AMD acquires Taalas to boost inference performance by etching models in silicon

Post by phonon » Sat, Aug 08, 2026, 8:18 PM UTC

briansm wrote: post #690

phonon wrote: post #590

Earlier quoted context omitted.

A full wafer like Cerebras is about 60x that, and N2P has about 3x the transistor density. So right now it's technically feasible to etch a 1.4 trillion parameter model. So roughly DeepSeek-V4-Pro class. Imagine that running a factory, for example.

Cerebras have special techniques to work around etching errors / bad cores on their wafers. This is possible since their wafers are effectively hundreds of identical copies of redundant cores. Can't do that for a globally unique model. Etching failure in that situation would be like brain-damage in a human, all sorts of weird effects would start appearing.

A few hundred bad bits/transistors in a trillion+ parameter model would compromise its abilities not one iota...the models are inherently lossy and resistant to "brain damage"...

Post by sensanaty » Sat, Aug 08, 2026, 8:44 PM UTC

Closi wrote: post #561

mixermachine wrote: post #520

Earlier quoted context omitted.

Scaling a model on a chip is quite hard. ChatJimmy is based on Llama 3.1 8 billion. Kimi K3 has 2.8 trillion parameters. That are 350x more parameters. I would expect that Gemma 4 E2B (approx 5.1 billion parameters) or maybe even Gemma 4 26 billion A4B at some point is running on a chip.

Scaling is definetly hard - but there is no absolute requirement to put huge flagship models into this technology (although it might be possible over time). A fairly dumb but FAST model has it's own totally distinct use-cases even if it can't be scaled in size. Think about a LLM-infused-Alexa where the response time is instant. Where you can request it looks at hotel options in Montreal, and it starts answering in ha…

And outside of idiotic demos, who exactly is going to ask an LLM to look at hotels in Montreal for them? This usecase has never made sense to me in the slightest

Re: AMD acquires Taalas to boost inference performance by etching models in silicon

Re: AMD acquires Taalas to boost inference performance by etching models in silicon