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Our eighth generation TPUs: two chips for the agentic era

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Re: Our eighth generation TPUs: two chips for the agentic era

#61

Post by someguyiguess »

jmyeet wrote: post #56

In recent discussions about Tim Apple [sic] moving on there was a discussion about whether Apple flopped on AI, which is my opinion. Of course you had the false dichotomy of doing nothing or burning money faster than the US military like OpenAI does. IMHO that happy medium is Google. Not having to pay the NVidia tax will likely be a huge competitive advantage. And nobody builds data centers as cost-effectively as Goo…

Apple has not flopped on AI as you say. They are just focused on privacy and are likely waiting for the time when local models become efficient enough to run on iPhones (which is quickly becoming a reality).

Google could probably train models for orders of magnitude less money as you say, but they aren't. They are not capable of creating high quality models like OpenAI and Anthropic are. Their company is just too disorganized and chaotic.

Anecdotally, I don't know a single person who uses Gemini on purpose.

Re: Our eighth generation TPUs: two chips for the agentic era

#62

Post by ckcheng »

someguyiguess wrote: post #54
harrall wrote: post #49

Earlier quoted context omitted.

Google invented the AI architecture that Anthropic and OpenAI based their entire companies on? Based off years of research at Google. Of course they should have to fight with the inventors of the technology they’re using.

> Google invented the AI architecture that Anthropic and OpenAI based their entire companies on Source?

Unless you don’t think Attention Is All You Need?

https://en.wikipedia.org/wiki/Attention_Is_All_You_Need

Re: Our eighth generation TPUs: two chips for the agentic era

#63

Post by IncreasePosts »

someguyiguess wrote: post #54
harrall wrote: post #49

Earlier quoted context omitted.

Google invented the AI architecture that Anthropic and OpenAI based their entire companies on? Based off years of research at Google. Of course they should have to fight with the inventors of the technology they’re using.

> Google invented the AI architecture that Anthropic and OpenAI based their entire companies on Source?

"Attention Is All You Need" was a paper by a bunch of Google researchers

Re: Our eighth generation TPUs: two chips for the agentic era

#64

Post by himata4113 »

I already felt that gemini 3 proved what is possible if you train a model for efficiency. If I had to guess the pro and flash variants are 5x to 10x smaller than opus and gpt-5 class models.

They produce drastically lower amount of tokens to solve a problem, but they haven't seem to have put enough effort into refinining their reasoning and execution as they produce broken toolcalls and generally struggle with 'agentic' tasks, but for raw problem solving without tools or search they match opus and gpt while presumably being a fraction of the size.

I feel like google will surprise everyone with a model that will be an entire generation beyond SOTA at some point in time once they go from prototyping to making a model that's not a preview model anymore. All models up till now feel like they're just prototypes that were pushed to GA just so they have something to show to investors and to integrate into their suite as a proof of concept.

Re: Our eighth generation TPUs: two chips for the agentic era

#65

Post by jbellis »

kamranjon wrote: post #39

It's interesting that, of the large inference providers, Google has one of the most inconvenient policies around model deprecation. They deprecate models exactly 1 year after releasing them and force you to move onto their next generation of models. I had assumed, because they are using their own silicon, that they would actually be able to offer better stability, but the opposite seems to be true. Their rate limitin…

Flash 2 isn't even at EOL until June but we started seeing ~90% error rates getting 429s over the weekend. (So we switched to GPT 5.4 nano.)

Re: Our eighth generation TPUs: two chips for the agentic era

#67

Post by surajrmal »

gordonhart wrote: post #41
kamranjon wrote: post #39

It's interesting that, of the large inference providers, Google has one of the most inconvenient policies around model deprecation. They deprecate models exactly 1 year after releasing them and force you to move onto their next generation of models. I had assumed, because they are using their own silicon, that they would actually be able to offer better stability, but the opposite seems to be true. Their rate limitin…

It's frustrating how cavalier they are about killing old Gemini releases. My read is that once a new model is serving >90% of volume, which happens pretty quickly as most tools will just run the latest+greatest model, the standard Google cost/benefit analysis is applied and the old thing is unceremoniously switched off. It's actually surprising that they recently extended the EOL date for Gemini 2.5. Google has never…

What benefit is there to sticking on older models? If the API is the same, what are the switching costs?

Re: Our eighth generation TPUs: two chips for the agentic era

#68

Post by knowaveragejoe »

written-beyond wrote: post #26
vibe42 wrote: post #12

Earlier quoted context omitted.

Training their own, closed, internal models on their own data sets? Probably a good way to squeeze out some market trading signals.

I thought these TPUs were primarily used for inference?

As the article states, there's both training and inference dedicated chips.

Re: Our eighth generation TPUs: two chips for the agentic era

#69

Post by knowaveragejoe »

jmyeet wrote: post #56

In recent discussions about Tim Apple [sic] moving on there was a discussion about whether Apple flopped on AI, which is my opinion. Of course you had the false dichotomy of doing nothing or burning money faster than the US military like OpenAI does. IMHO that happy medium is Google. Not having to pay the NVidia tax will likely be a huge competitive advantage. And nobody builds data centers as cost-effectively as Goo…

> I saw a claim that Claude Mythos cost ~$10B to train.

Can you cite this? That seems absurd.

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