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TPUs vs. GPUs and why Google is positioned to win AI race in the long term

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311–320 of 328 posts

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#311
post #41

Google's real moat isn't the TPU silicon itself—it's not about cooling, individual performance, or hyper-specialization—but rather the massive parallel scale enabled by their OCS interconnects. To quote The Next Platform: "An Ironwood cluster linked with Google’s absolutely unique optical circuit switch interconnect can bring to bear 9,216 Ironwood TPUs with a combined 1.77 PB of HBM memory... This makes a rackscale…

Also, Google owns the entire vertical stack, which is what most people need. It can provide an entire spectrum of AI services far cheaper, at scale (and still profitable) via its cloud. Not every company needs to buy the hardware and build models, etc., etc.; what most companies need is an app store of AI offerings they can leverage. Google can offer this with a healthy profit margin, while others will eventually run…

when chatgpt came, I thought google didn't have the leadership and team spirit to recover, seems like i was very wrong

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#312

Earlier quoted context omitted.

It was only brought in-house after the $5,000,000,000,000 self-dealing AI chip venture failed to launch.

Nvidia?

Sam Altman attempted to raise $5Tn for an AI-chip startup

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#313

Earlier quoted context omitted.

I feel like this is more like the console/PC debate in the 90s. Consoles like the SNES had dedicated fixed function graphics hardware with weaker general specs, but with the special HW they could perform as well as a much more expensive PC - but as devs made more and more varied and clever games, that fixed function hardware couldn't support it and the PC became the superior choice.

I guess that's why Nintendo stopped making game consoles and Sony's PlayStation never went anywhere.

Consoles still exist, but they have evolved to use PC hardware.

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#314
post #41

Google's real moat isn't the TPU silicon itself—it's not about cooling, individual performance, or hyper-specialization—but rather the massive parallel scale enabled by their OCS interconnects. To quote The Next Platform: "An Ironwood cluster linked with Google’s absolutely unique optical circuit switch interconnect can bring to bear 9,216 Ironwood TPUs with a combined 1.77 PB of HBM memory... This makes a rackscale…

[deleted]

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#316
post #215

I always enjoy being wrong and I was very wrong in my predictions about Google : I thought they should theoretically win, but I was also very confident they couldn't possibly turn their execution ship around to actually pull together a coherent competitor to OpenAI. But they do seem to have done that and it's very impressive. If they do continue to execute, I can't see anybody stopping them dominating and I would be…

> because of the lack of any clear or reasonable statement or guidelines on how they use your data. They’ve been very clear, in my opinion: https://cloud.google.com/gemini/docs/discover/data-governanc... I suppose there will always be the people who refuse to trust them or choose to believe they’re secretly doing something different. However I’m not sure what you’re referring to by saying they haven’t said anything a…

This echos my experience with GCP and Google in general.

If you’re a business/enterprise, you get a different ToS that very clearly states that your data is yours.

If you use the free/consumer options, that’s where they are vague or direct about vacuuming up data.

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#317
post #215

I always enjoy being wrong and I was very wrong in my predictions about Google : I thought they should theoretically win, but I was also very confident they couldn't possibly turn their execution ship around to actually pull together a coherent competitor to OpenAI. But they do seem to have done that and it's very impressive. If they do continue to execute, I can't see anybody stopping them dominating and I would be…

I don’t know if Google will win but the message they sent is that Nvidia will not: if Google can release the best model without using their own chips instead of GPUs, and save money in the process, then others (Microsoft, Amazon, etc.) will do it too sooner or later.

That is the opposite of good. If only big companies can afford bespoke hardware, they literally become a monopoly, At home LLMs and other usages become either prohibitively expensive in purchase and running cost or you have to deal with a low quality model. Just admit that it's environmentally fucked and not open in any sense. This is not something that the community at large should strive for.

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#318

Earlier quoted context omitted.

Sam Altman attempted to raise $5Tn for an AI-chip startup

Link? I only know of Rain and they raised <<$1 billion IIRC

Note that I said "attempted". https://www.wsj.com/tech/ai/sam-altman-seeks-trillions-of-do...

Re: TPUs vs. GPUs and why Google is positioned to win AI race in the long term

#319
If an outsider is ever allowed to have a simplified mental model of why nvidia was unbeatable, here's mine:

- they were way ahead, and they didn't make any big mistakes

- they weren't waiting for others to catch up. They were aggressively improving

- memory bandwidth is almost always the bottleneck. Hence systolic array is "overrated". Furthermore, interconnect is the new bottleneck now

- cuda offers the most flexibility in the world of ever changing model requirements

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