71–80 of 197 posts
Earlier quoted context omitted.
Where can I buy a TPU v5 to install in my server? If the answer is “cloud”: that’s why NVidia is wiping the floor.
How many people are out there buying H100s for their personal use?
How is it that Google invented the TPU and Google Research came up with the paper on LLM and NVDA and AI startup companies have captured ~100% of the value
Earlier quoted context omitted.
Something similar happens on Wikipedia, where topics that use math inevitably get explained in the highest level math possible. It makes topics harder to understand than they need to be.
As a helpful Wiki editor just trying to make sure that we don't lead people astray, I've made some small changes to clarify your statement: In the virtual compendium of Wikipedia, an extensive repository of human knowledge, there is a discernible proclivity for the hermeneutics of mathematically-infused topics to be articulated through the prism of esoteric and sophisticated mathematical constructs, often employing a…
Earlier quoted context omitted.
Where can I buy a TPU v5 to install in my server? If the answer is “cloud”: that’s why NVidia is wiping the floor.
You probably can't even rent them from Google if you wanted to, in my experience.
Quote from the OP: "The TPU v1 uses a CISC (Complex Instruction Set Computer) design with around only about 20 instructions." chuckle CISC/RISC has gone from astute observation, to research program, to revolutionary technology, to marketing buzzwords....and finally to being just completely meaningless sounds. I suppose it's the terminological circle of life.
You’re seeming to imply the number of instructions available is what distinguishes CISC, but it never has been.
How is it that Google invented the TPU and Google Research came up with the paper on LLM and NVDA and AI startup companies have captured ~100% of the value
ChatGPT v Google is a far crazier history. Not only did Google invent Transformers, not only did Google open-source PaLM and Bert, but they even built chat tuned LLM chat bots and let employees talk with it. This isn’t a case where they were avoiding for disruption or protecting search - they genuinely didn’t see its potential. Worse, they got so much negative publicity over it that they considered it an AI safety issue to release. If that guy hadn’t gone to the press and claimed LaMDA was sentient than they may have entirely open sourced it like PaLM. This would likely mean that GPT-3 was open sourced and maybe never chat tuned either.
GPT-2 was freely available and OpenAI showed off GPT-3 freely as a parlor trick before ChatGPT came out. ChatGPT was originally the same - fun text generation as chat not a full product.
TLDR - Tensors probably didn’t have a lot of value until NVidia because scarce and they actively invented the original ChatGPT and “AI Safety” concerns caused them to lock it down.
How is it that Google invented the TPU and Google Research came up with the paper on LLM and NVDA and AI startup companies have captured ~100% of the value
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…
Earlier quoted context omitted.
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…
The answer is far weirder - they had a chat bot, and no one even discussed it in the context of search replacements. They didn’t want to release it because they just didn’t think it should be a product. Only after OpenAI actually disrupted search did they start releasing Gemini/Bard which takes advantage of search.
ChatGPT showed that people could still get value out of something that wasn’t perfect.
E.g. they had this in their labs: https://www.theguardian.com/technology/2022/jun/12/google-en... from July, 2022z
How is it that Google invented the TPU and Google Research came up with the paper on LLM and NVDA and AI startup companies have captured ~100% of the value
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…
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 occasionally says something offensive!) and being too complacent (too comfortable with incremental changes in Search, no appetite for launching an entirely new type of product / doing something really out there). There are many ways to monetize a chatbot, OpenAI for example is raking billions in subscription fees.