Comment on OpenAI’s new “deep-thinking” o1 model crushes coding benchmarks.
stephen01king@lemmy.zip 1 month agoMost adults can also lean to code, if they actually tried. If you’re gonna add the argument that most people can’t code proficiently, most people can’t drive proficiently, either.
Also, driving and coding are completely different set of skills that it’s kinda stupid to compare them. Some people can code just fine but might never learn how to drive because they didn’t need to, so to consider driving as a prerequisite skill to coding doesn’t make sense.
Valmond@lemmy.world 1 month ago
Well I think you’re wrong here, and about any adult can learn how to drive, but only a small subset can learn how to code. Not learning how to throw a simple script together, real codeing.
Coding is engineer level, engineers build cars, they dont only drive them. For me the difference is the same between a developer of a software and the user of said soft.
One it way way way more complicated, and IA is supposed to do that “soon” when it can’t even drive a car.
Nah, not happening any time soon.
stephen01king@lemmy.zip 1 month ago
I think you’re completely wrong by still comparing skills that have no relation to each other. What’s the similarity between driving and coding that would require an LLM to be need to do one before you can believe it can do the other? Explain that leap in logic properly before you continue with your argument.
An LLM is designed to output text. Expecting them to drive to prove their ability to output code is like expecting them to dance to prove their ability to produce poems. It’s inability to do an unrelated skill has no bearing on it’s ability to do a different one. You’re basically judging a fish on its ability to walk on land, and using that as the basis to judge its ability to swim.
Valmond@lemmy.world 1 month ago
Neural networks are quite similar in complexity, whatever they output.
Driving is way less complex than programming.
stephen01king@lemmy.zip 1 month ago
What does that even mean? Neural networks have varying levels of complexity, even within the same technology. Even the same LLM model can have different number of tokens that differentiate the complexity of their operation.
So instead of using a neural network that is designed to input and output text and making it learn to output coding, which is also text, you think it’s supposed to be easier for them to make it instead analyse various video and audio input from multiple cameras, and then output the various actions that is required for it to drive a car? Does that make sense to you?