alt Hacker NewsI guess when it can't be tripped up by simple things like multiplying numbers, counting to 100 sequentially or counting letters in a string without writing a python program, then I might believe it.
Also no matter how many math problems it solves it still gets lost in a codebase
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anal_reactor • today at 8:40 AM
Arguments like "but AI cannot reliably multiply numbers" fundamentally misunderstand how AI works. AI cannot do basic math not because AI is stupid, but because basic math is an inherently difficult task for otherwise smart AI. Lots of human adults can do complex abstract thinking but when you ask them to count it's "one... two... three... five... wait I got lost".
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tourist2d • today at 8:38 AM
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LLMs are bad at arithmetic and counting by design. It's an intentional tradeoff that makes them better at language and reasoning tasks.
If anybody really wanted a model that could multiply and count letters in words, they could just train one with a tokenizer and training data suited to those tasks. And the model would then be able to count letters, but it would be bad at things like translation and programming - the stuff people actually use LLMs for. So, people train with a tokenizer and training data suited to those tasks, hence LLMs are good at language and bad at arithmetic,