4 ms·
I've looked for papers, but can't figure this out: do our current neural networks (LLM, vision) qualify as complex systems? Are they composed of autonomous age
by concinds 4y ago
I've looked for papers, but can't figure this out: do our current neural networks (LLM, vision) qualify as complex systems?
Are they composed of autonomous agents that exhibit:
- diversity (in behavior)
- high connectedness
- interaction among agents
- adaptation (agents changing their behavior based on the behavior of other agents)?
Because if current NNs don't fit that definition of complexity, they it seems unreasonable to expect them to be intelligent, no matter their scale. Intelligence will likely be an emergent property of the above four criteria.
If anyone knows of relevant books or papers, would love to hear it.
BTW: "AI winter" refers to a collapse in funding; but I think we're well past that point. Previous winters only happened because academia led AI research, and there were no commercial opportunities. Now, the economic benefits are far more tangible. And if funding doesn't dry up, there's no reason to think innovation will dry up either.
- pksebben 4y agothey're gonna. I've seen a lot of material on wiring these models together to have them do more interesting cross-functional work. Microsoft is about to put out a model you can talk to that makes and recognizes images - and there's already multi-model frameworks that do things like speech-to-text to LLM to text-to-speech, which means you can hold a verbal conversation. Once the continuous learning problem is solved, it'll be pretty trivial to just tell your compound model to "go learn everything you can about x" and have it autonomously do so. If it were me, the first thing I'd ask it to do was learn how to make other AI, then give it some hardware and the directive to build the best thing it could and test it until it can build a model better than itself.