151–160 of 426 posts
Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.
Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.
The economics of local AI just doesn’t make sense. A model like Opus is - supposedly - something like 5T parameters, which is likely something like 3TB of GPU memory. Local models never reach the % utilization that cloud providers have (80%+), and they’re always going to be much better than local models for this reason.
It’s not unreasonable to suppose that in 2 years time an opus 5 quality model will be etched into silicon for high performance local inference. Then you just upgrade your model every 2-3 years by upgrading your hardware.
Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.
> within a few years we will be running local models as good as today’s frontier models I seriously doubt it. Scaling is already strained (don't buy into the "exponential" hype). And, in any case, the competition will be against the frontier models that will exist in two years.
The big question I'd be asking if I was investing in one of the big players is if those changes are "it can do 99% instead of 97% of the tasks a user will throw at it" (at which point going local and taking back cost control/ownership makes a lot of sense, especially for companies) OR "it will fully replace a human with better output"?
I already don't need Opus for a lot of my tasks and choose instead faster/cheaper ones.
The former is a company that's gonna be trying to sell mainframes against the PC. The latter is a company that is in potentially huge demand, assuming the replaced humans end up with other ways of getting money to still be able to buy stuff in the first place. ;)
Earlier quoted context omitted.
I would readjust your convictions. We are only 2-4 years away from consumer grade immutable-weight ASICs.
We are discussing how rapid development has been, and now you want to freeze your model in silicon?
Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.
> within a few years we will be running local models as good as today’s frontier models with almost no cost burden Based on what? The RAM requirements alone are extraordinary. No, running large models on shared, dedicated hosted hardware at full utilization is going to be vastly more cost-efficient for the foreseeable future.
That is only true right now because hundreds of billions of dollars are being burned by these AI companies to try to win market share. If you paid what it actually cost, your comment would likely be very different.
Earlier quoted context omitted.
We are discussing how rapid development has been, and now you want to freeze your model in silicon?
Genuine question from a place of ignorance: what in the silicon pipeline makes it take 2-4years to produce chips with a new model on them? Curious what the process bottleneck is.
You might be interested in the tiny tape out project, which guides you through the process of getting your own design etched on silicon. If you only need larger features and not the next gen single digit nanometer stuff, you may not be so supply constrained.
Earlier quoted context omitted.
Compared to the inference prices for open models it’s highly unlikely OpenAI/Anthropic are not making decent amounts of money from inference. How many times bigger could Opus be than GLM or Kimi, it’s certainly not proportional to the price
it’s highly unlikely OpenAI/Anthropic are not making decent amounts of money from inference. Based on what ? Why are we all whispering about how profitable all this is? It is the absolute last thing these firms would keep secret.
Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.