you put efforts elsewhere, only to find that those things weren't molehills after all.
Predictions are hard and I think a lot of people confuse critiques with lack of motivation. Some people do find flaws and use them as excuses to claim everything is fruitless. But I think most people that find flaws are doing so in an effort to actually push things forward. I mean isn't that the job of any engineer or scientist? You can't solve problems if you can't identify problems. Triaging and prioritizing problems is a whole other mess, but it is harder to do when you're working at the edge of known knowledge. Little details are often not so little.
It's going to persist until shareholders punish them for it. My guess is it's going to be some near-random-trigger, such as a little-known AI company declaring bankruptcy, but becoming widely reported. Suddenly, investing in AI with no roadmap to profitability will become unfashionable, budget cuts, down-rounds, bankruptcies and consolidation will follow. But there's no telling when this will be, as there's elite convergence to keep the hype going for now.
Telco capex was $100 billion at the peak of the IT bubble, give or take. There's going to be $400 billion investments in AI in 2025.
While there's a lot of money going towards research, there's less than there was years ago. There's been a shift towards engineering research and ML Engineer hiring. Fewer positions for lower level research than there were just a few years ago. I'm not saying don't do the higher level research, just that it seems weird to not do the lower level when the gap is so small.
I really suspect that the winner is going to be the one that isn't putting speed above all else. Like you said, first to market isn't everything. But if first to market is all the matters then you're also more likely to just be responding to noise in the system. The noisy signal of figuring out what that market is in the first place. It's really easy to get off track with that and lose sight of the actual directions you need to pursue.
Which that framing weirdly undermines DeepSeek's own accomplishments. They did do some impressive stuff. But that's much more technical and less exciting of a story (at least to the average person. It definitely is exciting to other AI researchers).
Remember capsule networks?
You bring up the only relevant data point at the end, as a throw in. Nobody outside of academia cares about your PhD and work history if you have a startup that is impressive to them. That's the only reason he's being paid.
Don’t get me wrong, they are smart people - but so are thousands of other researchers you find in academia etc. - difference here is scale of the operation.
Even if it’s 1% at the scale you’re talking that’s 1B to the company. So still worth it.
Wild.
For AI researchers pursuing AGI, this variance between distributions is arguably even worse than the distribution between samples - there's no past data whatsoever to build estimates, it's all vibes.
You can argue the distribution is hard to pin down (hence my note on risk), but let’s not pretend there’s zero precedent.
If it turns out to be another winter at least it will have been a fucking blizzard.
But the distribution for individual researcher salaries really is pure guesswork. How does the datapoint of "Attention Is All You Need?" fit in to this distribution? The authors had very comfortable Google salaries but certainly not 9-figure contracts. And OpenAI and Anthropic (along with NVIDIA's elevated valuation) are founded on their work.
I'd argue the top individual researchers figure into the overall AI spend. They are the people leading teams/labs and are a marketable asset in a number of ways. Extrapolate this further outward - why does Jony Ive deserve to be part of a $6B aquihire? Why does Mira Murati deserve to be leading a 5 month old company valued at $12B with only 50 employees? Neither contributed fundamental research leading to where we are today.
How much revenue does Google make in a day? £700m+.
They're not high because of performance/results alone.
I can't help but think that the structure of this kinda hints at there being a bit of a scam-y element, where a bunch of smart people are trying to pump some rich people out of as much money as possible, with questionable chances at making it back. Imagine that the people on The List had all the keys needed to build AGI already if they put their knowledge together, what action do you think they would take?
You can just doodle away with whatever research interests you the most, there's no need to deliver a god mode AI to the great leader even if you had the ability to.
I suggest we saw a clear demonstration of that with the Metaverse and the answer is no, but more intensely than two letters can communicate.
.. that had already leaked and would later plummet in value.
These AI researchers fundamentally need access to tons of compute, data and engineers in order to pursue their passion.
There is hope for humanity.
Jokes aside, how and why?
We are in a time where the impact can be measured more quickly, so good for the engineers taking advantage of this.
