Matt. I think your comments are most relevant and to the point. Your 
assumptions may be wandering off a little though due to ecological bias, 
affecting the accuracy of some of your statements. Still, it does not matter. 
You mustered a good argument. It was a pleasure to read.

________________________________
From: Matt Mahoney <[email protected]>
Sent: Monday, 02 December 2019 03:50
To: AGI <[email protected]>
Subject: Re: [agi] Anyone worked / working on SOAR Cognitive Architecture? Or 
just requiring help "in general" ...

I don't believe anyone on this list is working on SOAR. It is an old system 
(1983). Back then the only thing you could do in AI with available computing 
power was structured knowledge representation, rule based language models, and 
expert systems. Any work done with autonomous agents was only in simulation. 
There was no vision, hearing, speech, or robotics. Language understanding was 
brittle, with little resemblance to the way humans process language. We learn 
semantics before grammar, the opposite of machines, which is why they are so 
bad with ambiguity.

OpenCog by Ben Goertzel, who posts here occasionally, dates to 1995 if you 
include it's precursors Webmind and Novamente. It has many similar limitations 
due to hardware. The atomspace architecture is supposed to support structured 
knowledge, probabilistic reasoning, induction, and learning, but there is 
nevertheless no knowledge base or useful applications. The evolutionary learner 
MOSES and neural vision system DeSTIN only work on toy problems and were never 
integrated with atomspace as it was designed to be. The last public demo was in 
2009 of a puppy in a virtual world. Since then there really hasn't been any 
basic research.

I don't mean to be critical but AGI is a really hard problem which no 
individual on this list has the resources to solve. Google, Amazon, Apple, 
Facebook, and Microsoft have made some progress, but these are companies with 
trillion dollar market caps. A human brain sized neural network needs 10 to 20 
petaflops and a petabyte of RAM. Our software, encoded in DNA, is equivalent to 
300 million lines, or $30 billion. And then you have to train it on an exabyte 
of video.

But this approach doesn't even make sense. Our whole economy is based on job 
specialization. It is far more efficient to organize machines like we organize 
people, each doing a specific task. Everyone making progress in AI is doing 
narrow AI, and really this is the only practical approach. Instead of trying to 
automate a million different jobs all at once, you'll have more success 
automating one job. That's going to be hard enough, given that all the low 
hanging fruit has been picked.

On Sat, Nov 30, 2019, 11:28 AM digikar via AGI 
<[email protected]<mailto:[email protected]>> wrote:
I am a third year student pursuing a Bachelors in Computer Science and 
Engineering, and have been wanting to get into AGI, since, two years may be. I 
discovered OpenCog, and felt it to be too daunting - like I think I'll require 
another year or two of study to make good sense of it.

I studied some first language acquisition the last summer (along with a basic 
Andrew Ng's ML course, another NLPwDL CS 224n from Stanford, and a more 
rigorous and exhaustive (than the Ng's anyways) Foundations of ML at my own 
university). Reading about first language acquisition led me to believe that a 
primary problem is being able to represent the world (with as much details as 
possible, since dealing with block worlds is easy). So, this is the primary 
issue.

Recently, I spent some time with Natural Semantic Metalanguage, and its 
criticisms. The concept is definitely ambitious; however, that definitely 
doesn't seem to be the way our thoughts work. For instance, see explication for 
"left"<https://linguistics.stackexchange.com/questions/29586/nsm-explication-for-left>;
 for me, 'left' just evokes a direction than all the other things. May be, it 
might be useful for actually representing the world in a computer, but an 
explicit simulation (with which I haven't worked with yet) seems more wieldy.

I found SOAR ambitious and more "established" - however, their 
forums<https://soar.eecs.umich.edu/forum> seemed void. So, just wanted to know 
if anyone is working on it.

Other than that, does their exist some system for representing the world - 
gaming systems come to mind, but is their some established standard?

Thanks!
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