You might wanna look at https://taalas.com/

There's no mention of SLMs or LLMs, though.

> This work represents a compelling real-world demonstration of “tiny AI” — highly specialised, minimal-footprint neural networks

FPGAs for Neural Networks have been s thing since before the LLM era.

Are they some ancient small-scale integration VLSI design? Do they broadcast on a low-frequency VHF band? Face it: Oxymorons like those are part of the technical world. "VLSI" was a current term back when whole CPUs were made out of fewer transistors than we use for register files now, and "VHF" is low frequency even by commercial broadcasting standards.

turns out we still needs more vibes

This is a good one

https://madoc.bib.uni-mannheim.de/809/ is one of a gazillion papers you can find with ancient technology called web search.

It was ten years ago I worked on an oscilloscope for CERN with FPGA trigger. You were able to update the trigger portion of the bitstream at any time, without a reset. Typically that was a FIR filter but it could be anything.

Like anything else, once you work with a system, it gives you ten ideas where to go next...

It doesn't say LLM anywhere.

> That's what Groq did as well: burning the Transformer right onto a chip

Are you perhaps confusing Groq with the Etched approach? IIUC Etched is the company that "burned the transformer onto a chip". Groq uses LPUs that are more generalist (they can run many transformers and some other architectures) and their speed comes from using SRAM.