technology

The field I exited only a couple of years ago has already been decimated by it.

My favourite weird GPT5 fail so far:

I would be perfectly fine with Sam Altman being sent to a reeducation camp.

A lot of people contributed to those crypto numbers. The AI models run in special built data centers. Some have their own generators because the power usage is so high.

This is one of those things that starts getting into the fuzzy area around the unanswered questions regarding what exactly qualifies as qualia and where that first appears. But having needs/wants probably is a necessary condition for actual AI if we're defining actual (general) AI as having self awareness. In addition to what @Awoo@hexbear.net said, here's another thing.

You mention how AI probably has to have a world model as a prerequisite for genuine self aware intelligence, and this is true. But part of that is that the world model has to be accurate at least in so far as it allows the AI to function. Like, maybe it can even have an inaccurate fantasy-world world model, but it still has to model a world close enough to reality that it's modeling a world that it can exist in; in other words the world model can't be random gibberish because intelligence would be meaningless in such a world, and it wouldn't even be a "world model." All of that is mostly beside the point except to point out that AI has to have a world model that approaches accuracy with the real world. So in that sense it already "wants" to have an accurate world model. But it's a bit of a chicken and egg problem: does the AI only "want" to have an accurate model of the world after it gains self-awareness, the only point where true "wants" can exist? Or was that "want" built-in to it by its creators? That directionality towards accuracy for its world model is built into it. It has to be in order to get it to work. The accuracy-approaching world model would have to be part of the programming put into it long before it ever gains sentience (aka the ability to experience, self-awareness) and that directionality won't just disappear when the AI does gain sentience. That pre-awareness directionality that by necessity still exists can then be said to be a "want" in the post-awareness general AI.

An analogy of this same sort of thing but as it is with us bio-intelligence beings: We "want" to avoid death, to survive (setting aside edge cases that actually prove the rule like how extreme of an emotional state a person has to be in to be suicidal). That "want" is a result of evolution that has ingrained into us a desire (a "want") to survive. But evolution itself doesn't "want" anything. It just has directionality towards making better replicators. The appearance that replicators (like genes) "want" to survive enough to pass on their code (in other words: to replicate) is just an emergent property of the fact that things that are better able to replicate in a given environment will replicate more than things that are less able to replicate in that environment. When did that simple mathematical fact, how replication efficiency works, get turned into a genuine desire to survive? It happened somewhere along the ladder of evolutionary complexity where brains had evolved to the extent that self awareness and qualia emerged (they are emergent properties) from the complex interactions of the neurons that make up those brains. This is just one example, but a pretty good one imo that shows how the ability to experience "wanting" something is still rooted in a kind of directionality that exists independently of (and before) the ability to experience. And also how that experience wouldn't have come about if it weren't for that initial directionality.

Wants/needs almost certainly do have to be part of any actual intelligence. One of the reasons for that is because those wants/needs have to be there in some form for intelligence to even be able to arise in the first place.

It gets really hard to articulate this kind of thing, so I apologize for all the "quoted" words and shit in parentheses. I was trying to make it so that what I was attempting to convey with these weird sentences could be parsed better, but maybe I just made it worse.

Machine learning requires needs or wants in order to evolve. If your model is going to learn how to utilise energy efficiently between recharging then it needs to desire energy (need/want). This is just "eat" and "collect water" process of learning. Then you give it predators to learn how to avoid being killed in the process of doing this so it learns survival methods. Add complexity to the environment over time and it'll learn more and more and more.

Reproduction probably needs some sort of social cues to learn, the ability to communicate with other models that they wish to reproduce, or the ability to start working in teams.

It all has the requirement of needs/wants. The basis of all animal intelligence evolving into more efficient methods of doing something is having needs.