>Training a model to do math is impossible.

https://www.deepmind.com/blog/discovering-novel-algorithms-w...

A language model cannot, by itself, figure that out, at least not to arbitrary complex inputs.

But it’s a fairly sweeping statement to say that AI cannot do it.

Of course it is possible for LLM model to learn this!

The problem was with token embeddings, not with math.

Has this actually been tried? It would be trivial to generate a very large dataset of simple additions and see if an LLM gets it. Maybe it wouldn't serve an immediate practical purpose but I'm curious.

I did try this, although I'm not an AI expert. It will work great for everything that are in the training set, but if there is a hole the model will have trouble. Lets say we train a model with the numbers 1 and 2. 1+1=2, 1+2=3, 2+2=4 we now give the model 2+1 it will likely guess 2 or 4 because those are the ones that have 2 or 1 in the correct place. A neural network can't do logic. It's good at other things though, for example parsing, a language model could parse human input "two plus one" to 2+1 and then just calculate the answer using a math library.

I wish I still believed this.