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

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

#81

Post by the_af »

CuriouslyC wrote: post #49
GordonS wrote: post #35

Earlier quoted context omitted.

Highly unlikely. Despite the rampant anti-Chinese FUD that's so prevalent in the media (and, sadly, here on HN), China isn't really in the habit of invading other lands.

The plot twist here is that China doesn't view Taiwan as foreign.

But China also doesn't see war as the best path forward in Taiwan (they want to return it to the mainland, not lay waste to it). The grandparent comment is unfairly downvoted in my opinion, the fact remains modern China is far less likely to be involved in military campaigns than, say, the US.

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

#83

Post by croon »

villgax wrote: post #61
m4r1k wrote: 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…

100 times more chips for equivalent memory, sure.

Ironwood is 192GB, Blackwell is 96GB, right? Or am i missing something?

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

#84

Post by nostrademons »

thomascgalvin wrote: post #39
siliconc0w wrote: post #15

Google has always had great tech - their problem is the product or the perseverance, conviction, and taste needed to make things people want.

Their incentive structure doesn't lead to longevity. Nobody gets promoted for keeping a product alive, they get promoted for shipping something new. That's why we're on version 37 of whatever their chat client is called now. I think we can be reasonably sure that search, Gmail, and some flavor of AI will live on, but other than that, Google apps are basically end-of-life at launch.

It's telling that basically all of Google's successful projects were either acquisitions or were sponsored directly by the founders (or sometimes, were acquisitions that were directly sponsored by the founders). Those are the only situations where you are immune from the performance review & promotion process.

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

#85

Post by never_inline »

NaomiLehman wrote: post #72
1980phipsi wrote: post #60

> It is also important to note that, until recently, the GenAI industry’s focus has largely been on training workloads. In training workloads, CUDA is very important, but when it comes to inference, even reasoning inference, CUDA is not that important, so the chances of expanding the TPU footprint in inference are much higher than those in training (although TPUs do really well in training as well – Gemini 3 the prim…

inference is often a static, bounded problem solvable by generic compilers. training requires the mature ecosystem and numerical stability of cuda to handle mixed-precision operations. unless you rewrite the software from the ground up like Google but for most companies it's cheaper and faster to buy NVIDIA hardware

> static, bounded problem

What does it even mean in neural net context?

> numerical stability

also nice to expand a bit.

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

#86

Post by lazyfanatic42 »

jsheard wrote: post #28
dana321 wrote: post #11

That and the fact they can self-fund the whole AI venture and don't require outside investment.

That and they were harvesting data way before it was cool, and now that it is cool, they're in a privileged position since almost no-one can afford to block GoogleBot. They do voluntarily offer a way to signal that the data GoogleBot sees is not to be used for training, for now, and assuming you take them at their word, but AFAIK there is no way to stop them doing RAG on your content without destroying your SEO in th…

Wow, they really got folks by the short hairs if that is true...

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

#87

Post by bryanlarsen »

qwertox wrote: post #17

How high are the chances that as soon as China produces their own competitive TPU/GPU, they'll invade Taiwan in order to starve the West in regards to processing power, while at the same time getting an exclusive grip on the Taiwanese Fabs?

China will invade Taiwan when they start losing, not when they're increasingly winning.

As long as "tomorrow" is a better day to invade Taiwan than today is, China will wait for tomorrow.

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

#88

Post by mrbungie »

m4r1k wrote: 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…

It's fun when then you read last Nvidia tweet [1] suggesting that still their tech is better, based on pure vibes as anything in the (Gen)AI-era.

[1] https://x.com/nvidianewsroom/status/1993364210948936055

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

#89

Post by m4r1k »

villgax wrote: post #61
m4r1k wrote: 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…

100 times more chips for equivalent memory, sure.

Check the specs again. Per chip, TPU 7x has 192GB of HBM3e, whereas the NVIDIA B200 has 186GB.

While the B200 wins on raw FP8 throughput (~9000 vs 4614 TFLOPs), that makes sense given NVIDIA has optimized for the single-chip game for over 20 years. But the bottleneck here isn't the chip—it's the domain size.

NVIDIA's top-tier NVL72 tops out at an NVLink domain of 72 Blackwell GPUs. Meanwhile, Google is connecting 9216 chips at 9.6Tbps to deliver nearly 43 ExaFlops. NVIDIA has the ecosystem (CUDA, community, etc.), but until they can match that interconnect scale, they simply don't compete in this weight class.

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

#90

Post by tuhgdetzhh »

bfrog wrote: post #56
p-e-w wrote: post #54

Earlier quoted context omitted.

It’s true that architectures change, but they are built from common components. The most important of those is matrix multiplication, using a relatively small set of floating point data types. A device that accelerates those operations is, effectively, an ASIC for LLMs.

We used to call these things DSPs

What is the difference between a DSP and Asic? Is a GPU a DSP?
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