11–20 of 166 posts
Does anyone know why they are using language models instead of a more purpose-built statistical model? My intuition is that a language model would either be overfit, or its training data would have a lot of noise unrelated to the application and significantly drive up costs.
5 years ago we would've called it a Machine Learning algorithm. 5 years before that, a Big Data algorithm.
https://www.youtube.com/watch?v=8IZwhbsjhvE (From Zettabytes to a Few Precious Events: Nanosecond AI at the Large Hadron Collider by Thea Aarrestad)
Page: https://www.scylladb.com/tech-talk/from-zettabytes-to-a-few-...
Hey Siri, show me an example of an oxymoron! > CERN is using extremely small, custom large language models physically burned into silicon chips to perform real-time filtering of the enormous data generated by the Large Hadron Collider (LHC).
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.
Like (~9K) Jumbo Frames!
Does anyone know why they are using language models instead of a more purpose-built statistical model? My intuition is that a language model would either be overfit, or its training data would have a lot of noise unrelated to the application and significantly drive up costs.
It's not an LLM, it is a purpose built model. https://arxiv.org/html/2411.19506v1 5 years ago we would've called it a Machine Learning algorithm. 5 years before that, a Big Data algorithm.
A bit of hype in the AI wording here. This could be called a chip with hardcoded logic obtained with machine learning
Earlier quoted context omitted.
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.
Huh? The first paragraph literally says they are using LLMs > [ GENEVA, SWITZERLAND — March 28, 2026 ] — CERN is using extremely small, custom large language models physically burned into silicon chips to perform real-time filtering of the enormous data generated by the Large Hadron Collider (LHC).
Does anyone know why they are using language models instead of a more purpose-built statistical model? My intuition is that a language model would either be overfit, or its training data would have a lot of noise unrelated to the application and significantly drive up costs.
It's not an LLM, it is a purpose built model. https://arxiv.org/html/2411.19506v1 5 years ago we would've called it a Machine Learning algorithm. 5 years before that, a Big Data algorithm.
> 5 years before that, a Big Data algorithm.
The DNN part? Absolutely not.
I don’t know why people feel the need for such revisionism but AI has been a field encompassing things far more basic than this for longer than most commenters have been alive.