[yunohn]

But the BTC mining algorithm has not and will not change. That’s the only reason ASICs atleast make a bit of sense for crypto.

AI being static weights is already challenged with the frequent model updates we already see - but may even be a relic once we find a new architecture.

[fxnn]

We can expect the model landscape to consolidate some day. Progress will become slower, innovations will become smaller. Not tomorrow, not next year, but the time will come.

And then it'll increasingly make sense to build such a chip into laptops, smartphones, wearables. Not for high-end tasks, but to drive the everyday bread-and-butter tasks.

[yunohn]

The world continues to evolve, in a way that requires flexibility - not more constraints. I just fail to see a future where we want less general purpose computers, and more hard-wired ones? Would be interesting to be proven wrong though!

[dzhiurgis]

TPU usb-c dongle is less than $100 (widely used for detecting people in home assistant / frigate nvr camera feeds). If one-off $100 purchase can replace (and improve 10x by speed) anthropic subscription even for 12 months - I don't see why not.

[dangus]

Sounds to me like there’s potential to use these for established models to provide cost/scale advantage while frontier models will run in the existing setup.

[yunohn]

IME llama et all require LoRA or fine-tuning to be usable. That's their real value vs closed source massive models, and their small size makes this possible, appealing, and doable on a recurring basis as things evolve. Again, rendering ASICs useless.

[fxnn]

Read the blog post. It mentions that their chip has a small SRAM which can store LoRA.

[yunohn]

Neither the blog nor Taalas' original post specify what speed to expect when using the SRAM in conjunction with the baked-in weights? To be taken seriously, that is really necessary to explain in detail, than a passing mention.