What I find more interesting is how many people have left big orgs where they had major leadership roles, to become ICs at Anthropic.

Right, at this point its ~150 person cohorts, 4x a year. 105 is a drop in the bucket.

To reframe the silliness of this analysis, ~1% of the study population is Sam Altman founding OpenAI.

What if out of 13000 there are no other cases where close to 100+ worked at the same company

I wonder what the income distribution is like

I prefer that scenario to the one we had before where too many smart people were building out social networks and similar services trying to maximize ad impressions. We are still dealing with the consequences…

> With so much human capital and resources dedicated to developing and running LLMs all the other business, research opportunities aren’t being explored and invested in

It probably feels this way if you only see headlines like this, but the LLM companies and even extending into their data center buildouts are still only a part of the economy. Investment dollars get spread around far and wide. Investors can’t even get allocations in these companies if they want to because they’re so oversubscribed.

This headline and website are a good example. If you think being a YC founder is rare and reserved for the truly elite, you may not have seen the size of YC batches lately. The number of YC founders is in the tens of thousands. Showing a list of 100 of them who joined a couple big tech companies doesn’t mean anything by itself.

It’s on the order of 1% of YC founders. YC startups don’t work out all the time and their employees and founders go work for other startups. Barely worth noting, if not for a website making it look like a big deal.

I fear another related possibility. With *so* much money on the table, if this new industry shrinks or collapses, it is hard to believe that it will collapse same way dot-com did, and instead investors will seek to protect their capital who knows at what cost. Given the influence they have it is not hard to imagine the impact on policies, etc. I fear that tax payers are not the winners in either case, whether this industry grows or not.

> Whatever you think of AI for your own work, the fact that the entire economy is betting everything on it is really concerning. It’s not just the fact that it may not work well economically speaking and would end up with a market crash, or all the negative externalities from AI development, it’s also the opportunity cost we are paying.

It's worth pointing out that "entire economy is betting everything on [AI]" you're talking about here is in the economy in the "numbers go up sense" (e.g. the stock market). It's not the economy in the providing for the general well being sense (e.g. gives people jobs so they can get housing and food).

I don’t really buy the opportunity cost argument. The bets we are placing look EV-positive to me.

The 90th percentile upside is way, way higher than is priced into the current stocks, the 10th percentile looks to me like 2000 where a bunch of investors loose their shirts and then for the next few decades new companies boom on all the infrastructure that was built.

The “failure mode” for this tech is that we don’t advance much beyond Sol/Fable and the existing models just get cheaper. If there is an AI bust in hindsight it likely will look like the dotcom bust did, which is a small blip on the decades-scale GDP curve.

Opportunity cost arguments are more convincing when there’s some specific opportunity that you’re comparing against.

Otherwise, it’s sort of like saying that people will find a job doing something else, without any thought to what that something else would be. The jobs don’t create themselves.

Tech != the entire economy

I also think this is a huge problem in government. A lot of government services could be digitized via simple CRUD API/UIs and instead politicians talk about AI...

Moonshots are concerning until you consider the alternative.

AI is the one and only possibility for saving millions (likely billions) of lives from “old age”, cancers, Alzheimer’s, ALS… you name it.

It’s a big bet. The alternative is we all die anyway: sadly after a gradual decline at best or horribly after long undignified suffering at worst.

I’ll take the economic risk.

Researchers are increasingly using LLMs and other transformer based AI. My friend at a well known research institution asked Anthropic for access to their biology model (not sure if it's Mythos or some other sort of uncensored model) and recently made breakthroughs with it and other AI.

What metric are you using to say the entire economy is betting on it?

at the current pace, LLMs are the researchers

the end goal isnt to serve a chatbot to replace google or a coding agent to build crud

Sunk cost fallacy is already too established for anything else.

> the fact that the entire economy is betting everything on it

This is untrue. Spend is about 2% of GDP.

It’s not just the fact that it may not work well economically speaking

That's not going to happen. Everything is different now, and the only long-term losers will be those who continue to deny it. Even now we still see stupid analogies to parrots, calculators, toddlers, and so on, being advanced here of all places.

and would end up with a market crash

That might happen, because the first attempt a market makes to allocate funding and spending optimally is almost never on target. Great, it'll give the rest of us a chance to buy in.

I know Ed Zitron is a dirty word on HN most days but having recently read some of his (highly editorialized) work… it seems like he’s right and the numbers just aren’t making sense.

Combine that with the fact that “good enough” is a real thing and cheap Chinese models are either there or close depending on your use case and it’s hard to see how this ends well.

Not only that but with so much human capital and resources devoted to AI’s explicit goal of replacing human labor there are two outcomes: 1) it succeeds and we have a serious social problem on our hands with large swaths of the population out or a job, or 2) it fails and we have a very large market and economic crisis as the AI bubble collapses.

Maybe there’s a partial success future that isn’t those two, but I’m not hopeful. And I’d take the Ai bubble collapse over AI BigTech achieving its goals

This. the comments here talk as if YC is this secret cabal of upper elites when they're probably one of the least selective good accelerators

I’ve seen many people climb the SWE ladder or build a YC company (having done both myself), and trust me the founder route is not the most efficient. You only believe this because you didn’t see the 2 failed startups and 10 year journey grinding 80h weeks almost running out of cash a few times.