For example, Meta seem to be spending so much so they don't later have to fight a war against an external Facebook-as-chatbot style competitor, but it's hard to see how such a thing could emerge from the current social media landscape.
Why why would they need fears about a quasi-facebook chatbot?
Anyhow, with the Metaverse as a flop, and apparently having self-assessed Meta's current LLM efforts as unsatisfactory, it seems Zuck may want to rescue his reputation by throwing money at it to try to make his next big gamble a winner. It seems a bit irrational given that other companies, and countries, have built SOTA LLMs without needing to throw NBA/NFL/rockstar money around.
This is the same thing. It is the new shiny tech demo that is really cool. And technically works really, really well and has some real uses, but that doesn’t make a multi billion dollar business.
I mean I'm with you, I think these things are pretty far away and are going to cost a lot of money to make and require a lot of failure in the mean time. But then again, it looks like they spent ~$18bn on Reality Labs last year. So if he was funding it all on his own dime, his current $260bn of wealth would give him a good 14 years runway if we ignore interest. It would be effectively indefinite if he earns about a 5% interest on that money.
I guess I'm just trying to say, it's hard to think about these things when we're talking about such scales of wealth. I mean at those scales, I'm pretty sure the money is meaningless, that money (and the ability to throw it around) is more a proxy for ego.
He's not there yet, and he knows it. Jobs gave us GUIs and smartphones. Facebook is not even in the same universe, and Instagram is just something he bought. He went all in on the metaverse, but the technology still needs at least 10-15 years to fully bake. In the meantime, there's AGI/super-intelligence. He needs to beat Sam Altman.
The sad thing is, even if he does beat Sam to AGI, Sam will still probably get the credit as the visionary.
Steve Jobs neither gave/invented GUIs nor smartphones. :-D
The only case where this may have made sense - but more for an individual rather than a team - is Google's aqui-rehire of Noam Shazeer for $1B. He was the original creator of the transformer architecture, had made a number of architectural improvements while at Character.ai, and thus had a track record of being able to wring performance out of it, which at Google-scale may be worth that kind of money.
It is the same thing in sports as well. There will only ever be one Michael Jordan one Lionel Messi one Tiger Woods one Magnus Carlsen. And they are paid a lot because they are worth it.
>> Meta seem to be spending so much so they don't later have to fight a war against an external Facebook-as-chatbot style competitor
Meta moved on from facebook a while back.It has been years since I last logged into facebook and hardly anybody I know actually post anything there. Its a relic of the past.
It’s not just uncomfortable but might not be true at all. Sports is practically the opposite type of skills: easy to measure, known rules, enormous amount of repetition. Research is unknown. A researcher that guarantees result is not doing research. (Coincidentally, the increasing rewards in academia for incrementalist result driven work is a big factor in the declining overall quality, imo.)
I think what’s happening is kind of what happened in Wall Street. Those with a few documented successes got disproportionately more business based to a large part on initial conditions and timing.
Not to take away from AI researchers specifically, I’m sure they’re a smart bunch. But I see no reason to think they stand out against other academic fields.
Occam’s razor says it’s panic in the C-suites and they perceive it as an existential race. It’s not important whether it actually is, but rather that’s how they feel. And they have such enormous amount of cash that they’re willing to play many risky bets at the same time. One of them being to hire/poach the hottest names.
It is not a question of exquisitely rare intellect, but rather the opportunity and funding/resources to prosper.
(And while there are certainly those who could have been the best who did not have the opportunity to succeed, or just didn't actually want to pursue it, I think usually this is way at the edges, i.e. removing the top would not make room for these people, because they're probably not even on anyone's radar at all, like the 'Einstein toiling in a field')
These AI researchers will probably have far more impact on society (good or bad I dont know) than the athletes, and the people who pay them (ie zuck et al) certainly thinks its worth paying them this much because they provide value.
When someone had a successful business model that offsets the incredible costs let me know, but it is all hypothetical.
But I counsel a different perspective: it's quite remunerative to be selling tulips when there's a mania on!
I think negative feelings are coming from more of a “why are they getting paid so much to build a machine that’s going to wreck everything” sort of angle, which I find understandable.
