> compensation packages that truly gifted AI researchers can make now

I guess it depends on your definition of "truly gifted" but, working in this space, I've found that there is very little correlation between comp and quality of AI research. There's absolutely some brilliant people working for big names and making serious money, there's also plenty of really talented people working for smaller startups doing incredible work but getting paid less, academics making very little, and even the occasional "hobbyist" making nothing and churning out great work while hiding behind an anime girl avatar.

OpenAI clearly has some talented people, but there's also a bunch of the typical "TC optimization" crowd in there these days. The fact that so many were willing to resign with sama if necessary appears largely because they were more concerned with losing their nice compensation packages than any of their obsession with doing top tier research.

Two people I knew recently left Google to join OpenAI. They were solid L5 engineers on the verge of being promoted to L6, and their TC is now $900k. And they are not even doing AI research, just general backend infra. You don't need to be gifted, just good. And of course I can't really fault them for joining a company for the purpose of optimizing TC.

> their TC is now $900k

As a community we should stop throwing numbers around like this when more than half of this number is speculative. You shouldn't be able to count it as "total compensation" unless you are compensated.

Word on town is OpenAI folks heavily selling shares in secondaries in 100s of millions.

The number is as real as someone else is willing to pay for them. Plenty of VCs willing to pay for it.

Word in town is [1] openai "plans" to let employees sell "some" equity through a "tender process" which ex-employees are excluded from; and also that openai can "claw back" vested equity, and has used the threat of doing so in the past to pressure people into signing sketchy legal documents.

[1] https://www.cnbc.com/2024/06/11/openai-insider-stock-sales-a...

I would definitely discount OpenAI equity compared to even other private AI labs (i.e. Anthropic) given the shenanigans, but they have in fact held 3 tender offers and former employees were not, as far as we know, excluded (though they may have been limited to selling $2m worth of equity, rather than $10m).

> Word on town is OpenAI folks heavily selling shares in secondaries in 100s of millions

OpenAI heavily restricts the selling of its "shares," which tends to come with management picking the winners and losers among its ESOs. Heavily, heavily discount an asset you cannot liquidate without someone's position, particularly if that person is your employer.

Did you mean permission, not position? I’m not sure I understand what someone’s position could mean.

Yes.

don’t comment if you don’t know what you’re talking about, they have tender offers

You have no idea what youre talking about

> their TC is now $900k.

Everyone knows that openai TC is heavily weighted by ~~RSUs~~ options that themselves are heavily weighted by hopes and dreams.

You mean PPUs or smoke and mirrors compensation. RSUs are actually worth something.

why are PPUs “smoke and mirrors” and RSUs “worth something”?

i suspect people commenting this don’t have a clue how PPU compensation actually works

> Note at offer time candidates do not know how many PPUs they will be receiving or how many exist in total. This is important because it’s not clear to candidates if they are receiving 1% or 0.001% of profits for instance. Even when giving options, some startups are often unclear or simply do not share the total number of outstanding shares. That said, this is generally considered bad practice and unfavorable for employees. Additionally, tender offers are not guaranteed to happen and the cadence may also not be known.

> PPUs also are restricted by a 2-year lock, meaning that if there’s a liquidation event, a new hire can’t sell their units within their first 2 years. Another key difference is that the growth is currently capped at 10x. Similar to their overall company structure, the PPUs are capped at a growth of 10 times the original value. So in the offer example above, the candidate received $2M worth of PPUs, which means that their capped amount they could sell them for would be $20M

> The most recent liquidation event we’re aware of happened during a tender offer earlier this year. It was during this event that some early employees were able to sell their profit participation units. It’s difficult to know how often these events happen and who is allowed to sell, though, as it’s on company discretion.

https://www.levels.fyi/blog/openai-compensation.html

Edit:

I’m realizing we had the exact same conversation a month ago. I’m guessing you have more insider information.

As an outsider it looks like smoke and mirrors.

Everything OpenAI does is about weights.

bro does their ceo even lift?

When I looked into it and talked to some hiring managers, the big names were offering cash comp similar to total comp for big tech, with stock (sometimes complicated arrangements that were not options or RSUs) on top of that. I’m talking $400k cash for a senior engineer with equity on top.

> big names

Big names where? Inside of openai? What does that even mean?

