Amara Angelica pointed me to an article in IEEE Spectrum titled MoNETA: A Mind Made from Memristors
I'm often skeptical of hardware projects hyped as AI projects, but truth be told, I find this one an extremely exciting and promising project.
I think the memristor technology is amazing and may well play part in the coming AGI revolution.
Creating emulations of human brain microarchitecture is one fascinating application of memristors, though not the only one and not necessarily the most exciting one. Memristors can also be used to make a lot of other different AI architectures, not closely modeled after the human brain.
[For instance, one could implement a semantic network or an OpenCog-style AtomSpace (weighted labeled hypergraph) via memristors, where each node in the network has both memory and processor resident in it ... this is a massively parallel network implemented via memristors, but the nodes in the network aren't anything like neurons...]
And, though the memristors-for-AGI theme excites me, this other part of the article leaves me a bit more skeptical:
By the middle of next year, our researchers will be working with thousands of candidate animats at once, all with slight variations in their brain architectures. Playing intelligent designers, we'll cull the best ones from the bunch and keep tweaking them until they unquestionably master tasks like the water maze and other, progressively harder experiments. We'll watch each of these simulated animats interacting with its environment and evolving like a natural organism. We expect to eventually find the "cocktail" of brain areas and connections that achieves autonomous intelligent behavior.
I think the stated research program places too much emphasis on brain microarchitecture and not enough on higher-level cognitive architecture. The idea that a good cognitive architecture is going to be gotten to emerge via some simple artificial-life type experiments seems very naive to me. I suspect that, even with the power of memristors, designing a workable cognitive architecture is going to be a significant enterprise. And I also think that many existing cognitive architectures, like my own OpenCog or Stan Franklin's LIDA or Hawkins' or Arel's deep learning architectures, could be implemented on a memristor fabric without changing their underlying concepts or high-level algorithms or dataflow.
So: memristors for AI, yay!
But: memristors as enablers of a simplistic Alife approach to AGI ... well, I don't think so.
Yep, they're quite naive. You can't evolve an AGI without the correct selection pressures to evolve against. If at all.
Memristor tech is pretty good IFF it causes better FPGA chips. If it does, well, the applications surely aren't limited to AGI. However, I suppose AGI would greatly benefit from that. I wish the evil FPGA firm and I hadn't parted ways.
Re: "But here's the really interesting thing about a memristor: Whatever its past state, or resistance, it freezes that state until another voltage is applied to change it. Maintaining that state requires no power. That's different from a dynamic RAM cell, which requires regular charge to maintain its state."
That sounds a lot like flash memory.
"The idea that a good cognitive architecture is going to be gotten to emerge via some simple artificial-life type experiments seems very naive to me."
A 'mind' produced using artificial life simulations would be a binary blob. Even an evolved logical controller (a computer program you could trace and analyze) wouldn't serve as a configurable, stock cognitive architecture that could be repurposed or extended
Nonetheless the cognitive engines so produced can be used as-is, in robots or electronic spaces used for their evolution. Imagine if cycles-per-second boomed to the point where we could evolve-on-demand an intelligent agent for any task. The notion of a cognitive architecture would be summarily defenestrated, entirely! That day is of course not foreseeable but I felt I should say something for a-life. Tom Barbalet had me on the Biota podcast a week ago and that recording should be up in maybe another week... if you're interested in my further thoughts
Yeah this seems too naive for me to. I think it's important to understand that "from nothing nothing comes".
So there's got to be something that makes the magic happen.
I think that the point about a useful a-life being basically a binary blob is important.
The article conflates the purpose and utility of digital and artificial-synapse systems; digital systems are, e.g., easily serializable to storage medium and easily reproduced and duplicated. Artificial-synapse systems, however, don't have this benefit, and must indeed be "grown" to purpose, unless some way can be devised to mass-read and mass-set memristor states in a digital fashion. And then you hit problems of storage capacity, etc.
Part of the allure of AI has always been the combination of both worlds -- the adaptiveness and sheer power of wetware/artificial-synapse brains, and the programmability, reproducibility, and storability of digital media. If you throw away one part of this equation -- if you just keep the synapse-like behaviors, but don't have the easy control and replication of digital media, I think that you'll find that applications outside of academia and certain one-off purposes are few and far between.
Just like with the meshing of real neurons and digital circuitry, I believe that research must proceed in parallel to learn how to effectively use this massive memristor-based processing/learning power in real world, commercial applications.
In short, who's going to want to have an artificial cat that's as unique, poorly behaved, and quirky as a real cat, and take just as long to "train?" Why do that when you can have... a real cat? Now, if that "cat" could be duplicated, reprogrammed, and "tweaked" to do things like find your car keys... and then you could copy that "program" to other "cats"... well, that's when things would start to get interesting, but that's also when you start to deviate from memristor architectures back towards traditional digital architectures.
I don't understand the last comment. The first uses of memristors will be memories. Of course you can mass read and set their states.
we thank to you for this kind of platform thanks
ib math tutor in gurgaon
ib tutor in gurgaon
ib home tutor in gurgaon
ib home tutor in Delhi
I recommend to write such more post.I also recommend visiting elearning mobile app developer
Thank for Sharing the Blog it really Provide a profound Knowledge keep sharing like this. I also recommend visiting Best Hotel Management College in UP .
Really this article is truly one of the best in article history and am a collector of old "items" and sometimes read new items if i find them interesting which is one that I found quite fascinating and should be part of my collection. Very good work!
Data Scientist Course in Gurgaon
Very great post which I really enjoy reading this and it is not everyday that I have the possibility to see something like this. Thank You.
Best Online Data Science Courses
Excellent work done by you once again here and this is just the reason why I’ve always liked your work with amazing writing skills and you display them in every article. Keep it going!
Data Analytics Courses in Hyderabad
Interesting post. which i wondered about this issue so thanks for posting and very good article which is a really very nice and useful article. Thank you
Data Science Course in Noida
This is truly an practical and pleasant information for all and happy to see this awesome post by the way thanks for sharing this post.
Data Scientist Course in Noida
Nice post. This is a great article and am pretty much pleased with your good work. Very helpful information. Thank you.
Best Data Science Courses
Really Like These New Tips, Which I Haven't Heard of Before, Like Telewear”: What to wear when seeing patients virtually. Can’t Wait to Implement Some of These as Soon as Possible.
Post a Comment