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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 a

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.

infecto 2y ago
Yes! I have had the exact same mental model. The biggest losers in this news are the groups building frontier models. They are the ones with huge valuations but if the optimizations becomes even close to true, its a massive threat to their business model. My feet are on the ground but I do still believe that the world does not comprehend how much compute it can use...as compute gets cheaper we will use more of it. Ignoring equity pricing, this benefits all other parties.
- sigmoid10 2y ago
  My big current conspiracy theory is that this negative sentiment toward Nvidia from Deepseek's release is spread by people who actually want to buy more stock at a cheaper price. Like, if you know anything about the topic, it's wild to assume that this will drive demand for GPUs anywhere but up. If Nvidia came out with a Jetson like product that can run the full 670B R1, they could make infinite money. And in the datacenter section, companies will stumble over each other to get the necessary hardware (which corresponds to a dozen H100s or so right now). Especially once HF comes out with their uncensored reproduction. There's so much opportunity to turn more compute into more money because of this, almost every company could theoretically benefit.
matco11 2y ago
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 happen in the long run?
- sghiassy 2y ago
  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 https://en.m.wikipedia.org/wiki/Knowledge_distillation So the takeaway is they have no moat
  - infecto 2y ago
    Beautiful and concise, much better than my word salad.
  - majewsky 2y ago
    Link without mobile UI: https://en.wikipedia.org/wiki/Knowledge_distillation https://en.wikipedia.org/wiki/Knowledge_distillation
- infecto 2y ago
  I believe in general the business model of building frontier models has not been fully baked out yet. Lets ignore the thought of AGI and just say models do continue to improve. In OpenAIs case they have raised lots of capital in the hopes of dominating the market. That capital pegged them at a valuation. Now you have a company with ~100 employees and supposedly a lot less capital come in a get close to OpenAIs current leading model. It has the potential to pop their balloon massively. 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.
- DebtDeflation 2y ago
  First of all, we need to just stop talking about AGI and Superintelligence. It's a total distraction from the actual value that has already been created by AI/ML over the years and will continue to be created. 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.

infecto 2y ago

Yes! I have had the exact same mental model. The biggest losers in this news are the groups building frontier models. They are the ones with huge valuations but if the optimizations becomes even close to true, its a massive threat to their business model. My feet are on the ground but I do still believe that the world does not comprehend how much compute it can use...as compute gets cheaper we will use more of it. Ignoring equity pricing, this benefits all other parties.

sigmoid10 2y ago
My big current conspiracy theory is that this negative sentiment toward Nvidia from Deepseek's release is spread by people who actually want to buy more stock at a cheaper price. Like, if you know anything about the topic, it's wild to assume that this will drive demand for GPUs anywhere but up. If Nvidia came out with a Jetson like product that can run the full 670B R1, they could make infinite money. And in the datacenter section, companies will stumble over each other to get the necessary hardware (which corresponds to a dozen H100s or so right now). Especially once HF comes out with their uncensored reproduction. There's so much opportunity to turn more compute into more money because of this, almost every company could theoretically benefit.

matco11 2y ago

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 happen in the long run?

sghiassy 2y ago
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 https://en.m.wikipedia.org/wiki/Knowledge_distillation So the takeaway is they have no moat
- infecto 2y ago
  Beautiful and concise, much better than my word salad.
- majewsky 2y ago
  Link without mobile UI: https://en.wikipedia.org/wiki/Knowledge_distillation https://en.wikipedia.org/wiki/Knowledge_distillation
infecto 2y ago
I believe in general the business model of building frontier models has not been fully baked out yet. Lets ignore the thought of AGI and just say models do continue to improve. In OpenAIs case they have raised lots of capital in the hopes of dominating the market. That capital pegged them at a valuation. Now you have a company with ~100 employees and supposedly a lot less capital come in a get close to OpenAIs current leading model. It has the potential to pop their balloon massively. 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.
DebtDeflation 2y ago
First of all, we need to just stop talking about AGI and Superintelligence. It's a total distraction from the actual value that has already been created by AI/ML over the years and will continue to be created. 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.