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by bigyabai 117 days ago
Many laptops and workstations also fell for the NPU meme, which in retrospect was a mistake compared to reworking your GPU architecture. Those NPUs are all dark silicon now, just like these Taalas chips will be in 12-24 months.

Dedicated inference ASICs are a dead end. You can't reprogram them, you can't finetune them, and they won't keep any of their resale value. Outside cruise missiles it's hard to imagine where such a disposable technology would be desirable.
1 comments
ivan_gammel 116 days ago
Most consumers do not care about reprogramming or fine-tuning and have no idea what NPU is. For many (including specifically those who still mourn dead AI companions, killed by 4o switch) the long term stability is much more important than benchmark performance of evergreen frontier model. If Taalas can produce a good hardwired model at scale at consumer market price point, a lot of people will just drop their AI subscriptions.
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bigyabai 116 days ago
> a lot of people will just drop their AI subscriptions.

For a 2.5 kW Server? I don't see it happening, your money and electricity is better spent on CUDA compute.

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ivan_gammel 116 days ago
>For a 2.5 kW Server?

I don’t see any reason why this should not drop to 100-300W at peak with maybe 100W*h of daily usage on smartphones.

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