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Nvidia to buy assets from Groq for $20B cash

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Re: Nvidia to buy assets from Groq for $20B cash

#261

Post by bubblethink »

frozenport wrote: post #246
yousif_123123 wrote: post #115

Not good. This shouldn't be allowed. What would be better is if groq and cerebras combined, and maybe other companies invested in them to help them scale. Why would the major cloud providers not lobby against this? Usually antitrust is for consumers, but here I think companies like Microsoft and AWS would be the biggest beneficiaries of having more AI chip competition.

>> if groq and cerebras combined There isn't to be shared between the two techs, Groq's hardware is a like a railgun that installs all the weights into the optimal location before firing off an inference. Cerebras computer engineering more convention requiring the same data movement that GPUs struggle with optimizing. Suspect Groq is complementary/superior to nvidia's GPUs, while it is unclear what Cerebras brings ot…

They are both SRAM based solutions currently with the same benefits and pitfalls.

Re: Nvidia to buy assets from Groq for $20B cash

#262

Post by janderson215 »

biggc wrote: post #219
DivingForGold wrote: post #158

Earlier quoted context omitted.

Indeed, as justincormack comments: ”It is not structured as an outright acquisition to avoid US Gov't anti trust scrutiny, but effectively it probably is”. “Non-exclusive” ? Ummmm, yeah, right, sure. You can probably bet there is an private understanding that Groq will no longer offer it's “top of the line” best technology to competitors of Nvidia. Some may see this as a clever, “slight of the hand” attempt for Nvidi…

What generated this comment?

GPT1 Nano

Re: Nvidia to buy assets from Groq for $20B cash

#263

Post by tickerticker »

MobiusHorizons wrote: post #215
_fizz_buzz_ wrote: post #211

Earlier quoted context omitted.

> their main trick for model improvement is distilling the SOTA models Could you elaborate? How is this done and what does this mean?

I am by no means an expert, but I think it is a process that allows training LLMs from other LLMs without needing as much compute or nearly as much data as training from scratch. I think this was the thing deepseek pioneered. Don’t quote me on any of that though.

Yes. They bounced millions of queries off of ChatGPT to teach/form/train their DeepSeek model. This bot-like querying was the "distillation."

Re: Nvidia to buy assets from Groq for $20B cash

#264

Post by allovertheworld »

zamalek wrote: post #187
ilaksh wrote: post #179

Earlier quoted context omitted.

Yes, you are way off, because Groq doesn't make open source models. Groq makes innovative AI accelerator chips that are significantly faster than Nvidia's.

> Groq makes innovative AI accelerator chips that are significantly faster than Nvidia's. Yeah I'm disappointed by this, this is clearly to move them out of the market. Still, that leaves a vacuum for someone else to fill. I was extremely impressed by Groq last I messed about with it, the inference speed was bonkers.

more like now Nvidia wants to release their own ASIC to combat google

Re: Nvidia to buy assets from Groq for $20B cash

#265

Post by fragmede »

allovertheworld wrote: post #264
zamalek wrote: post #187

Earlier quoted context omitted.

> Groq makes innovative AI accelerator chips that are significantly faster than Nvidia's. Yeah I'm disappointed by this, this is clearly to move them out of the market. Still, that leaves a vacuum for someone else to fill. I was extremely impressed by Groq last I messed about with it, the inference speed was bonkers.

more like now Nvidia wants to release their own ASIC to combat google

Umm... no one tell them, okay?

Re: Nvidia to buy assets from Groq for $20B cash

#266

Post by Kiboneu »

impulser_ wrote: post #97

Are they buying them to try and slow down open source models and protect the massive amounts of money they make from OpenAI, Anthropic, Meta ect? It quite obvious that open source models are catching up to closed source models very fast they about 3-4 months behind right now, and yeah they are trained on Nvidia chips, but as the open source models become more usable, and closer to closed source models they will eat i…

>Are they buying them to try and slow down open source models

The opposite, I think.

Why do you think that local models are a direct threat to Nvidia?

Why would Nvidia let a few of their large customers have more leverage by not diversifying to consumers? Openai decided to eat into Nvidia's manufacturing supply by buying DRAM; that's concretely threatening behavior from one of Nvidia's larger customers.

If Groq sells technology that allows for local models to be used better, why would that /not/ be a profit source for Nvidia to incorporate? Nvidia owes a lot of their success on the consumer market. This is a pattern in the history of computer tech development. Intel forgot this. AMD knows this. See where everyone is now.

Besides, there are going to be more Groqs in the future. Is it worth spending ~20B for each of them to continue to choke-hold the consumer market? Nvidia can afford to look further.

It'd be a lot harder to assume good faith if Openai ended up buying Groq. Maybe Nvidia knows this.

Re: Nvidia to buy assets from Groq for $20B cash

#267

Post by frozenport »

dwa3592 wrote: post #57

This doesn't make much sense- In September, Groq was valued at $7B. How is it that in 4 months it is being bought for $20B? Can someone with better understanding dumb this down for me please?

Groq kept delivering so their valuation has effectively gone up.

A year ago it wasn't clear if they'd stay competitive but it seems they are.

Re: Nvidia to buy assets from Groq for $20B cash

#269

Post by tensor »

MobiusHorizons wrote: post #215
_fizz_buzz_ wrote: post #211

Earlier quoted context omitted.

> their main trick for model improvement is distilling the SOTA models Could you elaborate? How is this done and what does this mean?

I am by no means an expert, but I think it is a process that allows training LLMs from other LLMs without needing as much compute or nearly as much data as training from scratch. I think this was the thing deepseek pioneered. Don’t quote me on any of that though.

No, distillation is far older than deepseek. Deepseek was impressive because of algorithmic improvements that allowed them to train a model of that size with vastly less compute than anyone expected, even using distillation.

I also haven’t seen any hard data on how much they do use distillation like techniques. They for sure used a bunch of synthetic generated data to get better at reasoning, something that is now commonplace.

Re: Nvidia to buy assets from Groq for $20B cash

#270

Post by gessha »

gejose wrote: post #244
impulser_ wrote: post #127

Earlier quoted context omitted.

They don't need to catch up. They just need to be good enough and fast as fuck. Vast majority of useful tasks of LLMs has nothing to do with how smart they are. GPT-5 models have been the most useless models out of any model released this year despite being SOTA, and it because it slow as fuck.

> just need to be good enough and fast as fuck Hard disagree. There are very few scenarios where I'd pick speed (quantity) over intelligence (quality) for anything remotely to do with building systems.

As long as the faster tech is reliable and I understand its quirks, I can work with it.
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