The only place you can get 400k cash base for senior is quantfi

> The only place you can get 400k cash base for senior is quantfi

confident yet wrong

not only can you get that much at AI companies, netflix will also pay that much all cash - and that’s fully public info

> not only can you get that much at AI companies

Please show not tell

> netflix will also pay that much all cash

Okay that's true

Netflix is just cash, no stock. That’s different from 400k stock + cash.

> The only place you can get 400k cash base for senior is quantfi

That statement is false for the reasons I said. I’m not sure why your point matters to what I’m saying

Because op’s usage of base implies base + stock. including a place where base = total comp is really misleading and is just being unnecessarily pedantic about terminology.

OP is correct that a base cash of 400k is truly rare if you’re talking about typical total comp packages where 50% is base and 50% is stock.

quantfi doesn’t pay stock at all usually so i disagree that it implies cash + stock

I don’t know what point you’re trying to make other than being super pedantic. This was a discussion about how OpenAI’s base of 400k is unique within the context of a TCO in the 800-900k range. It is. That quantfi and Netflix offer similar base because that’s also their TCO is a silly argument to make.

> This was a discussion about how OpenAI’s base of 400k is unique within the context of a TCO in the 800-900k range.

That's not how I interpret the conversation.

I see a claim that 900k is a BS number, a counterargument that many big AI companies will give you 400k of that in cash so the offers are in fact very hot, then a claim that only finance offers 400k cash, and a claim that netflix offers 400k cash.

I don't see anything that limits these comparisons to companies with specific TCOs.

Even if the use of the word "base" is intended to imply that there's some stock, it doesn't imply any particular amount of stock. But my reading is that the word "base" is there to say that stock can be added on top.

You're the one being pedantic when you insist that 400k cash is not a valid example of 400k cash base.

Notice how the person being replied to looked at the Netflix example and said "Okay that's true". They know what they meant a lot better than you do.

ok so the conversation starts out with 900k TCO with 400k in cash, a claim that that’s BS and then morphs into a discussion about a TCO of 400k all cash being an example of equivalent compensation to OpenAI packages?

Nobody said it was equivalent. The subdiscussion was about whether you can even get that much cash anywhere else, once TCO got pulled apart into cash and stock to be compared in more detail.

Again, the person that made the original claim about where you can get "400k cash base" accepted the Netflix example. Are you saying they're wrong about what they meant?

Amazon pays 400k cash lol. Many companies do

Up until 2 years ago you were extremely wrong and you're still wrong: https://www.bloomberg.com/news/articles/2022-02-07/amazon-is...

It's amazing to me how many people are willing to just say the first thing that comes to their head while knowing they can be fact-checked in a heartbeat.

Google itself is now filled with TC optimizing folks, just one level lower than the ones at Open AI.

Seems like you need to have been working at a place like Google too

the thing about mentioning compensation numbers on HN is you will get tons of pissy/ressentiment-y replies

I don't care about these. I care about the readers who might not have done job searching recently and might not know their worth in the market.

Half the advancements around Stable Diffusion (Controlnet etc.) came from internet randoms wanting better anime waifus

advancements around parameter efficient fine tuning came from internet randoms because big cos don’t care about PEFT

... Sort of?

HF is sort of big now. Stanford is well funded and they did PyReft.

HF is not very big, Stanford doesn’t have lots of compute.

Neither of these are even remotely big labs like what I’m discussing

HF has raised more than $400m. If that doesn't qualify them as "big", I don't know what does.

"...even the occasional "hobbyist" making nothing and churning out great work while hiding behind an anime girl avatar."

the people i often have the most respect for.

TC optimization being tail call optimization?

Could be sarcasm, but I'll engage in good faith: Total Compensation

You don't get to that level by thinking about code...

Nope, that's a misnomer, it's tail-call elimination. You can't call it an optimization if it's essential for proper functioning of the program.

(they mean total compensation)

Curie temperature

Definitely true of even normal software engineering; my experience has been the opposite of expectations, that TC-creep has infected the industry to an irreparable degree and the most talented people I've ever worked around or with are in boring, medium-sized enterprises in the midwest US or australia, you'll probably never hear of them, and every big tech company would absolutely love to hire them but just can't figure out the interview process to weed them apart from the TC grifters.

TC is actually totally uncorrelated with the quality of talent you can hire, beyond some low number that pretty much any funded startup could pay. Businesses hate to hear this, because money is easy to turn the dial up on; but most have no idea how to turn the dial up on what really matters to high talent individuals. Fortunately, I doubt Ilya will have any problem with that.

