I read this as a response to the current hype around LLMs. He is showing computers can solve these issues, without using an LLM architecture. A lot of people have sort of forgot that machine learning is more than just LLMs these days.
I found it to be a very interesting angle.
Just to be clear: It was well known that you can reach such scores with small models and without an LLM if you train on the task. The author highlights those models himself - e.g. HRM/TRM.
The novelty is more that it works with such a plain transformer and low compute price.
> He is showing computers can solve these issues, without using an LLM architecture.
Isn't it a LLM he's building though? My very point is that this particular use case could be solved better without building a LLM, now you claim he is not? The description of what he's doing surely makes it sound like it's a (very small) LLM, and personally I'm still on the "if it quacks like a duck" train in life.
> A lot of people have sort of forgot that machine learning is more than just LLMs these days.
Yeah, which I guess if you make my previous comment more concise, is exactly what I state too.