--- On Thu, 9/4/08, Valentina Poletti <[EMAIL PROTECTED]> wrote: >Ppl like Ben argue that the concept/engineering aspect of intelligence is >independent of the type of environment. That is, given you understand how >to make it in a virtual environment you can then tarnspose that concept >into a real environment more safely. > >Some other ppl on the other hand believe intelligence is a property of >humans only. So you have to simulate every detail about humans to get >that intelligence. I'd say that among the two approaches the first one >(Ben's) is safer and more realistic.
The issue is not what is intelligence, but what do you want to create? In order for machines to do more work for us, they may need language and vision, which we associate with human intelligence. But building artificial humans is not necessarily useful. We already know how to create humans, and we are doing so at an unsustainable rate. I suggest that instead of the imitation game (Turing test) for AI, we should use a preference test. If you prefer to talk to a machine vs. a human, then the machine passes the test. Prediction is central to intelligence. If you can predict a text stream, then for any question Q and any answer A, you can compute the probability distribution P(A|Q) = P(QA)/P(Q). This passes the Turing test. More importantly, it allows you to output max_A P(QA), the most likely answer from a group of humans. This passes the preference test because a group is usually more accurate than any individual member. (It may fail a Turing test for giving too few wrong answers, a problem Turing was aware of in 1950 when he gave an example of a computer incorrectly answering an arithmetic problem). Text compression is equivalent to AI because we have already solved the coding problem. Given P(x) for string x, we know how to optimally and efficiently code x in log_2(1/P(x)) bits (e.g. arithmetic coding). Text compression has an advantage over the Turing or preference tests in that that incremental progress in modeling can be measured precisely and the test is repeatable and verifiable. If I want to test a text compressor, it is important to use real data (human generated text) rather than simulated data, i.e. text generated by a program. Otherwise, I know there is a concise code for the input data, which is the program that generated it. When you don't understand the source distribution (i.e. the human brain), the problem is much harder, and you have a legitimate test. I understand that Ben is developing AI for virtual worlds. This might produce interesting results, but I wouldn't call it AGI. The value of AGI is on the order of US $1 quadrillion. It is a global economic system running on a smarter internet. I believe that any attempt to develop AGI on a budget of $1 million or $1 billion or $1 trillion is just wishful thinking. -- Matt Mahoney, [EMAIL PROTECTED] ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=111637683-c8fa51 Powered by Listbox: http://www.listbox.com