I find this hard to believe having worked in multiple enterprises and in the FAANG world.

In my anecdotal experience, I can only think of one or two examples of someone from the enterprise world who I would consider outstanding.

The overall quality of engineers is much higher at the FAANG companies.

I have also worked in multiple different sized companies, including FAANG, and multiple countries. My assessment is that FAANGs tend to select for generally intelligent people who can learn quickly and adapt to new situations easily but who nowadays tend to be passionless and indifferent to anything but money and prestige. Personally I think passion is the differentiator here, rather than talent, when it comes to doing a good job. Passion means caring about your work and its impact beyond what it means for your own career advancement. It means caring about building the best possible products where “best” is defined as delivering the most value for your users rather than the most value for the company. The question is whether big tech is unable to select for passion or whether there are simply not enough passionate people to hire when operating at FAANG scale. Most likely it’s the latter.

So I guess I agree with both you and the parent comment somewhat in that in general the bar is higher at FAANGs but at the same time I have multiple former colleagues from smaller companies who I consider to be excellent, passionate engineers but who cannot be lured to big tech by any amount of money or prestige (I’ve tried). While many passionless “arbitrary metric optimizers” happily join FAANGs and do whatever needs to be done to climb the ladder without a second thought.

I sort of agree and disagree. I wouldn't agree with the idea that most FAANG engineers are not passionate by nature about their work.

What I would say is that the bureaucracy and bullshit one has to deal with makes it hard to maintain that passion and that many end up as TC optimizers in the sense that they stay instead of working someplace better for less TC.

That said, I am not sure how many would make different choices. Many who join a FAANG company don't have the slightest inkling of what it will be like and once they realize that they are tiny cog in a giant machine it's hard to leave the TC and perks behind.

perfect sort of thing to say to get lots of upvotes, but absolutely false in my experience at both enterprise and bigtech

Academic compensation is different than what you’d find elsewhere on Hacker News. Likewise, academic performance is evaluated differently than what you’d expect as a software engineer. Ultimately, everyone cares about scientific impact so academic compensation relies on name and recognition far more than money. Personally, I care about the performance of the researchers (i.e., their publications), the institution’s larger research program (and their resources), the institution’s commitment to my research (e.g., fellowships and tenure). I want to do science for my entire career so I prioritize longevity rather than a quick buck.

I’ll add, the lack of compute resources was a far worse problem early in the deep learning research boom, but the market has adjusted and most researchers are able to be productive with existing compute infrastructure.

But wouldn't the focus on "safety first" sort of preclude them from giving their researchers the unfettered right to publish their work however and whenever they see fit? Isn't the idea to basically try to solve the problems in secret and only release things when they have high confidence in the safety properties?

If I were a researcher, I think I'd care more about ensuring that I get credit for any important theoretical discoveries I make. This is something that LeCun is constantly stressing and I think people underestimate this drive. Of course, there might be enough researchers today who are sufficiently scared of bad AI safety outcomes that they're willing to subordinate their own ego and professional drive to the "greater good" of society (at least in their own mind).

If you're working on superintelligence I don't think you'd be worried about not getting credit due to a lack of publications, of all things. If it works, it's the sort of thing that gets you in the history books.

Not sure about that. It might get Ilya in the history books, and maybe some of the other high profile people he recruits early on, but a junior researcher/developer who makes a high impact contribution could easily get overlooked. Whereas if that person can have their name as lead author on a published paper, it makes it much easier to measure individual contributions.

There is a human cognitive limit to the detail in which we can analyze and understand history.

This limit, just like our population count, will not outlast the singularity. I did the math a while back, and at the limit of available energy, the universe has comfortable room for something like 10^42 humans. Every single one of those humans will owe their existence to our civilization in general and the Superintelligence team in specific. There'll be enough fame to go around.

At the end game, a "non-safe" superinteligence seems easier to create, so like any other technology, some people will create it (even if just because they can't make it safe). And in a world with multiple superintelligent agents, how can the safe ones "win"? It seems like a safe AI is at inherent disadvantage for survival.

The current intelligences of the world (us) have organized their civilization in a way that the conforming members of society are the norm and criminals the outcasts. Certainly not a perfect system, but something along those lines for the most part.

I like to think AGIs will decide to do that too.

