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Where will artificial general intelligence come from?

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Re: Where will artificial general intelligence come from?

#41
post #12
post #7

That was really interesting. I'm interested why he's so pessimistic about the simulating a brain approach. Yes it's the boring and obvious approach but it also seems the most direct. Also found this quote interesting > Might have to make it illegal to evolve AI strains or an upper bound of computation per person and closely track all computational resources on earth.

The brain is slow and redundant. It has to be like that because it is not produced in a factory - it is created by self replication. Self replication imposes strict limits and requirements on the type of brain that can be created. AI neurons, on the other hand, are perfect - they never get old or tired and always remember. A neural net like ResNet-150 is capable of doing essentially what 1/3 of the brain is doing (vi…

> The brain is slow and redundant. It has to be like that because it is not produced in a factory - it is created by self replication. Self replication imposes strict limits and requirements on the type of brain that can be created.

It is also limited by the efficiency that it must attain in order to operate under the energy conditions of our environment.

The energy efficiency of biological systems might be a hint that we should more-directly employ them in the "artificial" minds we build. You're right that the human brain is limited because of its context, but we'll only get superhuman hard artificial intelligence when we're able to build/grow a big one in a vat.

> A neural net like ResNet-150 is capable of doing essentially what 1/3 of the brain is doing (vision).

Is it? There is probably a lot more going on in that 1/3 of our brain than mapping images to words.

Re: Where will artificial general intelligence come from?

#42

I feel that those who argue that any approach other than running human brain emulations and then reverse engineering them or speculatively modifying them is the most likely way to get to AGI has a pretty steep hill to climb in order to justify that point of view. Nothing else that is going on now or even on the agenda or even foreseeable offers a plausible, definitive plan to get to AGI. Whereas brain emulation is cl…

Why reverse it when you can evolve it?

Re: Where will artificial general intelligence come from?

#43

Background: I did AI and Philosophy of Mind in undergrad, an MSc focused on ALife, then a PhD at Yale under a Macarthur Fellow who developed the theoretical framework for the 'evolution of Evolvability' where I worked on computational evolutionary biology. I can say we're not going to blindly brute force our way forward, but instead we'll need to reverse engineer nature's core algorithms to generate hard AI. Every ti…

> neuroscientist say: "why didn't you talk to us 15 years ago? We could have told you that!".

Interested to hear about these. I can honestly not remember any.

Re: Where will artificial general intelligence come from?

#44
post #6

I think a very interesting aspect of general AI is that while an incredibly complex technology, it is not unrealistic that it could be created for the first time in someone's home office. Unlike many other earth changing technologies there is nothing that a massive corporation has that a home tinkerer does not (besides the obvious of money and many engineers). With the rise of cloud computing and open source; everyth…

[X] Open Source Tools [ ] Massive Data Sets [ ] $Millions in Computing Resources I'd put it roughly on par with finding a general cure for cancer. While unlikely, quite amazing that the cure for one of the largest causes of death could be solved 3 doors down with lab supplies from amazon and a handful of mice.

The computing resources are getting cheaper. There was an estimate that to get something roughly equivalent to a human brain you'd need ~100 teraflops and currently you can now get a 12 teraflop GPU from Nvidia for $1200.

Part of the reasoning for the Kurzweil turing test by 2029 type of stuff is that once human level hardware falls in price to hobbyist levels, loads of people will hack away and someone will figure it out.

Re: Where will artificial general intelligence come from?

#45

Background: I did AI and Philosophy of Mind in undergrad, an MSc focused on ALife, then a PhD at Yale under a Macarthur Fellow who developed the theoretical framework for the 'evolution of Evolvability' where I worked on computational evolutionary biology. I can say we're not going to blindly brute force our way forward, but instead we'll need to reverse engineer nature's core algorithms to generate hard AI. Every ti…

Hand-engineering and hand-assembling evolved components will fail, way too complex. We struggle with making bug-free word processors. This will only be solved by fully evolving AGI, or some other form of automated search of high-dimensional design space.

Re: Where will artificial general intelligence come from?

