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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 sm
by BSOhealth 1y ago
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.
- AIPedant 1y agoA 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.
- brandall10 1y agoIt'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.
- jgalt212 1y agoIf you imagine hard enough, you can expect anything. e.g. Extraordinary Popular Delusions and the Madness of Crowds
- brandall10 1y agoSure, 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.
- AIPedant 1y agoThe 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.
- brandall10 1y agoWe’ve seen $T+ scale impacts from AI over the past few years. You can argue the distribution is hard to pin down (hence my note on risk), but let’s not pretend there’s zero precedent. If it turns out to be another winter at least it will have been a fucking blizzard.
- AIPedant 1y agoThe distribution is merely tricky to pin down when looking at overall AI spend, i.e. these "$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.
- brandall10 1y agoWhen 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.
- ignoramous 1y agoAnother major difference is, BigTech is bigger than these global sporting institutions. How much revenue does Google make in a day? £700m+.
- ojbyrne 1y agoMy 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.
- positron26 1y agoOOf. Trying awfully hard to have a bad day there eh?
- magic_man 1y agoTop 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?
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- stocksinsmocks 1y agoIt’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.
- layer8 1y agoThe 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.
- dbacar 1y agohow do you know they are nerds?
- gherkinnn 1y agoSounds vindictive. And yet. According to Forbes, the top 8 richest people have a tech background, most of whom are "nerdy" by some definition.
- hkt 1y agoThose are nerds who did founding rather than being an employee, though. Maybe that's the distinction they're trying to make?
- Waterluvian 1y agoI 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.
- moomin 1y agoIt’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.
- TrackerFF 1y agoFrontier 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.
- torginus 1y agoYeah, 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.
- cadamsdotcom 1y ago10% is an enormous amount. Let’s say 1%. Even if it’s 1% at the scale you’re talking that’s 1B to the company. So still worth it. Wild.
- diamond559 1y agoYeah 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.
- LightBug1 1y ago[flagged]
- bbminner 1y agoHm, 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.
- bbminner 1y agoA 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?
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- naveen99 1y agoMolmo was pretty slick
- parineum 1y ago> and started a startup 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.
- sbinnee 1y agoI 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.
- cm2187 1y agoWhat 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.
- storus 1y agoLLaMA 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.
- godelski 1y ago> 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).
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- perks_12 1y agoI 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.
- ulfw 1y agoF1 or soccer salaries are high because these are MARKETABLE people. The people themselves are a marketable brand. They're not high because of performance/results alone.
- user____name 1y agoRational inside a deeply olligopolistic and speculative market.