Ask ChatGPT to estimate the carbs in your lunch. Now ask it again. And again. Five hundred times. You’d expect the same answer each time. It’s the same photo, the same model, the same question. But you won’t get the same answer. Not even close — and the differences are large enough to cause a
AI doesn’t see individual characters, it sees tokens, with most tokens being a word or part of a word. That’s why per-character questions have such a high failure rate.
It doesn’t understand anything though? It never will. It’s a probability machine. If you choose to believe its output, that’s on you. I use it as a coding assistant to get boring things done faster. Fire a prompt at claude code, grab a coffee, check out the diff. But that last step is crucial. Can’t trust AI output blindly.
The embedding layer post tokenization is not just a probability machine the way you’re suggesting it. You can argue that it is probabilistic with inferred sentiment, but too many people think it works like how text prediction on your phone does and that is just factually inaccurate.
Verify output of course, but saying “it doesn’t understand anything” and “probability machine” is a borderline erroneous short sell. At the level of tokens it “understands” relationships, and those relationships are not probabilistic, though they are fundamentally approximated based on a training corpus.
AI doesn’t see individual characters, it sees tokens, with most tokens being a word or part of a word. That’s why per-character questions have such a high failure rate.
If it doesn’t understand the simple concept of the number of letters and spaces, it needs to be reprogrammed.
ETA: sorry folks, not gonna change my view and simp for shit A.I., continue with the downvotes.
It doesn’t understand anything though? It never will. It’s a probability machine. If you choose to believe its output, that’s on you. I use it as a coding assistant to get boring things done faster. Fire a prompt at claude code, grab a coffee, check out the diff. But that last step is crucial. Can’t trust AI output blindly.
The embedding layer post tokenization is not just a probability machine the way you’re suggesting it. You can argue that it is probabilistic with inferred sentiment, but too many people think it works like how text prediction on your phone does and that is just factually inaccurate.
Verify output of course, but saying “it doesn’t understand anything” and “probability machine” is a borderline erroneous short sell. At the level of tokens it “understands” relationships, and those relationships are not probabilistic, though they are fundamentally approximated based on a training corpus.
ah right, and my eyes need to be recreated because they can’t see ultraviolet