#46
post #6

I think a very interesting aspect of general AI is that while an incredibly complex technology, it is not unrealistic that it could be created for the first time in someone's home office. Unlike many other earth changing technologies there is nothing that a massive corporation has that a home tinkerer does not (besides the obvious of money and many engineers). With the rise of cloud computing and open source; everyth…

[X] Open Source Tools [ ] Massive Data Sets [ ] $Millions in Computing Resources I'd put it roughly on par with finding a general cure for cancer. While unlikely, quite amazing that the cure for one of the largest causes of death could be solved 3 doors down with lab supplies from amazon and a handful of mice.

[deleted]

Re: Where will artificial general intelligence come from?

#47

Background: I did AI and Philosophy of Mind in undergrad, an MSc focused on ALife, then a PhD at Yale under a Macarthur Fellow who developed the theoretical framework for the 'evolution of Evolvability' where I worked on computational evolutionary biology. I can say we're not going to blindly brute force our way forward, but instead we'll need to reverse engineer nature's core algorithms to generate hard AI. Every ti…

I don't think you're wrong that AGI will have (something like) those components in its inception.

I just disagree that we have to intentionally create them -- I think there are a lot of places we can experimentally bruteforce the implementation instead of having a solid theoretical understanding if our only goal is creating an AGI.

I don't think we need any theoretical breakthroughs, per se, but rather, a lot of computing power and time. No one seems willing to take a million nodes and run them for a decade to brute force some of the mechanisms -- everyone wants results on the short timelines that grants or Wall St operate on. I get why, but that bias towards quantifiable short-term gains fundamentally limits the search algorithms we're implementing in our quest for AI, and likely means that we won't get there in a meaningful way, because intentionally implementing the necessary requirements is a fool's errand of complexity.

In short: we're not smart enough to do the simple, but slow thing, so we're trying the highly complex one with demonstrable incremental results. I expect this approach to continuously fail to develop AGI even while it demonstrates results on discrete problems.

Re: Where will artificial general intelligence come from?

#48
post #26
post #14

Earlier quoted context omitted.

The problem with the brain simulation approach seems not that it's boring and obvious but that it's hard to do. They struggle to simulate C. elegans which has 302 neurons in a fixed layout. Humans are harder. >[OpenWorm] project coordinator Stephen Larson estimates it as "only 20 to 30 percent of the way towards where we need to get. (wikipedia) That said, figuring what we can about how the human brain works and tryi…

Numenta is doing much better than the worm brain simulation.

Why do you think so? The Wikipedia page on their method of hierarchical temporal memory[1] says that:

The goal of current HTMs is to capture as much of the functions of neurons and the network (as they are currently understood) within the capability of typical computers and in areas that can be made readily useful such as image processing. For example, feedback from higher levels and motor control are not attempted because it is not yet understood how to incorporate them and binary instead of variable synapses are used because they were determined to be sufficient in the current HTM capabilities.

It doesn't seem like they are even close to a simulation that could accurately model something like C. elegans.

[1] https://en.wikipedia.org/wiki/Hierarchical_temporal_memory

Re: Where will artificial general intelligence come from?

#49

Background: I did AI and Philosophy of Mind in undergrad, an MSc focused on ALife, then a PhD at Yale under a Macarthur Fellow who developed the theoretical framework for the 'evolution of Evolvability' where I worked on computational evolutionary biology. I can say we're not going to blindly brute force our way forward, but instead we'll need to reverse engineer nature's core algorithms to generate hard AI. Every ti…

Hmm, reading your experience clarifies to me (a Maths guy) why current deep learning efforts are producing real fruit from their labor. Linear Regression and Vector/dot products are just constructs to re-create the evolutionary biology seen in nature. When looking at the slow process of evolution, it's the nuances that matter and over time, they compound exponentially. Pretty neat. By breaking down a task into abstract constructs and sifting problems out with a sigmoid function.

Re: Where will artificial general intelligence come from?

#50

When he says "artificial life", is he referring to reinforcement learning?

http://www.alife.org/

Artificial Life is a field with very fuzzy boundaries. Roughly, computer systems that look like biological or ecological systems.

From an AL perspective, life evolves to function in it's ecology. The problem is not building an AGI, it's building an ecology in which AGI will emerge.

Oh... and hopefully, also one in which ruthlessly destroying other intelligent agents isn't a good survival strategy.

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