121–130 of 196 posts
Great post, but every time I read something like this I feel like I am living in a prequel to the Culture.
Is that bad? The Culture is pretty cool I think. I doubt the real thing would be so similar to us but who knows.
Earlier quoted context omitted.
That doesn't really settle it, just dismiss the question. The submarine analogy could be interpreted to support either conclusion.
Wasn’t the point that process does not matter if we can’t distinguish the end results?
Earlier quoted context omitted.
Wasn’t the point that process does not matter if we can’t distinguish the end results?
I doubt Dijkstra was unable to distinguish between a submarine and a swimmer.
Earlier quoted context omitted.
Is that bad? The Culture is pretty cool I think. I doubt the real thing would be so similar to us but who knows.
It's cool to read about, but there's a reason most of the stories are not about living as a person in the Culture. It sounds extremely dull.
Earlier quoted context omitted.
It's cool to read about, but there's a reason most of the stories are not about living as a person in the Culture. It sounds extremely dull.
It doesn't sound dull to me. The stories are about the periphery of the Culture because that gets the most storytelling value out of the effort that went into worldbuilding, not because it would be impossible to write interesting stories about ordinary Culture members. I don't think you need external threats to give life meaning. Look at the popularity of sports in real life. The challenge there is self-imposed, but…
I didn't say people did. But overcoming real challenges seems to be a big part of feeling alive, and I wonder if we really all would settle back into going for walks all day or whatever we could do that entertain us without needing others to work to provide the entertainment. Perhaps the WALL-E future, where we sit in chairs? But with AI-generated content?
Earlier quoted context omitted.
Not at all, we are building conceptual reasoning machines, but it is an entirely different technology than GPT/LLM dl/ml etc. [1] [1] https://graphmetrix.com/trinpod-server
Conceptual reasoning machines rely on concrete, explicit and intelligble concepts and rules. People like this because it 'looks' like reasoning on the inside. However, our brains, like language models, rely on implicit, distributed representations of concepts and rules. So the intelligble representations of conceptual reasoning machines are maybe too strong a requirement for 'reasoning' unless you want to exclude hum…
Earlier quoted context omitted.
Software Engineering is difficult to verify because it requires dealing with ambiguous understanding of the end-user actual needs / value and subtle trade-offs about code maintainability vs feature coverage vs computational performance. Algorithmic puzzles, on the other hand, both require reasoning and are easy to verify. There are other things in coding that are both useful and easy to verify: checking that the gene…
I agree with you on the first part, but no, code is not easy to verify. I think you missed part of what I wrote. I mean verify that your code is bug free. This cannot be done purely through testing. Formal verification still remains an unsolved problem.
Another issue is, how much data can you synthesize in such a way, so that you can construct both the problem and solution, so that you know the answer before using it as a sample.
Ie, some problems are easier to make knowing you can construct the problem yourself, but if you were to solve said problems, with no prior knowledge, they would be hard to solve, and could be used as a scoring signal?
Ie, you are the Oracle and whatever model is being trained doesn't know the answer, only if it is right or wrong. But I don't know if the reward function must be binary or on a scale.
Does that make sense or is it wrong?
Earlier quoted context omitted.
I think this is because they're trained using RL, and math and coding problems offer an easy way to automatically assess an answer's correctness. I'm not sure how you'd score the correctness of other types of reasoning problems without a lot of manual (and highly subjective!) effort. Perhaps using simulations and games?
but even then it is not so trivial. Yesterday I gave DeepSeek a simple diophantine equation and it got it wrong 3 times, tried to correct itself and didn't end on a correct solution, but rather lied that the final solution is correct.
I am sure this is improperly worded, I apologise.