141–150 of 176 posts
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General learning is uncomputable, it's called Solomonoff induction. You don't need general learning, you need something at least as powerful as the mess in a human brain.
What if the mess in the human brain is powered by an uncomputable transcendent mind?
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1) Is first order logic not expressive enough for some use cases? Do you need higher order logic? 2) Where can I found a complete explanation of why Cyc hasn't yet been enough to build true natural language understanding, which technical difficulties needs to be solved? Examples would be welcome. 3) Is would be really nice if you showed progress in real time and allowed community to contribute intellectually. You cou…
I'm also a Cycorp employee, so I can say a little bit at least about (1) and (2). 1) We often use HOL. CycL isn't restricted to first order logic and we often reason by quantifying over predicates. 2) I don't know where you could read an explanation of it, other than the general problem that NLU is hard. It is something people at the company are interested in, though, and some of us think Cyc can play a big role in N…
1) What do you think about hybrid approach: hypergraphs + large-scale NLP models (transformers)? 2) How far we're from real self-evolving cognitive architectures with self-awareness features? Is it a question of years, months, or it's already solved problem? 3) Does it make sense to use embeddings like https://github.com/facebookresearch/PyTorch-BigGraph to achieve better results? 4) Why Cycorp decided to limit commu…
Doug Lenat is very much still active in the project. He doesn't do as much work building the ontology, but he plays a role in how various projects develop and provides a lot of feedback.
Which6is the most promising AGI project according to you?
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1) Do you think it's possible that Cyc would lead to AGI? 2) Do you think it's possible that Cyc would lead to AI advances that are impressive to the layman like AlphaGo or GPT-2?
These answers are very personal to me. I joined Cycorp because Doug Lenat sold me on it being a more viable path toward something like AGI than I had suspected when I read about it. I left for a number of reasons (e.g. just to pursue other projects) but a big one was slowly coming to doubt that. I could be sold on the idea that Cyc or something Cyc-like could be a piece of the puzzle for AGI. I say "Cyc-like" because…
* it doesn't represent the full potential of something that could be built using the lessons learned along the way.*
the lessons learned What are those lessons? I would like to benefit from them instead to reproduce your past mistakes.
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OK, what experiments would you design to test whether AGI is possible? Given the decades (centuries?) of thought that have gone into the issue, I'm sure a set of experiments would be valuable.
If humans can solve problems that require more computational resources than exist in the universe, then AGI is not possible. I have run one experiment to demonstrate this.
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1) Do you think it's possible that Cyc would lead to AGI? 2) Do you think it's possible that Cyc would lead to AI advances that are impressive to the layman like AlphaGo or GPT-2?
These answers are very personal to me. I joined Cycorp because Doug Lenat sold me on it being a more viable path toward something like AGI than I had suspected when I read about it. I left for a number of reasons (e.g. just to pursue other projects) but a big one was slowly coming to doubt that. I could be sold on the idea that Cyc or something Cyc-like could be a piece of the puzzle for AGI. I say "Cyc-like" because…
I was visiting MCC during the startup phase and Bobby Inman spent a little time with me. He had just hired Doug Lenat, but Lenat was not there yet. Inman was very excited to be having Lenat on board. (Inman was on my board of directors and furnished me with much of my IR&D funding for several years.)
From an outsider’s perspective, I thought that the business strategy of Open Cyc made sense, because many of us outside the company had the opportunity to experiment with it. I still have backups of the last released version, plus the RDF/OWL releases.
Personally, I think we are far from achieving AGI. We need some theoretical breakthroughs (I would bet on hybrid symbolic, deep learning, and probabilistic graph models). We have far to go, but as the Buddha said, enjoy the journey.
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If humans can solve problems that require more computational resources than exist in the universe, then AGI is not possible. I have run one experiment to demonstrate this.
What was the experiment you ran?
Knowledge bases should work in principle. There are many issues with filling them manually: a) the schema/ontology/conceptual framework is not guaranteed to be useful especially when done with no specific application in mind b) high cost of adding each fact with little marginal benefit etc. But I don't think it outweighs the issues of "pure" machine learning that much: poor introspection, capricious predictability of…
I wonder what would have happened with Cyc if twenty years ago a funding manager at DARPA had provided incentives to have Cyc entirely open. This might have led to major code refactoring, many more contributions, etc. even understanding that adding common sense knowledge to Cyc requires special skills and education.
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Yes, I understand computationalism does not imply physicalism, but physicalism does imply computationalism. Thus, if computationalism is empirically refuted, then physicalism is false. I know the Lucas Godel incompleteness theorem type arguments. Whether successful or not, the counter arguments are certainly fallacious. E.g. just because I form a halting problem for myself does not mean I am not a halting oracle for…
> physicalism does imply computationalism That's not true either. There are plenty of materialists who think the universe is not computable, thus it's totally possible to believe that the mind is not computable despite being entirely physical.
So, if a macro phenomena, i.e. the human mind, is uncomputable, then it is not emergent from the low computable physical substrate.
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But there might be even better approaches if human intelligence is not computable. E.g. if the mind is a halting oracles that can get us all kinds of cool things.
If the mind were a halting oracle I don't think most of our open problems in mathematics would be.