Will never understand the logic. They is literally better than an average senior dev, if he has been offered 250m package.
In contrast, a skilled football player lands somewhere between neutral and positive, as at the very least they entertain millions of people. And I'm saying that as someone who finds football painfully dull.
but I dont see news articles about athletes in such negativity, citing their young age etc.
The money here (in the AI realm) is coming a handful of oligarchs who are transparently trying to buy control of the future.
The difference between the two scenarios is... kinda obvious don't you think?
Are there 250 million AI specialists and the ones hired by Meta still come out on top?
Also much more people are affected by whatever AI is being developed/deployed than worldwide football viewers.
Top 5 football leagues have about 1.5billion monthly viewers. Top 5 AI companies (google, openai, meta etc) have far more monthly active users.
Meta can make 40 of these hires (over a number of years) and still be in a better place than feeling like they have to make a single $10B acquisition (if they could even make it at that point)
Microsoft Research had hundreds of big brains for decades that all worked independently and added little of value to the business.
To me it's obvious that these extremes create perverse incentives, so the people who will take those jobs won't amount to much. I m willing to bet that Meta's AI efforts are doomed from now on.
If you're going to offer an opinion contrary to the majority, you should at least have a convincing argument why.
I worry that those who became billionaires in the AI boom won't want the relative status of their wealth to become moot once AGI hits. Most likely this will come in the form of artificial barriers to using AI that, for ostensible safety reasons, makes it prohibitively difficult for all but the wealthiest or AGI-lab adjacent social circles to use.
This will cause a natural exacerbation of the existing wealth disparities, as if you have access to a smarter AI than everyone else, you can leverage your compute to be tactically superior in any domain with a reward.
All we can hope for is a general benevolence and popular consensus that avoids a runaway race to the bottom effect as a result of all this.
https://80000hours.org/2025/03/when-do-experts-expect-agi-to...
>One way to reduce selection effects is to look at a wider group of AI researchers than those working on AGI directly, including in academia. This is what Katja Grace did with a survey of thousands of recent AI publication authors.
>In 2022, they thought AI wouldn’t be able to write simple Python code until around 2027.
>In 2023, they reduced that to 2025, but AI could maybe already meet that condition in 2023 (and definitely by 2024).
>Most of their other estimates declined significantly between 2023 and 2022.
>The median estimate for achieving ‘high-level machine intelligence’ shortened by 13 years.
Basically every median timeline estimate has shrunk like clockwork every year. Back in 2021 people thought it wouldn't be until 2040 or so when AI models could look at a photo and give a human-level textual description of its contents. I think is reasonable to expect that the pace of "prediction error" won't change significantly since it's been on a straight downward trend over the past 4 years, and if it continues as such, AGI around 2028-2030 is a median estimate.
Claim doesn't check out; here's a YouTube video from Apple uploaded in 2021, explaining how to enable and use the iPhone feature to speak a high level human description of what the camera is pointed at: https://www.youtube.com/watch?v=UnoeaUpHKxY
That because experts aren't good at making predictions that non-experts must be BETTER at making predictions?
Let me ask you this: who do you think is going to make a less accurate prediction?
Assuming no one is accurate here, everybody is wrong. So the question is who is more or less accurate. Because there is a thing as "more accurate" right?
Go look at the referenced paper[0]. It is on page 3, last item in Figure 1, labeled "Simple Python code given spec and examples". That line is just after 2023 and goes to just after 2028. There's a dot representing the median opinion that's left of the vertical line half way between 2023 and 2028. Last I checked, 8-3 = 5, and 2025 < 2027.And just look at the line that follows
Something doesn't add up here... My guess, as someone who literally took that survey, is what's being referred to as "a simple program" has a different threshold.Here's the actual question from the survey
Is the answer to this question clear? Place your bets now!Here, I asked ChatGPT the question[1], it got it wrong. Yeah, I know it isn't very wrong, but it is still wrong. Here's an example of a correct solution[2] which shows the (at least) two missing lines. Can we get there with another iteration? Sure! But that's not what the question was asking.
