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interesting that the article mentions Microsoft is trying to build their own AI chips to help reduce cost, they are years behind Google in that effort. Google s

interesting that the article mentions Microsoft is trying to build their own AI chips to help reduce cost, they are years behind Google in that effort. Google still has the advantage in both research and hardware, they just fumbled the execution but it's still very early in the game

barkerja 3y ago
> they are years behind Google in that effort. Google still has the advantage in both research and hardware, they just fumbled the execution but it's still very early in the game Where do we think Apple is in regards to this? If anyone has the upper-hand here with hardware, I would think it'd be Apple. But there's been zero indication that Apple has been working on any sort of generative AI.
- rvnx 3y ago
  Local Siri for June WWDC :)
- kolinko 3y ago
  Apple already has a super-efficient neural engine in all their chips - it's just a matter of them building dedicated models for them.
  - yunohn 3y ago
    Apple has stuffed their consumer hardware with high-end chips - that are completely under-utilised by themselves and restricted for third-party apps…
- pr337h4m 3y ago
  This was very promising: https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon https://machinelearning.apple.com/research/stable-diffusion-...
behnamoh 3y ago
The past 3 years showed that Google is not as ahead as people thought they were.
- edgyquant 3y ago
  In what way?
  - behnamoh 3y ago
    In Bard way.
brrrrrm 3y ago
In terms of production pipeline, sure. But since there’s an established model architecture, the hardware doesn’t need to be super generic. Google had to build TPUs in a world where everything was still rapidly changing - deciding on things like precision, memory bandwidth, SRAM size etc. Microsoft could theoretically stamp out some GPT ASICS and call it a day.
rapsey 3y ago
Aren't Google TPUs way less performant than A100s?
- Workaccount2 3y ago
  They are actually as good or better depending on the use case. IIRC their compute is around the same, and the compute per watt is substantially better. They are also purpose built for transformers. But google is fumbling so hard right now it's not surprising that they are squandering this too.

barkerja 3y ago

> they are years behind Google in that effort. Google still has the advantage in both research and hardware, they just fumbled the execution but it's still very early in the game Where do we think Apple is in regards to this? If anyone has the upper-hand here with hardware, I would think it'd be Apple. But there's been zero indication that Apple has been working on any sort of generative AI.

rvnx 3y ago
Local Siri for June WWDC :)
kolinko 3y ago
Apple already has a super-efficient neural engine in all their chips - it's just a matter of them building dedicated models for them.
- yunohn 3y ago
  Apple has stuffed their consumer hardware with high-end chips - that are completely under-utilised by themselves and restricted for third-party apps…
pr337h4m 3y ago
This was very promising: https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon https://machinelearning.apple.com/research/stable-diffusion-...

behnamoh 3y ago

The past 3 years showed that Google is not as ahead as people thought they were.

edgyquant 3y ago
In what way?
- behnamoh 3y ago
  In Bard way.

brrrrrm 3y ago

In terms of production pipeline, sure. But since there’s an established model architecture, the hardware doesn’t need to be super generic. Google had to build TPUs in a world where everything was still rapidly changing - deciding on things like precision, memory bandwidth, SRAM size etc. Microsoft could theoretically stamp out some GPT ASICS and call it a day.

rapsey 3y ago

Aren't Google TPUs way less performant than A100s?

Workaccount2 3y ago
They are actually as good or better depending on the use case. IIRC their compute is around the same, and the compute per watt is substantially better. They are also purpose built for transformers. But google is fumbling so hard right now it's not surprising that they are squandering this too.