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The impact of competition and DeepSeek on Nvidia

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Re: The impact of competition and DeepSeek on Nvidia

#281

The description of DeepSeek reminds me of my experience in networking in the late 80s - early 90s. Back then a really big motivator for Asynchronous Transfer Mode (ATM) and fiber-to-the-home was the promise of video on demand, which was a huge market in comparison to the Internet of the day. Just about all the work in this area ignored the potential of advanced video coding algorithms, and assumed that broadcast TV-q…

Doesn’t your point about video compression tech support Nvidia’s bull case? Better video compression led to an explosion in video consumption on the Internet, leading to much more revenue for companies like Comcast, Google, T-Mobile, Verizon, etc. More efficient LLMs lead to much more AI usage. Nvidia, TSMC, etc will benefit.

It improves TSMC' case.. Paying Nvidia would be like paying Cray for every smartphone that is faster than a supercomputer of old.

Re: The impact of competition and DeepSeek on Nvidia

#282

Earlier quoted context omitted.

Unique, ye, but isn't their method open? I read something about a group replicating a smaller variant of their main model.

Which brings the question, if LLMs are an asset of such strategic value, why did China allow the DeepSeek to be released? I see two possibilities here, either that the CCP is not that all-reaching as we think, or that the value of the technology isn't critical, and that the release was further cleared with the CCP and maybe even timed to come right after Trump's announcement of American AI supremacy.

It's early innings, and supporting the open source community could be viewed by the CCP as an effective way to undermine the US's lead in AI.

In a way, their strategy could be:

1) Let the US invest $1 trillion in R&D

2) Support the open source community such that their capability to replicate these models only marginally lags the private sector

3) When R&D costs are more manageable, lean in and play catch up

Re: The impact of competition and DeepSeek on Nvidia

#283

The description of DeepSeek reminds me of my experience in networking in the late 80s - early 90s. Back then a really big motivator for Asynchronous Transfer Mode (ATM) and fiber-to-the-home was the promise of video on demand, which was a huge market in comparison to the Internet of the day. Just about all the work in this area ignored the potential of advanced video coding algorithms, and assumed that broadcast TV-q…

I love algorithms as much the next guy, but not really.

DCT was developed in 1972 and has a compression ratio of 100:1.

H.264 compresses 2000:1.

And standard resolution (480p) is ~1/30th the resolution of 4k.

---

I.e. Standard resolution with DCT is smaller than 4k with H.264.

Even high-definition (720p) with DCT is only twice the bandwidth of 4k H.264.

Modern compression has allowed us to add a bunch more pixels, but it was hardly a requirement for internet video.

Re: The impact of competition and DeepSeek on Nvidia

#284
post #263

Earlier quoted context omitted.

Google's moat was significantly better results than the competition for about 2 decades. Your analogy is valid at this time, but proves the GP's point, not yours.

I think it's worth double clicking here. Why did Google have significantly better search results for a long time? 1) There was a data flywheel effect, wherein Google was able to improve search results by analyzing the vast amount of user activity on its site. 2) There were real economies of scale in managing the cost of data centers and servers 3) Their advertising business model benefited from network effects, where…

In theory, the more people use the product, the more OpenAI knows what they are asking about and what they do after the first result, the better it can align its model to deliver better results.

A similar dynamic occurred in the early days of search engines.

Re: The impact of competition and DeepSeek on Nvidia

#285
post #275

The most important part for me is: > DeepSeek is a tiny Chinese company that reportedly has under 200 employees. The story goes that they started out as a quant trading hedge fund similar to TwoSigma or RenTec, but after Xi Jinping cracked down on that space, they used their math and engineering chops to pivot into AI research. I guess now we have the answer to the question that countless people have already asked: W…

This is completely fake though. It was more like their founder decided to start a branch to do AI research. It was well planned, they bought significantly more GPUs than they can use for quant research even before they start to do anything AI.

There was a crack down on algorithmic trading, but it didn't had much impact and IMO someone higher up definitely does not want to kill these trading firms.

