561–570 of 820 posts
Ed's posts always sing the same tune - AI spend is unsustainable. But why are the investors pouring into these megacorps allowing them to burn cash? What calculations are the investors making? I would like to see those projections, assumptions and backout plans.
Ed is an interesting character. His financial analysis of the AI industry makes logical sense to me (though I am not knowledgeable enough to actually know if it is correct .) However, he seems to be so angry at AI in general, that he misses the obvious areas where LLMs are actually changing the State of the Art. Coding seems to be one of the core use-cases for LLMs (as Simon Willison pointed out recently) and even if…
If inference becomes cheaper, it becomes cheaper for everyone.
Earlier quoted context omitted.
Uber is not the only company that's putting a per-developer limit on AI spending. I know this because I work for another one (and we have a significantly lower limit). You just heard about Uber first because they're high profile.
I didn't say they were the only company, I said they were the "first signal". The more signals the better! What cap did your company pick, and what geography / kind of industry are you in?
The cap is moderately above the high subscription tiers, and managements/the executives were clearly extremely concerned about how expensive it would be if we all or even mostly came close to hitting it. I heard that they originally wanted to go lower but the developers in the pilot program blew past their planned limit very quickly.
As for the company, its almost entirely B2B SaaS (I think it has some offerings that are used by consumers, but they're mostly/entirely paid for by another business on behalf of their customers), and they have developers all over the world, although the headquarters and biggest group of developers is in silicon valley (my office is in the midwest).
I have been a pretty consistent user of AI since 2022 (Instruct-GPT), so I don't have a bad opinion about the topic. However, I think the real problem now has become pretty obvious. We are hitting a reality wall, where we simply don't have enough ressources to feed the AI industry. We don't generate enough electrical power nor enough GPU or TPU. For the first time in computer science, the real issue here is the finit…
Earlier quoted context omitted.
> You have * zero * reason to believe inference is costly other than just vibes. If you go by data and intuitions - the margins are high. 1. What data? 2. Intuitions = vibes. Vibes are bad when used against you, but good when used in your favor. Come on :-)))
I have the data here and intuition https://simianwords.bearblog.dev/conclusive-proofs-that-llm-... But if you don't believe me, lets have a bet based on what the IPO filings show?
A better way to model this, since you seem interested is the following:
How much would it cost you to start such a service for, say, 10k users?
Any other internet service has had virtually Zero cost, $0. Google, Facebook, youtube, Wikipedia, you name it. They all went into the dumpster to pick up a thrown away desktop computer, and they could serve up towards 100k if not a million users.
How much would it cost you to serve, say, 10k simultaneous users with a SOTA model? And if you wanted to go cash positive after a year, how much would each user have to pay?
I have been a pretty consistent user of AI since 2022 (Instruct-GPT), so I don't have a bad opinion about the topic. However, I think the real problem now has become pretty obvious. We are hitting a reality wall, where we simply don't have enough ressources to feed the AI industry. We don't generate enough electrical power nor enough GPU or TPU. For the first time in computer science, the real issue here is the finit…
The best solution, from an efficiency point of view, is to use smaller models on datacenters, requiring much less of them.
Earlier quoted context omitted.
> He would begin somewhere–statistics on AI demand, say–and then walk the calculations carefully over to the next step–maybe revenue needed for profitability by AI companies–and you could follow the argument. That's exactly what the first (titled) section does?
Haha thought you were referring to the upsell at the start asking to subscribe to the newsletter for $70 / year. But yes it does call out the unprecedented amount of money getting dumped into AI. What turned me off though was this paragraph: > This is a hysterical era perpetuated by liars, cowards, imbeciles, craven boosters and the easily-fooled. Those excited about generative AI are either the victim or the perpetr…
Where are those numbers from?