this post was submitted on 23 Nov 2023
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The simplest way to get an LLM to "do" maths is to have it translate human language tokens relative to Maths to a standard set of Maths tokens, then passing it to a perfectly normal library that does Maths and then translating the results back into human language tokens: easy-peasy LLM "does Maths" only it doesn't, it's just integrated with something else (which was coded by a human) that does the maths and only serves as a translation layer.
Further, the actually implementation of the LLM itself is already doing Maths. For example a single neuron can add 2 numbers by having 2 inputs each with a weight of 1 and a single output because that's exactly how the simplest of neurons already calculate an output from its inputs in a standard neural networks implementation - it can do simple Maths because the very implementation is already doing maths: the "ability" to do maths is supported by the programming language in which the LLM was then coded, so the LLM would be doing maths with as much cognition as a human does food digestion.
Given the amount of bullshit in the AI domain, I would be very very weary of presuming this breakthrough being anywhere near an entirelly independent self-assembled (as in, trained rather than coded) maths engine.
This sounds very knowledgeable. If the reporting is to be believed, why do you think the OpenAI folks might be so impressed by the Q* model’s skills in simple arithmetic?