Re: The impact of competition and DeepSeek on Nvidia

#286

Earlier quoted context omitted.

OpenAI does not have a business model that is cashflow positive at this point and/or a product that gives them a significant leg up in the same moat sense Office/Teams might give to Microsoft.

Companies in the mobile era took a decade or more to become profitable. For example, Uber and Airbnb. Why do you expect OpenAI to become profitable after 3 years of chatgpt?

Nobody expects it but what we know for sure is that they have burnt billions of dollars. If other startups can get there spending millions, the fact is that openai won't ever be profitable.

And more important (for us), let the hiring frenzy start again :)

Re: The impact of competition and DeepSeek on Nvidia

#287
post #158

Great article. > Now, you still want to train the best model you can by cleverly leveraging as much compute as you can and as many trillion tokens of high quality training data as possible, but that's just the beginning of the story in this new world; now, you could easily use incredibly huge amounts of compute just to do inference from these models at a very high level of confidence or when trying to solve extremely…

Conversely, how much larger can you scale if frontier models only currently need 3 consumer computers? Imagine having 300. Could you build even better models? Is DeepSeek the right team to deliver that, or can OpenAI, Meta, HF, etc. adapt? Going to be an interesting few months on the market. I think OpenAI lost a LOT in the board fiasco. I am bullish on HF. I anticipate Meta will lose folks to brain drain in response…

>Imagine having 300.

Would it not be useful to have multiple independent AIs observing and interacting to build a model of the world? I'm thinking something roughly like the "councelors" in the Civilization games, giving defense/economic/cultural advice, but generalized over any goal-oriented scenario (and including one to take the "user" role). A group of AIs with specific roles interacting with each other seems like a good area to explore, especially now given the downward scalability of LLMs.

Re: The impact of competition and DeepSeek on Nvidia

#288

I'm rooting for DeepSeek (or any competitor) against OpenAI because I don't like Sam Altman. I'm confident in admitting it.

The enemy of your enemy is only temporarily your friend.

As a European I really don’t see the difference between US and Chinese tech right now - the last week from Trump has made me feel more threatened from the US than I ever have been by China (Greenland, living in a Nordic country with treaties to defend it).

I appreciate China has censorship, but the US is going that way too (recent “issues” for search terms). Might be different scales now, but I think it’ll happen. I don’t care as much if a Chinese company wins the LLM space than I did last year.

Re: The impact of competition and DeepSeek on Nvidia

#289

Earlier quoted context omitted.

There seem to be a 100 fold uptick in jingoists in the last 3-4 years which makes my head hurt but I think there is no consistent "underestimation" in academic circles? I think I have read articles about the up and coming Chinese STEM for like 20 years.

Yes, for people in academia the trend is clear, but it seems that WallStreet didn't believe this was possible. They assume that spending more money is all you need to dominate technology. Wrong! Technology is about human potential. If you have less money but bigger investment in people you'll win the technological race.

I think Wall Street is in for surprise as they have been profiting from liquidating the inefficiency of worker trust and loyalty for quite some time now.

It think they think American engineering excellence was due to neoliberal inginuenity visavi the USSR, not the engineers and the transfer of academic legacy from generation to generation.

Re: The impact of competition and DeepSeek on Nvidia

#290
post #207

Earlier quoted context omitted.

> If most of NVIDIAs moat is in being able to efficiently interconnect thousands of GPUs nah. it moat is CUDA and millions of devs using CUDA aka the ecosystem

And then some chineese startup create an amazing compiler that takes cuda and moves it to X (AMD, Intel, Asic) and we are back at square one. So far it seems that the best investment is in RAM producers. Unlike compute the ram requirements seem to be stubborn.

Don't forget that "CUDA" involves more than language constructs and programming paradigms.

With NVDA, you get tools to deploy at scale, maximize utilization, debug errors and perf issues, share HW between workflows, etc. These things are not cheap to develop.

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