Jensen Huang himself says nobody in their right mind should start a company https://www.cnbc.com/amp/2024/05/11/jensen-huang-i-didnt-kno...

> Going the YC founder route is a much faster and more efficient way to secure a high tier than climbing the SWE ladder.

YC has funded over 5,000 companies. If you assume 2-3 co-founders per company, that's more than 10,000 to 15,000 people. The vast majority of these founders aren't producing "generational wealth" outcomes. There's no glamorization of the companies that shut down, the ones that are scraping by, and the ones that get their founders a normal job, but those are the far more likely outcomes, especially in the more recent spray-and-pray batches.

This is not even close to true. I work at a big tech company and we reject applications from YC founders every week. Most of them are broke with failing companies and would love a cushy mid-level engineering or management job at a faang. People are biased by the success of the top few founders but 99% of them have worse outcomes than the average corporate engineer.

This is a very hot take. Being a founder might confer you some career advantage [1] if you're one of the few to make it to series A and you grow a large team, but if you're like the vast majority of founders and never make it past seed (or realistically, to seed), your network is the alpha and omega of any subsequent job search. It's a bit like saying that being an NBA starter is a good way to get a job as a basketball coach.

Point being: don't start a startup if your goal is to get a job. Just get a job.

[1] Note that I'm not arguing about experience -- you can gain a lot of experience as a startup founder, but that experience is rarely directly marketable. Also, most startup founders are completely clueless when they start, so "a lot of experience" is a relative term.

People ask the same question of why YC funds yet another Uber for dogs or a button on the Touch Bar that cost $10/mo to help join a meeting faster.

They invest in people more than ideas, so you’ve got, at least in many cases, people with good pedigree and skills (age adjusted anyway) building on stupid ideas, but that are eminently employable.

Obviously there are other factors, I’m not really trying to defend anything but just point out that there are legit reasons why someone impressive enough to get into YC would also be impressive enough to get a good job. It’s not like it’s random founders off the street.

The top % of YC founders are legitimately quite talented, and high agency/entrepreneurial talent goes a long way in these companies, even if its not in deep infra or research

The actual AI part of AI startups are at constant risk of commoditization. Where the companies will survive or fail is how they manage to attract customers and lock them into their offerings so they can't move away to the next competitor.

Someone with experience running a startup that has no moat probably does have some relevant experience in that area.

They are hiring HPC experts too. It’s a small community and you just don’t hear about it.

These 100 people repress a tiny fraction of the people who work at these labs. And many of the people that work at the labs are building on top of the models, not building the models themselves.

I actually have experience with that stuff, “old school” deep learning and ML as well. Is that something worth joining the fray with I wonder? Or is it as you point out really only the richly connected “locals” that are recruited?

Maybe they're sales hires. Hiring influential folks gets them aligned with your business. It means you get their Roladex and tap into their network. They can poach good people. They can convince folks to buy into Claude. If they were able to fund Uber for dogs they could probably pitch AI just fine.

How many times have you heard a C-level person say "I was just meeting with a bunch of my C-level friends and they're all talking about how AI is the future. We should look into this Claude thing"?

It isn’t that long ago that AI was heavily gatekept and had some serious barriers of entry, due to its origins from academia.

I figure most of these are working on products, rather that deep frontier research.

> The question I have is why are these companies hiring these people and what does it say about their hiring practices and the amount of capital they’re poorly spending?

They are hiring for sales.

> I’m not surprised that these companies are well funded and hiring a lot of people. I’m surprised that they chose to hire the people who were previously making “Uber but for dogs” gimmick apps and not just hollowing out the HPC specialists from national labs.

Culture. The Uber for Dogs idiots will gulp down the kool-aid like they’re dying in the dessert.

Silicon Valley is not about having specialists or knowledge. It's about having connections and charisma.

Is this causing massive problems for us as a society? Of course, but no one seems to want to do anything about it, so here we are.

Probably because they want snake oil salesman

Why spend to resources to invent AGI when you can just gaslight the whole world by telling everyone that LLMs are already better than people?

Based on typical announcements, they only get acquired to serve their customers even better. The selfless unsung heroes of our time...

Do you have a source link for the >5000 companies?

the only high iq kid in this comment section basides me is right

According to the stats in this article https://www.ycombinator.com/investors, we can estimate 98.5% of the founders are not in OpenAI or Anthropic.

If Product-Market fit for small companies take 3-4 years and AI can streamroll you by coming from behind, it makes sense to join the big boys rather than trying to finetune your creation in the hope of making something big.

Bootstrapped companies make more sense now

It's a set of properties/attributes commonly referred to as "style" (generic, not the CSS one). Or call it look & feel.

So you're saying the site screams "Claude's style!" to you. Not too different from "I know a WordPress site when I see one".

The sepia-tinted color scheme and the way LLMs overuse rounded corner tiles to the absolute death is part of it. Really what it comes down to, is that these LLMs have a design vocabulary of like 15 traits. None of the websites they generate have every single trait, but they are composed of some subset of 10 such traits, so it's still overwhelmingly obvious the moment you open the page, even though each one is slightly different. Humans might use 1~5 of those traits, but they'll also be mixed in with a much wider set of traits with more individuality to them.

Most AI-generated sites have coopted the Inter font, and usually they go for a dark colour scheme, the rounded tiles, a container representing a macOS-styled terminal with code, and, the thing that annoys me the most, divs that fade is as you scroll.