11–20 of 65 posts
This eliminates the need for more specialized models and the associated engineering and optimizations for their infrastructure needs.
Spending a lot (on capex or opex) certainly is not providing any kind of signaling benefit at this level. It's the opposite, because obviously every single financial analyst in the market is worried about the rapid increase in capex. The companies involved are cutting everything else to the bone to make sure they can still make those (necessary) investments without degrading their top-line numbers too much. Or in some cases actively working to hide the debt they're financing this with from their books.
Even if we imagined that the author's conspiracy theory were true, there would still be massive incentives for optimization because everyone is bottlenecked on compute despite expanding it as fast as is physically possible. Like, are we supposed to believe that nobody would run larger training runs if the compute was there? That they're intentionally choosing to be inefficient, and as a result having to rate-limit their paying customers? Of course not.
The reality is that any serious ML operation will have teams trying to make it more efficient, at all levels. If the author's services are not wanted, there are a few more obvious options than the outright moronic theory of intentional inefficiency. In this case most likely that their product is an on-edge speech to text model, which is not at all relevant to what is driving the capex.
Every part of this is nonsense. Spending a lot (on capex or opex) certainly is not providing any kind of signaling benefit at this level. It's the opposite, because obviously every single financial analyst in the market is worried about the rapid increase in capex. The companies involved are cutting everything else to the bone to make sure they can still make those (necessary) investments without degrading their top-…
It's not providing any benefit now but there's still signalling going on, and it absolutely provided benefit at the beginning of this cycle of economy-shattering fuckwittery.
>I see hundreds of billions of dollars being spent on hardware
>I don’t see are people waving large checks at ML infrastructure engineers like me
Which seemed like a valid question mark until you look at the github. I don't think we can conclude much of anything about the datacenter build out from that
If they optimize though - and this is coming at some point - local AI becomes possible, and their entire business case as a cloud monopoly evaporates. I think they know they're in a race between centralized control, and widespread use and control, and that is what is really driving this.
But if they succeed with agentic reasoning models (we are absolutly not there yet) then I think meritocracy will be replaced with assetocracy. The better the model, the more expensive it will be and the better the software will be.
I don’t worry about it myself, but I do worry for my kids. Im not even sure what to teach them anymore to have a shot at early retirement (and they keep raising the retirement age too).
Sounds like someone that got lucky in big picture (in ML during Alexnet era), but then unlucky in picking the sub-genre. >I see hundreds of billions of dollars being spent on hardware >I don’t see are people waving large checks at ML infrastructure engineers like me Which seemed like a valid question mark until you look at the github. I don't think we can conclude much of anything about the datacenter build out from…
The hyperscalers are playing the game hyperscalers are playing - and only them. Where do they expect to find talent then? If the logic is, you need to work at a hyperscaler to work at a hyperscaler, no wonder they won't find any talent. That would be like NASA only hiring astronauts to send to space if they had already experience being in space.
This is just not correct. Also nobody is making optimization startups because if you cared you’d have an in house team working on it.
But also, the companies are buying up this infrastructure because whoever controls the infrastructure also controls the industry in around 5 years time.
If they optimize though - and this is coming at some point - local AI becomes possible, and their entire business case as a cloud monopoly evaporates. I think they know they're in a race between centralized control, and widespread use and control, and that is what is really driving this.
Yes, if you see the LLM as a compressed dictionary of all available information. But if they succeed with agentic reasoning models (we are absolutly not there yet) then I think meritocracy will be replaced with assetocracy. The better the model, the more expensive it will be and the better the software will be. I don’t worry about it myself, but I do worry for my kids. Im not even sure what to teach them anymore to h…