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remich | 3 months ago
I'm an SWE working in AI-related development so I have a probably higher baseline of understanding than most, but even I end up awed sometimes. For example, I was playing a video game the other night that had an annoying box sliding puzzle in it (you know, where you've got to move a piece to specific area but it's blocked by other pieces that you need to move in some order first). I struggled with it for way too long (because I missed a crucial detail), so for shits and giggles I decided to let ChatGPT have a go at it.
I took a photo of the initial game board on my tv and fed it into the high thinking version with a bit of text describing the desired outcome. ChatGPT was able to process the image and my text and after a few turns generated python code to solve it. It didn't come up with the solution, but that's because of the detail I missed that fundamentally changed the rules.
Anyway, I've been in the tech industry long enough that I have a pretty good idea of what should and shouldn't be possible with programs. It's absolutely wild to me that I was able to use a photo of a game board and like three sentences of text and end up with an accurate conclusion (that it was unsolvable based on the provided rules). There's so much more potential with these things than many people realize.
ACCount37|3 months ago
They can process 2 megabytes of C sources, but not 2 sentences of natural language instructions. They find it easy to multiply 10-digit numbers but not to tell a picture of a dog from one of a cat. Computers are inhuman, in a very fundamental way. No natural language understanding, no pattern recognition, no common sense.
Machine learning was working to undermine that old assumption for a long time. But LLMs took a sledgehammer to it. Their capabilities are genuinely closer to "what humans can usually do" than to "what computers can usually do", despite them running on computers. It's a breakthrough.