I don’t see much similarity beyond the most superficial.

If you sit at a slot machine and pump quarters into it, each “turn” is independent. You spin and you win or lose. It’s pure chance and there is no destination. You execute the exact same action over and over and hope random chance brings you more money.

If you sit down in front of a coding harness, the progress is incremental and directed. You ask for a thing, the LLM produces something that is hopefully close to what you wanted. You give it more direction to prod it closer to the end state you want. You are not executing the same action, but incrementally nudging it in the right direction. I’ve literally never restarted from the same initial state with the same prompt and hoped for a different result and I don’t know why anyone would. Rarely I’ve thrown away the progress made and started over but always with a very different prompt that includes learnings from the failed attempt.

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rnjesus 28 minutes ago | parent [-]

i agree with you that it’s principally different from a slot machine, and that it’s possible to use it in a way (like you describe) that is much more focused, for lack of a better term, to great effect

most people don’t use ai this way though, and i still feel like the end-psychological reward mechanism is very, very similar to gambling regardless of how well one utilizes it (and this is even more obvious with image generation as you chase that perfect output)

perhaps it’s better to compare it to gacha than slots?

	▲	dpark 12 minutes ago \| parent [-]
		> most people don’t use ai this way though How do they use it? Surely no one is just repeating the same prompt over and over (except as a Ralph loop perhaps, which is automated). I’m really struggling with the notion that most people just throw the same prompt repeatedly hoping it eventually works. Because that doesn’t sound like gambling. It sounds crazy (and frustrating). > and i still feel like the end-psychological reward mechanism is very, very similar to gambling regardless of how well one utilizes it In the sense that you get a dopamine reward when you succeed, sure, but I get the same reward when I code by hand and achieve a successful result. > and this is even more obvious with image generation as you chase that perfect output This is fair, because sometimes with image generation the same exact prompt will produce very different output. This is becoming less true as the models get better and it becomes more effective to direct image generation iteratively than to keep starting from scratch with a barely tweaked prompt.