91–100 of 197 posts
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How many people are out there buying H100s for their personal use?
Probably many orders of magnitude greater than those buying TPU's for personal use...
Sigh...learning about TPUs a decade ago made me invest heavily in $GOOG for the coming AI revolution...got that one 100% wrong. +400% over 10 years isn't bad but I can't help but feel shortchanged seeing nvidia/etc
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It’s almost 15% per year, quite a lot.
yeah, but nvda is up like 500% in 2 years, so if you’re naive enough to think you can time the market, you’d have fomo over having invested in the “wrong” thing.
Sigh...learning about TPUs a decade ago made me invest heavily in $GOOG for the coming AI revolution...got that one 100% wrong. +400% over 10 years isn't bad but I can't help but feel shortchanged seeing nvidia/etc
I don't think anybody in 2014 believed that the performance of GPT-4/Claude Opus/... was 10 years away. 25 years maybe, 50 years probably, but not 10.
On the podcast interview now Groq CEO Jonathon Ross did[1] he talked about the creation of the original TPUs (which he built at Google). Apparently originally it was a FPGA he did in his 20% time because he sat near the team who was having inference speed issues. They got it working, then Jeff Dean did the math and the decided to do an ASIC. Now of course Google should spin off the TPU team as a separate company. It'…
This is wrong, both AMD and Intel (through Habana) have GPUs comparable to H100s in performance.
On the podcast interview now Groq CEO Jonathon Ross did[1] he talked about the creation of the original TPUs (which he built at Google). Apparently originally it was a FPGA he did in his 20% time because he sat near the team who was having inference speed issues. They got it working, then Jeff Dean did the math and the decided to do an ASIC. Now of course Google should spin off the TPU team as a separate company. It'…
The way I see, NVidia only has a few advantages ordered from most important to least: 1. Reserved fab space. 2. Highly integrated software. 3. Hardware architecture that exists today. 4. Customer relationships. but all of these aspects are weak in one way or another: For #1, fab space is tight, and NVidia can strangle its consumer GPU market if it means selling more AI chips at a higher price. This advantage is gone…
On the podcast interview now Groq CEO Jonathon Ross did[1] he talked about the creation of the original TPUs (which he built at Google). Apparently originally it was a FPGA he did in his 20% time because he sat near the team who was having inference speed issues. They got it working, then Jeff Dean did the math and the decided to do an ASIC. Now of course Google should spin off the TPU team as a separate company. It'…
The way I see, NVidia only has a few advantages ordered from most important to least: 1. Reserved fab space. 2. Highly integrated software. 3. Hardware architecture that exists today. 4. Customer relationships. but all of these aspects are weak in one way or another: For #1, fab space is tight, and NVidia can strangle its consumer GPU market if it means selling more AI chips at a higher price. This advantage is gone…
NVidia's biggest advantage is that AMD is unwilling to pay for top notch software engineers (and unwilling to pay the corresponding increase in hardware engineer salaries this would entail). If you check online you'll see NVidia pays both hardware and software engineers significantly more than AMD does. This is a cultural/management problem, which AMD's unlikely to overcome in the near-term future. Apple so far seems like the only other hardware company that doesn't underpay its engineers, but Apple's unlikely to release a discrete/stand-alone GPU any time soon.
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There's an old joke explanation about Xerox and PARC, about the difficulty of "pitching a 'paperless office' to a photocopier company". In Google's case, an example analogy would be pitching making something like ChatGPT widely available, when that would disrupt revenue from search engine paid placements, and from ads on sites that people wouldn't need to visit. (So maybe someone says, better to phase it in subtly, a…
This (innovator's dilemma / too afraid of disrupting your own ads business model) is the most common explanation folks are giving for this, but seems to be some sort of post-rationalization of why such a large company full of competent researchers/engineers would drop the ball this hard. My read (having seen some of this on the inside), is that it was a mix of being too worried about safety issues (OMG, the chatbot o…
What Google really needs to do is get into the 2nm EUV space and go sub 2nm. When they have the electro lithography (or whatever tech ASML has that prints on the chips) then you have something really dangerous. Probably a hardcore Google X moonshot type project. Or maybe they have 500mm sitting around to just buy one of the machines. If their tpu are really that good - maybe it is a good business - especially if they…
If Google has a compelling-enough business case, existing fabs will happily allocate space for their hardware. TPU is not remotely compelling enough.