Perhaps it's because, for its exponential complexity, agi defies theoretical 
science. If no executable, framework of computational intelligence exists, 
what's the use of being able to run at the speed of light?

Many commentators here agreed (over time) how agi development requires a 
radically-different approach to all other computational endeavors to date.  As 
evidenced, developing a feasible approach (in the sense of a platform) would 
require at least 10 years of R&D. In my opinion, that is correct. In my case it 
took more than 22 years - part-time. Towards an agi prototype then, with 
10-years' concentrated effort, perhaps another additional 5-7 years?

Perhaps we should start pooling our research and resources with those who offer 
the best 10-year result to date? I'm beginning to think this would be the best 
way forward. Imagine a safe, inclusive, collaborative environment where R&D 
parties could post real problems they needed solving and tangible credit was 
given to the authors of such solutions? We're talking sharing in the pot of 
gold at the end of the rainbow off course.

Except for those sticky-finger, big boys who do not play well with others at 
all. I'm quite certain they monitor this list trying to farm it yet never 
contributing one bit of usefulness to others.  Those we should weed out from 
any "collaborative" setup at every opportunity. They are only in it for 
themselves, not for the industry, or the benefit of the world. Yes, you know 
who you are!

This is the extent of my professional opinion.

Robert Benjamin

________________________________
From: Linas Vepstas <[email protected]>
Sent: Monday, 04 February 2019 6:16 AM
To: AGI
Subject: Re: [agi] The future of AGI

I have no clue what Peter is actually thinking because he's coy and secretive. 
But I'm not pessimistic. I'm just perplexed why no one ever seems to try the 
obvious things. Or why I can never seem to explain obvious things  to anyone 
and have them understand it.  I am quite certain that one can do better than 
neural nets and more easily,  too, an have explained exactly how more times 
than I can count, but my words are not connecting with anyone who understands 
them. So, whatever. Day at a time.

--linas

On Sun, Feb 3, 2019 at 5:28 PM <[email protected]<mailto:[email protected]>> 
wrote:

I’m not that pessimistic at all.



Our own AGI project has made steady progress over the past 17 years in spite of 
only spending about $10 million – about 150 man-years of focused effort.  We’ve 
managed to successfully commercialize an early version of our proto-AGI engine 
in a company that now employs about 100 people 
www.smartaction.com<http://www.smartaction.com> . For the last 5 years my 
full-time team of about 10 people has been working on the next generation 
engine www.AGIinnovations.com<http://www.AGIinnovations.com> /  
www.Aigo.ai<http://www.Aigo.ai> . We are now ready to commercialize this more 
advanced platform.



Our focus has been limited to natural language comprehension/ learning, 
question answering/ inference, and conversation management.

I think that $100 million could go a long way towards functional, demonstrable 
proto AGI.  It seems to me that DeepMind hasn’t made good use of the $200 or 
$300million spend so far – they lack a proper theory of intelligence.  I don’t 
know why Vicarious, the other well-funded AGI company, hasn’t made better 
progress in perception/ action – my guess, for the same reason….

I think all of the theoretical calculations of processing power are widely off 
the mark – we’re not trying to reverse-engineer a bird – just need to build a 
flying machine.



My articles are here: https://medium.com/@petervoss/my-ai-articles-f154c5adfd37



Peter Voss



From: Linas Vepstas <[email protected]<mailto:[email protected]>>
Sent: Friday, February 1, 2019 10:26 PM
To: AGI <[email protected]<mailto:[email protected]>>
Subject: Re: [agi] The future of AGI



Thanks Matt, very nice post! We're on the same wavelength, it seems. -- Linas



On Thu, Jan 31, 2019 at 3:17 PM Matt Mahoney 
<[email protected]<mailto:[email protected]>> wrote:

When I asked Linas Vepstas, one of the original developers of OpenCog
led by Ben Goertzel, about its future, he responded with a blog post.
He compared research in AGI to astronomy. Anyone can do amateur
astronomy with a pair of binoculars. But to make important
discoveries, you need expensive equipment like the Hubble telescope.
https://blog.opencog.org/2019/01/27/the-status-of-agi-and-opencog/

Opencog began 10 years ago in 2009 with high hopes of solving AGI,
building on the lessons learned from the prior 12 years of experience
with WebMind and Novamente. At the time, its major components were
DeStin, a neural vision system that could recognize handwritten
digits, MOSES, an evolutionary learner that output simple programs to
fit its training data, RelEx, a rule based language model, and
AtomSpace, a hypergraph based knowledge representation for both
structured knowledge and neural networks, intended to tie together the
other components. Initial progress was rapid. There were chatbots,
virtual environments for training AI agents, and dabbling in robotics.
The timeline in 2011 had OpenCog progressing through a series of
developmental stages leading up to "full-on human level AGI" in
2019-2021, and consulting with the Singularity Institute for AI (now
MIRI) on the safety and ethics of recursive self improvement.

Of course this did not happen. DeStin and MOSES never ran on hardware
powerful enough to solve anything beyond toy problems. ReLex had all
the usual problems of rule based systems like brittleness, parse
ambiguity, and the lack of an effective learning mechanism from
unstructured text. AtomSpace scaled poorly across distributed systems
and was never integrated. There is no knowledge base. Investors and
developers lost interest….




--
cassette tapes - analog TV - film cameras - you
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