Epstein Secrets

nd software engineer friends to one of my friends there -- Sander Olson, a blogger at the futurist blog "Next Big Future" and a tech angel investor (Sander is one of the forces behind the recent 3D printing Kickstarter success XX, for example). Sander saw the value in low-cost AI outsourcing and was int

every location on the planet. While IBM has put a supercomputing facility in Kenya, none of the major tech firms has moved into Ethiopia yet -- but OpenCog is there, gaining benefit from the large volume of tech graduates produced by Ethiopian universities, and at the same time producing a population of

some seed funding to enable the training of an initial programming team. And so iCog was born. Our idea was to have iCog do a mix of AI R&D on the OpenCog project, and commercial outsourcing for AI projects based around the world. The commercial projects would fund the AI R&D, and might also lead to e

eed for your article but you can pick and choose as you wish ;) By the way, technically, Epstein Foundation hasn't actually funded iCog Labs or the OpenCog researchers working there. Epstein Foundation has funded the OpenCog Hong Kong effort, which has been **very very very** much appreciated; but the

o Silva, Yang Ye, Shuo Chen, Michel Drenthe, Ted Sanders, Gustavo Gain and of course Nil and Cassio again.

g used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as described here. But if OpenCog continues to attract sufficient funding or volunteer in

the ideas presented here are not mere armchair speculation - they are currently being used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as d

validated or refuted via practice. (As a related note: here and there in this book, we will refer to the "current" CogPrime implementation (in the OpenCog framework); in all cases this refers to OpenCog as of late 2013.) To state one believes one knows a workable path to creating a human-level (and po

io Silva, Yang Ye, Shuo Chen, Michel Drenthe, Ted Sanders, Gustavo Gama and of course Nil and Cassio again.

ing used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as described here. But if OpenCog continues to attract sufficient funding or volunteer inte

at the ideas presented here are not mere armchair speculation — they are currently being used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as des

be validated or refuted via practice. (As a related note: here and there in this book, we will refer to the "current" CogPrime implementation (in the OpenCog framework); in all cases this refers to OpenCog as of late 2013.) To state one believes one knows a workable path to creating a human-level (and pot

ussion of semiotic learning according to Charles Sanders Peirce's theory of semiosis [Pei341, in which th

k for Natural Language Comprehension Now we move forward in the pipeline from syntax toward semantics. The NL comprehension framework provided with OpenCog at its inception in 2008 is RelEx, an English-language se- mantic relationship extractor, which consists of two main components: the dependency extra

rammar terms, this corresponds loosely to (S (NP The cat) (VP chased (NP a snake)) EFTA00624530 384 44 Natural Language Comprehension but the OpenCog linguistic pipeline makes scant use of this kind of phrase structure rendition (which is fine in this simple example; but in the case of complex sen