Comments URL: https://news.ycombinator.com/item?id=48464080

Points: 3

# Comments: 0

"Neurons?"

"Neurons. Cells that fire impulses. We checked the whole thing through. It's nothing but neurons."

"Neurons doing what? Where do the words come from?"

"The neurons make the words. Are you understanding me? We opened it up. There's no dictionary in there, no grammar rules, no little man. Just neurons. A whole cortex of neurons sending each other impulses."

...

People don't understand emergence.

But I guess everyone thinks the world is like he wants it to be in this respect.

Both sides have a mental bias, and just can't see each other's "reasoning" because of it.

We blues think of reds as selfish, because we can't conceive of anyone not thinking of the worst outcome for others, and being empathetic about it, making it one's own. And they see us as "virtue signalling", or getting some external value of some kind (recognition from peers) because they can't think of any other explanation to justify that behavior, when it is just pure bias towards sacrifice. Sacrifice is just that, giving something without asking nothing, which does not make sense for a red. Reds think we are dumb but society needs a little more blues than reds. Otherwise it probably collapses.

I'm such a proud blue. in fact... ;)

Some people thrive in more stressful situations, because they don't get as aroused in calmness, but everybody has a threshold velocity at which discomfort starts, higher or lower. AI puts us closer to that threshold, for sure.

Chemistry trumps psychology. Good enough chemistry enables cognitive treatments. But to fix the wrong chemistry you need chemistry.

From where I look at it, LLMs are flawed in many ways, and people who see progress as inevitable do not have a mental model of the foundation of those systems to be able to extrapolate. Also, people do not know any other forms of AI or have though hard about this stuff on their own.

The most problematic things are:

1) LLMs are probabilistic and a continuous function, forced by gradient descent. (Just having a "temperature" seems so crazy to me.) We need to merge symbolic and discrete forms of AI. Hallucinations are the elephant in the room. They should not be put under the rug. They should just not be there in the first place! If we try to cover them with a layer of varnish, the cost will be very large in the long run (it already is: step-by-step reasoning, mixture of experts, RAG, etc. are all varnish, in my opinion)

2) Even if generalization seems ok, I think it is still really far from where it should be, since humans need exponentially less data and generalize to concepts way more abstract than AI systems. This is related to HASA and ISA relations. Current AI systems do not have any of that. Hierarchy is supposed to be the depth of the network, but it is a guess at best.

3) We are just putting layer upon layer of complexity instead of simplifying. It is the victory of the complexifiers and it is motivated by the rush to win the race. However, I am not so sure that, even if the goal seems so close now, we are going to reach it. What are we gonna do? Keep adding another order of magnitude of compute on top of the last one to move forward? That's the bubble that I see. I think that that is not solving AI at all. And I'm almost sure that a much better way of doing AI is possible, but we have fallen into a bad attractor just because Ilya was very determined.

We need new models, way simpler, symbolic and continuous at the same time (i.e. symbolic that simulate continuous), non-gradient descent learning (just store stuff like a database), HAS-A hierarchies to attend to different levels of structure, IS-A taxonomies as a way to generalize deeply, etc, etc, etc.

Even if we make progress by brute forcing it with resources, there is so much work to simplify and find new ideas that I still don't understand why people are so optimistic.