I'm sure some people will say that GPT gave the right solution. So what that it ignored the case of a singular array and assumed all inputs are arrays. I didn't give it an example of a singular array or non-array inputs, but it did just assume. I mean leetcode questions pull out way more edge cases than I'm griping on here.
So maybe you're just cherry-picking. Maybe the author is just cherry-picking. Because their assertion that "AI could maybe already meet that condition in 2023" is not unobjectively true. It's not clear that this is true in 2025!
[0] https://arxiv.org/abs/2401.02843
[1] https://chatgpt.com/share/688ea18e-d51c-8013-afb5-fbc85db0da...
[2] https://www.geeksforgeeks.org/python/python-program-for-inse...
The graph you're looking at is of the 2023 survey, not the 2022 one
As for your question, I don't see what it proves. You described the desired conditions for an a sorting algorithm and chatGPT implemented a sorting algorithm. In the case of an array with one element, it bypasses the for loop automatically and just returns the array. It is reasonable for it to assume all inputs are arrays because your question told it that its requirements were to create a program that " turn any list of numbers into a foobar."
Of course I'm not any one of the researchers asked about their predictions in the survey, but I'm sure if you told them "a SOTA AI in 2025 produced working human readable code based on a list of specifications, and is only incorrect by a broad characterization of what counts as an edge case that would trip up a reasonable human coder on the first try", I'm sure the 2022 or 2023 respondents would say that it meets their criteria for their threshold.
I showed the claim was false
The author bases his argument on this and similar claims. Showing his claim is false says he's argument doesn't hold
I don't know of I'd really call a single item an "edge case" so much as generalization.But I do know I'd answer that question differently given your reframing.
No amount of describing pictures in natural language is AGI.
If you think an incremental improvement in transformers are what's needed for AGI, I see your angle. However, IMO, transformers haven't shown any evidence of that capability. I see no reason to believe that they'd develop that with a bit more compute or a bit more data.
So honestly, it doesn't seem like many of the predictions are that far off with this in context. That things sped up as funding did too? That was part of the prediction! The other big player here was falling cost of compute. There was pretty strong agreement that if compute was 50% more expensive that this would result in a decrease in progress by >50%.
I think uncontextualized, the predictions don't seem that inaccurate. They're reasonably close. Contextualized, they seem pretty accurate.
They are IC roles for the most part
I suppose those $100M are spread across years and potentially contingent upon achieving certain milestones.
With $250M they can easily buy their own competitive AI compute rig ...
Bear case: No, there's nothing you can do. These are exceptionally rare hires driven by FOMO at the peak of AI froth. If any of these engineers are successful at creating AGI/superintelligence within five years, then the market for human AI engineers will essentially vanish overnight. If they are NOT successful at creating AGI within five years, the ultra high-end market for human AI engineers will also vanish, because companies will no longer trust that talent is the key.
Bull case: Yes, you should go all in and rebrand as a self-proclaimed AI genius. Don't focus on commanding $250M in compensation (although 24, Matt Deitke has been doing AI/ML since high school). Instead, focus on optimizing or changing any random part of the transformer architecture and publishing an absolutely inscrutable paper about the results. Make a glossy startup page that makes some bold claims about how you'll utilize your research to change the game. If you're quick, you can ride the wave of FOMO and start leveling up. Although AGI will never happen, the opportunities will remain as we head into the "plateau of productivity."
These types of comp packages also seem designed to create a kind of indentured servitude for the researchers. Instead of forming their own rival companies that might actually compete with facebook, facebook is trying to foreclose that possibility. The researchers get the money, but they are also giving up autonomy. Personally, no amount of money would induce me to work for Zuckerberg.
Just a thought:
Assuming that Meta's AI is actually good. Could it rather be that having access to a massive amount of data does not bring that much of a business value (in this case particularly for training AIs)?
Evidence for my hypothesis: if you want to gain a deep knowledge about some complicated specific scientific topic, you typically don't want to read a lot of shallow texts tangentially related to this topic, but the few breakthrough papers and books of the smartest mind who moved the state of art in the respective area. Or some of the few survey monographs of also highly smart people who work in the respective area who have a vast overview about how these deep research breakthroughs fit into the grander scheme of things.
