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Nvidia's $20B antitrust loophole

ossa-ma.github.io

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Re: Nvidia's $20B antitrust loophole

#41

Post by krupan »

dangus wrote: post #32

The part I don’t fully understand is: could this non-acquisition eventually make the deal less than ideal for Nvidia? Is it really a given that GroqCloud is going to be sunset and the company will die? Couldn’t this company hire talent and continue to operate and maybe even innovate? Couldn’t Groq even hire back some employees from Nvidia? If any of them live in California there’s nothing stopping them and they have…

I agree, TFA seems to make a lot of assumptions. I kinda think they are correct just because they support the narrative that everyone involved is carefully taking care of their own, but it sure seems like it could go other ways.

Re: Nvidia's $20B antitrust loophole

#42

Post by ossa-ma »

krupan wrote: post #37

Read the article and where it talks about accelerated vesting of Groq shares for both the leadership team that goes to Nvidia and the regular employees that stay at Groq. Is that even guaranteed? It's not an IPO or an acquisition, so why would vesting schedules change?

Very interesting would love to read about this, do you have a link to the article?

Re: Nvidia's $20B antitrust loophole

#43

Post by kccqzy »

> The "non-exclusive" label is legal fiction. When you acquire all the IP and hire everyone who knows how to use it, exclusivity doesn't matter.

I have some doubts about this point. IP is IP, independent of the people who invented it. If a different hardware company were to also pay for a non-exclusive IP license, maybe it will just take a few months to catch up. It’s like inheriting a codebase written by another team, and there will be some pain and some time needed to integrate it.

In fact if GroqCloud wishes to survive, it should very well just attract licensees for its IP and collect license fees for the foreseeable future.

Re: Nvidia's $20B antitrust loophole

#44

Post by Havoc »

I wonder how much of the cap table knew

Matthew Berman (youtuber) mentioned he's invested in groq and found out same time as everyone else. Guessing he's a small/indirect investor but still telling

Re: Nvidia's $20B antitrust loophole

#45

Post by thayne »

jimnotgym wrote: post #30

IANAL, and am especially weak on US law, but I suspect this is only an antitrust loophole if the administration chooses not to act. Substance over form must apply? Pretty sure this wouldn't fly in European law.

Sure, but the US has a history of not acting.

If it was a normal acquisition, it would automatically trigger anti-trust investigations. Under the current administration, I think it is unlikely the acquisition would be blocked (although it probably should be...), but it would involve more bureaucracy, and would take longer.

Re: Nvidia's $20B antitrust loophole

#46

Post by spiantino »

I don't think you can treat owners of the same shares differently in the way this is suggesting. The VC shareholders and the employee shareholders are probably on equal footing and getting the same price. VCs will own preferred but I doubt that is enough to windfall them at the expense of the common shareholders.

So if VCs are getting paid a certain share price, employees with vested stock almost certainly are getting the same price. And probably employees with vested options can either exercise now or will just get paid the net during the transaction.

Yes, the company is probably doomed so people staying there are not doing well, but they also just got paid a 3x premium on their vested equity.

Re: Nvidia's $20B antitrust loophole

#47

Post by jmward01 »

georgeburdell wrote: post #25

This behavior is extremely damaging to the startup scene. Who would join a startup these days unless it’s run by a close friend or relative? At least in that case, the scorned junior employees would have social recourse.

It is definitely time to stop looking at equity as part of pay at a startup. The trend is extremely clear, startups aren't paying out to employees but the C suite gets internal raises and IPO is pushed to infinity. It is nice to have some paper laying around but that is all it is, paper. Go to a startup for a year. Get the experience, move and get a 20-50% pay increase and keep doing that every year and you will be way happier and financially healthier.

Re: Nvidia's $20B antitrust loophole

#48

Post by refibrillator »

ossa-ma wrote: post #21
vineethy wrote: post #14

I think it's important to note that there's nothing forbidding LPU style determinism from being used in training. They just didn't make that choice. Also tenstorrent could be a viable challenger in this space. It seems to me that their NoC and their chips could be mostly deterministic as long as you don't start adding in branches

You're right but my understanding is that Groq's LPU architecture makes it inference-only in practice. Like Groq's chips only have 230MB of SRAM per chip vs 80GB on an H100, training is memory hungry as you need to hold model weights + gradients + optimizer states + intermediate activations.

H100 has 80 GB of HBM3. There’s only like 37 MB of SRAM on a single chip.

Re: Nvidia's $20B antitrust loophole

#49

Post by tbrownaw »

jmward01 wrote: post #47
georgeburdell wrote: post #25

This behavior is extremely damaging to the startup scene. Who would join a startup these days unless it’s run by a close friend or relative? At least in that case, the scorned junior employees would have social recourse.

It is definitely time to stop looking at equity as part of pay at a startup. The trend is extremely clear, startups aren't paying out to employees but the C suite gets internal raises and IPO is pushed to infinity. It is nice to have some paper laying around but that is all it is, paper. Go to a startup for a year. Get the experience, move and get a 20-50% pay increase and keep doing that every year and you will be w…

I thought this was always the case? Hearing about examples certainly isn't new.

Re: Nvidia's $20B antitrust loophole

#50

Post by cubefox »

> Most production AI applications aren't running 405B models. They're running 7B-70B models that need low latency and high throughput.

Really? At least for LLMs, most actual usage is concentrated on huge SOTA models. 1 trillion parameters or more. And LLMs seem to be the lion's share of AI compute demand.

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