911–920 of 1001 posts
Nvidia doesn't have a monopoly on GEMM and GEMV. There will be dozens of hardware vendors. It is TSMC that should be the most valuable company in the world.
By that logic TSMC is not the only one capable of 5nm. ASML should be the most valuable company in the world?
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In the long run (which in the AI world is probably ~1 year) this is very good for Nvidia, very good for the hyperscalers, and very good for anyone building AI applications. The only thing it's not good for is the idea that OpenAI and/or Anthropic will eventually become profitable companies with market caps that exceed Apple's by orders of magnitude. Oh no, anyway.
Can you guys explain what this would be bad for the OpenAI and Anthropic of the world? Wasn't the story always outlined to be we build better and better models, then we eventually get to AGI, AGI works on building better and better models even faster, and we eventually get to super AGI, which can work on building better and better models even faster... Isn't "super-optimization"(in the widest sense) what we expect to…
https://en.m.wikipedia.org/wiki/Knowledge_distillation
So the takeaway is they have no moat
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This is partially why Apple is the one that stands to gain more, and it showed. Their "small models, on device" approach can only be perfected with something like DeepSeek, and they're not exposed to NVIDIA pricing, nor have to prove investors that their approach is still valid.
Until AGI removes the need for iOS. Apple is not immune to AI disruption. The Rabbit R1 was a scam but the concept was the right approach. It was just 5 years too early. You don’t need an iPhone with AGI. You just need a 5G device with a screen, connected to an AGI.
no the fuck i don't need that. how do you know what i need?
NVIDIA sells shovels to the gold rush. One miner (Liang Wenfeng), who has previously purchased at least 10,000 A100 shovels... has a "side project" where they figured out how to dig really well with a shovel and shared their secrets. The gold rush, wether real or a bubble is still there! NVIDA will still sell every shovel they can manufacture, as soon as it is available in inventory. Fortune 100 companies will still…
We now have very expensive Nvidia shovels that use a lot of power but do very little improvement to the models.
Here’s a take I haven’t seen yet: If training and inference just got 40x more efficient, but OpenAI and co. still have the same compute resources, once they’ve baked in all the DeepSeek improvements, we’re about to find out very quickly whether 40x the compute delivers 40x the performance / output quality, or if output quality has ceased to be compute-bound.
> If training and inference just got 40x more efficient Did training and inference just get 40x more efficient, or just training? They trained a model with impressive outputs on a limited number of GPUs, but DeepSeek is still a big model that requires a lot of resources to run. Moreover, which costs more, training a model once or using it for inference across a hundred million people multiple times a day for a year?…
Earlier quoted context omitted.
In the long run (which in the AI world is probably ~1 year) this is very good for Nvidia, very good for the hyperscalers, and very good for anyone building AI applications. The only thing it's not good for is the idea that OpenAI and/or Anthropic will eventually become profitable companies with market caps that exceed Apple's by orders of magnitude. Oh no, anyway.
Can you guys explain what this would be bad for the OpenAI and Anthropic of the world? Wasn't the story always outlined to be we build better and better models, then we eventually get to AGI, AGI works on building better and better models even faster, and we eventually get to super AGI, which can work on building better and better models even faster... Isn't "super-optimization"(in the widest sense) what we expect to…
By releasing a lot of it opensource everyone has their hands on it. Opens the door to new companies.
Or a simple mental model, there has been this ability for third parties to get quite close to leading frontier models. The leading frontier models takes hundreds of millions of dollars and if someone is able to copy it within a years time for significantly less capital, its going to be hard game of cat and mouse.
DeepSeek proved knowledge distillation works very well and cheaply https://en.m.wikipedia.org/wiki/Knowledge_distillation
But they didn’t show how to build a new frontier model cheaply.
So, you still need massive investments to build new frontier models. But the bad part, is they can be replicated cheaply
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Can you guys explain what this would be bad for the OpenAI and Anthropic of the world? Wasn't the story always outlined to be we build better and better models, then we eventually get to AGI, AGI works on building better and better models even faster, and we eventually get to super AGI, which can work on building better and better models even faster... Isn't "super-optimization"(in the widest sense) what we expect to…
Because building a frontier model is expensive. But building a model as good as an existing frontier model is cheap (re: distillation). https://en.m.wikipedia.org/wiki/Knowledge_distillation So the takeaway is they have no moat
Earlier quoted context omitted.
In the long run (which in the AI world is probably ~1 year) this is very good for Nvidia, very good for the hyperscalers, and very good for anyone building AI applications. The only thing it's not good for is the idea that OpenAI and/or Anthropic will eventually become profitable companies with market caps that exceed Apple's by orders of magnitude. Oh no, anyway.
Can you guys explain what this would be bad for the OpenAI and Anthropic of the world? Wasn't the story always outlined to be we build better and better models, then we eventually get to AGI, AGI works on building better and better models even faster, and we eventually get to super AGI, which can work on building better and better models even faster... Isn't "super-optimization"(in the widest sense) what we expect to…
That said, you have to distinguish between "good for the field of AI, the AI industry overall, and users of AI" from "good for a couple of companies that want to be the sole provider of SOTA models and extract maximum value from everyone else to drive their own equity valuations to the moon". Deepseek is positive for the former and negative for the latter.
Earlier quoted context omitted.
IIUC they released a paper, it's partially algorithmic improvements partially good old low level optimization.
There's something to be said about the idea that instead of just dumping oceans of money into buying Nvidia cards they just...optimized what they had I'd say the wider industry could learn a thing or two, but as other commentors have joked. The line must go up
Reminds me of Japanese cars and the OPEC boycott in the 1970s...