You can get that technical or scientific context for a lot less than $250 million per head.
Assuming a lab has 20 phds/postdocs and a few professors, call it 25 people per lab, and you're compute / equipment heavy, getting you up to an average of 1M per person per year in total fully loaded costs (including facilities overhead and GPUs and conferences and whatnot), then you're looking at 200 PhD researchers. Assuming that each PhD makes one contribution per 4 years, then that's 50 advances in the field per year from your lab. if only 10% are notable, that's 5 things you've gotten that people are going to get excited about in the field. You need 2% of these contributions to be groundbreaking to get a single major contribution per year.
So 250M for a single person is a lot, but if that person is really really good, then that may be only expensive and not insane.
Most would say, vibe-wise Llama 4 fell flat in face of Qwen & friends.
Media has this strange need for fully-grown responsible adults to be thought of as children. Not only for the amazing stories of "this (mid-30s career professional) kid did something", but also helpful to try and shirk responsibility.
Thinking about attempts to frame SBF as a wee smol bean kid in over his head while actively committing fraud.
You can always go back and finish your PhD later.
https://marvelcinematicuniverse.fandom.com/wiki/William_Gint...
For me the Meta storm of billions in hiring was enough to start selling any tech giant related stock.
It is about to crash, harder than ever.
The issue with high salaries is that there is a latent assumption that these people provide the multiples in additional value. That they are so smarter than everyone else.
This is simply not true, and will lead to a competitive disadvantage.
But feel free to prove me wrong - I am ammendable.
But I would expect them to be smart and have relevant experience that everyone else doesn’t have, and I expect the companies offering these salaries aren’t doing it for fun but because they believe their IP or ability to generate IP is very hard to come by, and it’s better to monopolize that talent than let competitors do so. If they could hire 10 people equally as good for 1/10 the price then they would do so. But I’m sure there’s also a large dose of gambling too; even in sports highly anticipated freshman drafts can turn into duds.
When OpenAI was making waves the first time, then Google launched their neutered incapable competitor, I thought it is “over” for Google because why would anyone use search anymore (apart from the 1% of use cases where it gives better results faster), and clearly they are incapable of building good new products anymore…
and now they are there with the best LLMs and they are at the top of the pack again.
Billions of dollars in the bank, great developers, good connections to politicians and institutions mean that you are hard to replace even if you fumble it a couple of times.
It is indeed; those people hired at those salaries are not going to "produce" more than the people hired at normal salaries.
Because what we have now is a "good enough" so getting a 10x better LLM isn't going to produce a 10x increase in revenue (nevermind profit).
The problem is not "We need a better LLM" or "We need cheaper/faster generation". It's "We don't know how to make money of this".
That doesn't require engineers who can creat the next generation SOTA in AI, that requires business people who can spot solutions which simply needs tokens.
We're sailing uncharted waters, all bets are off.
EUR:USD has been rising for a reason.
and then immediately bounce back to higher than it was before
I think the biggest confuser here is that there are really two games being played, the money game and the technology game. Investments in AI are going to be largely driven by speculation on their monetary outcome, not technological outcome. Whether or not the technology survives the Venture Capital Gauntlet, the investment bubble could still pop, and only the businesses that have real business models survive. Heaps of people lose their shirt to the tune of billions, yet we still have an AI powered future of some kind.
All this to say, you can both be certain AI is a valuable technology and also believe the economics around it right now are not founded in a clear reality. These are all bets on a future none of us can be sure of.
But thinking Tech Giants are going to crash is woefully ignorant of how the market works and indicates a clear wearing of blinders. And it's a common one among coders who feel the noose tightening and who are the types of people led by their own fear. And i find that when you mix that with arrogance, these three traits often correlate with older generations of software engineers who are poor at adapting to the new technology. The ones who constantly harp on how AI is full of mistakes and disregard that humans are as well. The ones who insist on writing even more than 70% of their own code rather than learning to guide new tools granularly. It's a take that nobody should entertain or respect.
