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Nvidia’s $589B DeepSeek rout

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Re: Nvidia’s $589B DeepSeek rout

#901
post #785

Earlier quoted context omitted.

With the crowdstrike outage earlier last year it was incredible how many hidden security and kernel "experts" came out crawling from the woodwork, questioning why anything needs to run in the kernel and predicting the company's demise.

They were correct that there is no need for it to run in the kernel. They were incorrect in thinking this would affect the company's future, because of course the sales of their product have nothing to do with its technical merit.

I think you've got it half correct: sales absolutely does have to do with the technical merit. Their platform works, it's just folks overestimated the impact of a single critical defect.

Nobody would pay crowdstrikes prices if it didn't stop attacks, or improve your detection chances (and I can assure you, it does, better than most platforms)

Re: Nvidia’s $589B DeepSeek rout

#902

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.

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 happen in the long run?

Re: Nvidia’s $589B DeepSeek rout

#903

Earlier quoted context omitted.

With the crowdstrike outage earlier last year it was incredible how many hidden security and kernel "experts" came out crawling from the woodwork, questioning why anything needs to run in the kernel and predicting the company's demise.

the experts were correct. in 2024 there are now OS APIs that provide the same observability and control with much less risk involved.

And yet crowdstrike's stock price is still 28% up on where it was 12 month ago, 46% up on 6 months ago after their crash.

Sibling is right, that type of product is nothing to do with actually preventing problems, its to do with outsourcing personal risk. Same as SAAS. Nobody got fired when office 365 was down for the second day in a year, but have a 5 minute outage on your on-prem kit after 5 years and there's nasty questions to answer.

Re: Nvidia’s $589B DeepSeek rout

#904

Earlier quoted context omitted.

Systems, it’s all about systems thinking. It is absolutely true that people in tech are often optimistic and/or delusional about the other expertise at their command. But it’s not like the basic assumption here is completely crazy. Being a surgeon might require thinking about a few interacting systems, but mostly the number and nature of those systems involved stay the same. Talented programmers without even formal t…

But even if we just look at the examples given by the parent, most of them are not about systems or models at all. Epidemiology and politics concern practical matters of life. In such matters, life experience will always trump abstract knowledge.

Epidemiology and politics are pretty much the poster children of systems[0], next to their eldest sibling, economics. Life and experience may trump abstract knowledge dumbly applied, but alone it won't let you reason at larger scales (not that you could collect any actual experience on e.g. pandemics to fuel your intuition here anyway).

A part of learning how to model things as systems is understanding your model doesn't include all the components that affect the system - but it also means learning how to quantify those effects, or at least to estimate upper bounds on their sizes. It's knowing which effects average out at scale (like e.g. free will mostly does, and quite quickly), and which effects can't possibly be strong enough to influence outcome and thus can be excluded, and then to keep track of those that could occasionally spike.

Mathematics and systems-related fields downstream of it provide us with plenty of tools to correctly handle and reason about uncertainty, errors, and even "unknown unknowns". Yes, you can (and should) model your own ignorance as part of the system model.

--

[0] - In the most blatant example of this, around February 2020, i.e. in the early days of the COVID-19 pandemic going global, you could quite accurately predict the daily infection stats a week or two ahead by just drawing up an exponential function in Excel and lining it up with the already reported numbers. This relationship held pretty well until governments started messing with numbers and then lockdowns started. This was a simple case because at that stage, the exponential component was overwhelmingly stronger than any more nuanced factor - but identifying which parts of a phenomenon dominate and describing their dynamics is precisely the what learning about systems lets you do.

Re: Nvidia’s $589B DeepSeek rout

#905
post #431

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…

Is AI expanding horizontally or vertically? My understanding is that smarter models dominate over hordes of dumber ones

Re: Nvidia’s $589B DeepSeek rout

#906
1) to address frontier model company stock valuations (openai for instance): deepseek is creating stuff months after frontier companies. In the AI arms race it might make sense to burn billions to be 3 months ahead (think about how you use that superintelligence to prevent anyone else acquiring it)

2) to address Nvidia valuation: there is no cap to demand on intelligence (or, we're not close). People will never be satisfied with the intelligence achieved and just stop asking for more. So Nvidia will still sell the hardware as the demand side is uncapped.

Unrelated note that I was considering and would like an opinion on: Nvidia is the software play in AI, and TSMC the hardware play. Nvidia has competitors like broadcom/AMD/TPUs but beats out on software. TSMC will be frontier on manufacturing everyone's hardware.

Re: Nvidia’s $589B DeepSeek rout

#908
post #906

1) to address frontier model company stock valuations (openai for instance): deepseek is creating stuff months after frontier companies. In the AI arms race it might make sense to burn billions to be 3 months ahead (think about how you use that superintelligence to prevent anyone else acquiring it) 2) to address Nvidia valuation: there is no cap to demand on intelligence (or, we're not close). People will never be sa…

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Re: Nvidia’s $589B DeepSeek rout

#909
post #868

Earlier quoted context omitted.

It goes up at least until LLMs match humans - ie until an LLM can write Windows

I want the LLM to decide not to do anything, or write a new OS. Whenever I prompt: "Do not do anything" It always does .

> Whenever I prompt: "Do not do anything" It always does .

Yep. A lot of times, the responses I get remind me of Simone in Ferris Bueller's Day Off: https://www.youtube.com/watch?v=swBtLPWeKbU

If you end up making a new model, please teach it that less is more and call it "LAIconic".

Re: Nvidia’s $589B DeepSeek rout

#910
post #605

Earlier quoted context omitted.

As a great example of this read Paul Graham’s essays that aren’t anout his core expertise.

I think that’s unfair unless you give specific examples and clear evidence he’s wrong. I disagree with PG on economics and politics, but much of his writing on that is subjective.

He recently said that evil people can’t survive long as founders of tech companies because they need smart people to work for them and smart people can work anywhere. There are lots of other examples. Especially read his recent tweets/essays that aren’t about his area of expertise.
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