Over just a few months, ChatGPT went from accurately answering a simple math problem 98% of the time to just 2%, study finds::ChatGPT went from answering a simple math correctly 98% of the time to just 2%, over the course of a few months.
Over just a few months, ChatGPT went from accurately answering a simple math problem 98% of the time to just 2%, study finds::ChatGPT went from answering a simple math correctly 98% of the time to just 2%, over the course of a few months.
LLMs act nothing like our brains and they aren’t trained on facts.
LLMs are essentially complicated mathematical equations that ask “what makes the most sense as the next word following this one?” Think autosuggest on your phone taken to the extreme limit.
They do not think in any sense and have no knowledge or facts internal to themselves. All they do is compose words together.
And this is also why they’re garbage at math (and frequently lie, and why they can’t “remember” anything). They are simply stringing words together based on their model, not actually thinking. If their model shows that the next word after “one plus two equals” is more likely to be four than three, they will simply answer four.
Err, yes they are. You don’t even need to read a paper on the subject, just go straight to the Wikipedia page and it’s right there in the first line. The ‘T’ in GPT is literally Transformer, you’re highly unlikely to find a Transformer model that doesn’t use an ANN at its core.
Please don’t turn this place into Reddit by spreading misinformation.
Edited, thanks!
“Nothing like our brains” may be too strong. I strongly suspect that much of human reasoning is little different from stringing words together, albeit with more complicated criteria than current LLMs. For example, children learn maths in a rather similar way, based on language and repeated exposure; humans don’t have a built in maths processor in our brains.