As for your point on 'future none of us can be sure of.' I'll push back on that: It is not clear how AGI or ASI will come about, ie. what architecture will underpin it. However - it is absolutely clear that AI powered coding will continue to improve, and that algorithmic progress can and will be driven by AI coders, and that that will lead to ASI.
The only way to not believe that is to think there is a special sauce behind consciousness. And I tend to believe in scientific theory, not magic.
That is why there is so much VC. That is why tech giants are all racing. It isn't a bet. It is a race to a visible, clear goal of ASI that again, it takes blinders to not see.
So while AI is absolutely a bubble, this bubble will mark the transition to an entirely new economic system, society, world, etc. (and flip a coin on whether any of us survive it lol, but that's a whole separate conversation)
Based on what precedent?
Maybe I need to get one of these recruitment agents.
Mr. Deitke, who recently dropped out of a computer science Ph.D. program at the University of Washington, had moonlighted at a Seattle A.I. lab, the Allen Institute for Artificial Intelligence. There, he led the development of a project called Molmo, an A.I. chatbot that juggles images, sounds and text — the kind of system that Meta is trying to build.
Probably Zuck is trying to prop up his failed Metaverse with "AI". $250 million is nothing compared to what has already been sunk into that Spruce Goose.
Paying 250m to a genius to more deeply entrap user time and attention is going to look diabolical unless there are measurable user life improvement outcome measurements... if metas more slop addiction that 250m is a diabolical contract
https://nypost.com/2025/08/01/business/meta-pays-250m-to-lur...
After that, it's manual labor like the plebs or having enough savings to ~~last them the rest of their lives~~ invest and "earn" passive income by taking a portion of the value produced by people who still do actual work.
Some people are rightly pointing out that for quite a lot of things right now we probably already have AGI to a certain extent. Your average AI is way better than the average schmuck on the street in basically anything you can think of - maths, programming, writing poetry, world languages, music theory. Sure there are outliers where AI is not as good as a skilled practitioner in foo, but I think the AGI bar is about being "about as good as the average human" and not showing complete supremacy in every niche. So far the world has been disrupted sure, but not ended.
ASI of course is the next thing, but that's different.
I've gotten some great results out of LLM's, but thats often because the prompt was well crafted, and numerous iterations were performed based on my expertise.
You couldn't get that out of the LLM without that person most of the time.
To highlight the inverse: If someone truly has an "AGI" system (the acronym the goalposts have been moved-to) then it wouldn't matter who was wrangling it.
These models don't understand anything similar to reality and they can be confused by all sorts of things.
This can obviously be managed and people have achieved great things with them, including this IMO stuff, but the models are despite their capability very, very far from AGI. They've also got atrocious performance on things like IQ tests.
Yeah, that framing for LLMs is one of my pet-causes: It's document generation, some documents resemble stories with characters, and everything else (e.g. "chatting" with an LLM) is an illusion, albeit an impressive and sometimes-useful one.
Being able to generate a document where humans perceive plausible statements from Santa Claus does not mean Santa Claus now lives inside the electronic box, that flying sleighs are real, etc. The principle still holds even if the character is described as "an intelligent AI assistant named [Product Name]".
I think a possible scenario is that we see huge open source advances in training and inference efficiency that ends up making some of the mega-investments in AI infrastructure look silly.
What will probably ‘save’ the mega-spending is (unfortunately!) the application of AI to the Forever Wars for profit.
Whenever and however it comes, it’s going to be a bloodbath because we haven’t had a proper burst since 2008. I don’t count 2020.
AI is great and it's the future, and a bunch of people will probably eventually turn it into very powerful systems able to solve industrially important maths and software development problems, but that doesn't meant they'll make huge money from that.
Chances are good that while they’re competitive for sure, what they really have that landed them these positions is connections and the ability to market themselves well.
and what exactly did this "whiz" kid do that you and I didn’t
I assume you are going for “there are no more useful resources to acquire so those with all the resources overpay just to feel like they own those last few they don’t yet own”.
seems like governments will have a thing to say about who's able to run that AGI or not.
GPU's run on datacenters which exist in countries
Tokyo Professor and former Beijing Billionaire CEO Jack Ma, may disagree.
Granted, capitalism needs maintenance.
