On a distinguished career, deep learning's promise, and directions for the field.
This new article is very interesting, although progress in DL may show the hypothesis wrong. Further progress in langauge and text may show no need for the complexity of physical information. Generative AI is showing us findings we had no idea of at the foundational level of science and language without the physical maybe another area.
Introducing this professor and access to his article on DL in 2015 was a great find.
It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with primary consciousness will probably have to come first.
What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990's and 2000's. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I've encountered is anywhere near as convincing.
I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there's lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.
My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar's lab at UC Irvine, possibly. Dr. Edelman's roadmap to a conscious machine is at https://arxiv.org/abs/2105.10461
Thanks for the detailed thoughts, Grant! This paper looks fascinating and I’ll absolutely take a look.
On “the proof will be in the pudding” I guess I come at this in a few ways. First I think there’s the obvious philosophical zombies refrain, but I think you can also come at it from the “if it’s entirely functional, does what’s it really matter?” perspective as well. I think this take also probably depends on some of your commitments on consciousness eg is it emergent etc etc.
On the primary vs higher-order consciousness distinction, I guess what you’re getting at is the mere having of mental states (primary) vs then reflecting on those mental states, articulating them, etc (higher-order) and I’d tend to agree.
How do you think about what meets the criterion for a mental state? There are people who might be open to the idea that, depending on what you think a mental state is, NNs / ML systems might have something like that already (I think Chalmers is, and indicated so in my conversation with him from some time ago).
Great article, I’m wondering if we can translate this blog into Chinese and post it on our WeChat official platform. We will keep the original link and state where it is translated from. Thank you so much!
Great interview Daniel. Couple of comments:
- I love hearing what people have to say about the open problems in the field, what ML is bad at, etc. I think it gives something for us to chew on while also inspiring with what the future could be. I think that happened to a reasonable degree here and I liked it
- Audio balance between you guys was really out of whack which made for a jarring experience (Yoshua was super quiet)