I disagree that civilization is organized along the lines of conforming and criminals. Rather, I would argue that the current intelligences of the world have primarily organized civilization in such a way that a small percentage of its members control the vast majority of all human resources, and the bottom 50% control almost nothing[0]

I would hope that AGI would prioritize humanity itself, but since it's likely to be created and/or controlled by a subset of that same very small percentage of humans, I'm not hopeful.

[0] https://en.wikipedia.org/wiki/Wealth_inequality_in_the_Unite...

It's a beautiful system, wherein "criminality" can be used to label and control any and all persons who disagree with the whim of the incumbent class.

Perhaps this isn't a system we should be trying to emulate with a technology that promises to free us of our current inefficiencies or miseries.

They well may, the problem is ensuring that humanity also survives.

The example from our environment suggests that the apex intelligences in the environment treat all other intelligent agents in only a few ways:

1. Pests to eliminate 2. Benign neglect 3. Workers 4. Pets 5. Food

That suggests that there are scenarios under which we survive. I'm not sure we'd like any of them, though "benign neglect" might be the best of a bad lot.

Our current meatware AGIs (corporations) are lawless as fuck and have effectively no ethics at all, which doesn’t bode well.

Considering the U.S. is likely to have a convicted felon as its next president, I don't agree with this characterization

> Perhaps they can find people who are ideologically driven

given the nature of their mission, this shouldn't be too terribly difficult; many gifted researchers do not go to the highest bidder

Generally, the mindset that makes the best engineers is an obsession with solving hard problems. Anecdotally, there's not a lot of overlap between the best engineers I know and the best paid engineers I know. The best engineers I know are too obsessed with solving problems to be sidetracked the salary game. The best paid engineers I know are great engineers, but the spend a large amount of time playing the salary game, bouncing between companies and are always doing the work that looks best on a resume, not the best work they know how to do.

My guess is they will work on a protocol to drive safety with the view that every material player will use / be regulated and required to use that could lead to a very robust business model

I assume that OpenAI and others will support this effort and the comp / training / etc and they will be very well positioned to offer comparable $$$ packages, leverage resources, etc

They will be able to pay their researchers the same way every other startup in the space is doing it – by raising an absurd amount of money.

Daniel Gross (with his partner Nat Friedman) invested $100M into Magic alone.

I don't think SSI will struggle to raise money.

I think they will easily find enough capable altruistic people for this mission.

I mean SBF was into Altruism - look how that turned out....

and that soured you on altruism as a concept??

i find the way people reason nowadays baffling

So what? He was a phony. And I'm not talking about the Effective Altruism movement.

Not really. He was into altruism insofar as it acted as moral licensing for him.

Not sure if spelling mistake.

Are you seriously asking how the most talented AI researcher of the last decade will be able to recruit other researchers? Ilya saw the potential of deep learning way before other machine learning academics.

Sorry, are you attributing all of deep learning research to Ilya? The most talented AI researcher of the last decade?

Not attributing all of it

The idea of multi layer neural networks goes back to the 60’s.

Last I checked the researcher salaries haven't even reached software engineer levels.

The kind of AI researchers being discussed here likely make an order of magnitude more than run of the mill "software engineers".

You're comparing top names with run of the mill engineers maybe, which isn't fair.

And maybe you need to discover talent rather than buy talent from the previous generation.

AI researchers at top firms make significantly more than software engineers at the same firms though (granted that the difference is likely not an order of magnitude in this case though).

Unless you know something I don’t, that’s not the case. It also makes sense, engineers are far more portable and scarcity isn’t an issue (many ML PhDs find engineering positions).

That is incredibly untrue and has been for years in the AI/ML space at many startups and at Amazon, Google, Facebook, etc. Good ML researchers have been making a good amount more for a while (source: I've hired both and been involved in leveling and pay discussions for years)

Great analysis, but you're missing two key factors IMO:

1. People who honestly think AGI is here aren't thinking about their careers in the typical sense at all. It's sorta ethical/"ideological", but it's mostly just practical.

2. People who honestly think AGI is here are fucking terrified right now, and were already treating Ilya as a spiritual center after Altman's coup (quite possibly an unearned title, but oh well, that's history for ya). A rallying cry like this -- so clearly aimed at the big picture instead of marketing they don't even need CSS -- will be seen as a do-or-die moment by many, I think. There's only so much of "general industry continues to go in direction experts recommend against; corporate consolidation continues!" headlines an ethical engineer can take before snapping and trying to take on Goliath, odds be damned