Externalities need to be consistently reflected, so capitalism can optimize real value creation, instead of profitable value destruction. It is a tool that can be very good at either.
Capitalism also needs to be protected from corrupted government by, ironically, shoring up the decentralization of power so critical for democracy, including protecting democracy from capitalism's big money.
(Democracy and capitalism complement each other, in good ways when both operating independently in terms of power, and supportively in terms of different roles. And, ironically, also complement each other when they each corrupt the other.)
The money and resources they have available is astronomical.
Instead they spend it on future proofing their profits.
What a sad world we have built.
But the promises turned into stock boosting lies; the environmental good into vote buying for climate change deniers, and space exploration into low earth cell-towers.
Those years were a long time ago for me. I’ve been arguing musk is a snake oil salesman since at least 2014. I lost friends over it at the time, people who were very heavily invested into musk, both financially and for some reason, emotionally.
Electric cars? That would be Martin Eberhard and Marc Tarpenning, Tesla’s actual founders. They created the Roadster and brought the vision. Musk came in with money, staged a hostile takeover, and then rewrote the company’s history to fit his inflated ego, like the sad little man he is. It's honestly cringe.
> cheap orbit rockets and with starlink internet almost everywhere possible on earth
Amazing what billions in government contracts and management smart enough to keep Elon out of the way can accomplish. SpaceX deserves praise; spinning it into a Elon is a genius narrative? Not so much.
As for the snake oil, just a few of Elon's greatest hits:
1. Hyperloop. Old idea's wrapped in new buzzwords. Never viable. He didn’t invent it, but he sure wants you to think he did, just like with Telsa.
2. FSD “next year” since forever. Still not here. Still being marketed like it's solved. And still charging like a wounded bull for it.
3. Robotaxis and appreciation hype. Musk literally claimed Teslas would go up in value and earn passive income as robotaxis. It doesnt get much more snake oil than this.
"We’re confident the cars will be worth more than what you pay for them today." – July 2019
"It’s financially insane to buy anything other than a Tesla." – April 2019
Absolutely laughable. Show me one consumer owned Tesla that’s worth more today than it was in 2019. I’ll wait. If you can't, we'll mark it down as snake oil bullshit.
4. Optimus. Elon hyped this like Tesla had cracked general purpose humanoid robotics out of nowhere, leapfrogging companies that have been grinding on this for decades. The first reveal? A guy in a suit dancing. The follow ups? Stiff prototypes doing slow, assisted movements and following that, remotely controlled animatronics and so on. Meanwhile, Musk is on stage talking about replacing human labor, reshaping the economy, and bots becoming more valuable than cars. None of it is remotely close. But it worked, stock popped, headlines flooded in, and the fantasy sold.
5. SolarCity. An overhyped, underdelivered money pit that Tesla had to bail out. Just another Elon tyre fire.
6. "Funding secured." Flat out lied about taking Tesla private at $420. SEC slapped him, but the stock soared. Mission accomplished.
And that’s just scratching the surface of his bullshit. It ignores all the other missed deadlines, quality issues, inflated delivery claims, etc etc etc. Here is some more of his bullshit, also I am sure not exhaustive:
https://elonmusk.today/
Yes, he’s had wins. But wins don’t erase the mountain of bullshit. Elon’s biggest output isn’t cars or rockets. It’s hype. His true skill is selling fantasy to retail investors and tech worshipping middled aged white dudes who still think he’s some genius messiah. Strip the PR away, and you’ve got a guy who overpromises, underdelivers, and never stops running his mouth.
I feel sorry for you. I guess we can share our feeling sorry for each other in common.
> You just write long BS for you bias.
Careful now, your bias is showing.
> Have a good day
Every day is a great day with the money i've made off TSLA lately :) Thanks Elon!
We should not listen to people who promise to make Mars safe for human habitation, until we have seen them make Oakland safe for human habitation. We should be skeptical of promises to revolutionize transportation from people who can't fix BART, or have never taken BART."
- https://idlewords.com/talks/sase_panel.htm
"Living standards in Poland in 2010 had more than doubled from 1990. In the same time period, in the United States, I’ve seen a whole lot of nothing. Despite fabulous technical progress, practically all of it pioneered in our country, there’s been a singular failure to connect our fabulous prosperity with the average person.
A study just out shows that for the median male worker in the United States, the highest lifetime wages came if you entered the workforce in 1967. That is astonishing. People born in 1942 had better lifetime earnings prospects than people entering the workforce today.
You can see this failure to connect with your own eyes even in a rich place like Silicon Valley. There are homeless encampments across the street from Facebook headquarters. California has a larger GDP than France, and at the same time has the highest poverty rate in America, adjusted for cost of living. Not only did the tech sector fail to build up the communities around it, but it’s left people worse off than before, by pricing them out of the places they grew up."
- https://idlewords.com/talks/notes_from_an_emergency.htm
Very aptly, the Manhattan Project or Space Race weren't aimed at the improvement of mankind per se. Motivation was a lot more specific and down to earth.
Well, no, the way forward is to just take away all that money and just spread it around.
https://soundcloud.com/adventurecapitalists/moving-mt-fuji
lyrics: https://genius.com/Adventure-capitalists-moving-mt-fuji-lyri...
but it's not the same reading the lyrics, you really need to hear his voice
Any left wing / socialist person on HN should be ecstatic - literally applauding with grins on their faces - that workers are extracting such sums out of the capitalist class. The hate for these salaries is mind boggling to me, and shows a lot of opposition to labor being paid what they are due is more about envy than class consciousness
I don't feel strongly about these salaries beyond them being an indication of deep dysfunction in the system. This is not healthy, for a market or for a society. No-one should be paid these amounts but I don't care about these developers because they don't run the system.
I've benefited from devs being paid well. Not that well. But same thing in concept.
I'm guessing not, but both the AI expert and the CEO are agents for the owner class: it is owners like Elon and Sam Altman that are deciding to pay these huge salaries and they are doing it for the same reason that corporate boards of directors pay CEOs huge salaries: namely, to help the owners accumulate more capital.
This gentleman now has an entirely different set of problems to everyone else. Do you think he will now go on to advocate for wealth equality, housing affordability, healthcare etc, or do you think he'll go buy some place nice away from his former problems and enjoy his (earned) compensation in peace?
A 1b $ anonymous software engineer is likely leading to 5000 more revenue than a 200k talented Ai engineer.
Personal anecdote time. One of the people named in the press as having turned down one of these hyper-offers used to work in an adjacent team, same "pod" maybe, whatever adjacent. That person is crazy smart, stands out even among elite glory days FAANG types. Anyways they left and when back on the market I was part of the lobby to get them back at any price, had to run it fairly high up the flagpole (might have been Sheryl who had to sign off, maybe it was Mark).
Went on to make it back for the company a hundred fold the first year. Clearly a good choice to "pay over market".
Now it's a little comical for it to be a billion or whatever, that person was part of a clique of people at that level and there's a lot of "brand" going into a price tag like that: the people out of our little set who did compilers or whatever instead of FAIR are just as good and what is called "AI" now is frankly not that differentiated (the person in question maintained as much back in the day).
But a luck and ruthlessness hire like Zuckerberg on bended knee to a legitimate monster hacker and still getting dissed? Applause. I had Claude write a greentext for the amusement of my chums. I recommend it kek.
Because if it's not funding the revolution (peaceful or otherwise) why exactly would a leftist applaud these salaries?
Marx hated the bourgeoisie (business owners, including petite-bourgeoisie AKA small business owners) and loved the proletariat - including the extremely skilled or well paid proletarians.
Marx also hated the lumpen-proletariet - AKA prostitutes, homeless, etc.
What I did or didn't read is alas occluded from you. The Masereel illustrated woodcuts on a recent edition of the manifesto are wonderful.
one would think that a talented academic/researcher getting a 1B salary would impress the socialist people but it doesn't because it was never about that. it was about bringing rich people down and not much else.
Edit oops, knowledge was outdated, it’s about 270.000.
Right now capital expenses are responsible for most of AI's economic impacts, as seen by the infrastructure spend contributing more to GDP than consumer spending this year.