--- James Ratcliff <[EMAIL PROTECTED]> wrote: > I still dont really follow this entire line of argument as well. > > > Youve given two main and not similar proposals here: > A. > > An AGI residing in your PC should be able to do the same > tasks as a human assistant, at least as fast and > as accurately. > > B. > > I proposed text compression and video compression as tests. For text, > the AGI must be able to losslessly compress 1 GB of text with no initial > training > A seems to be a general description of what an AGI is by many people and I > concur this would definitely pass as an AGI as well > What is B? You propose it as a test, but it seems that > 1. the test is merely a lossless compression of data back and forth. > 2. Something that would make A. better or faster or have a smaller KB, but > is not itself and AGI, or an AGI test?
I think that to solve A, you have to solve B. The reason I proposed B is that it is easier to test, and maybe this will speed development. Of course it is the capabilities of A that will ultimately prove its usefulness. > > A GOOD AGI should be able to store data effeciently, but conversely does a > program that stores data (compresses well) qualify as an AGI? > I would think this is a very limited AGI, and maybe just a helper > application for a KB instead. > I would say first we have to have a functional AGI according to A, and if > it requires a Google-data center to house the knowledge then so be it. > Later a great upgrade t oa working AGI would be to stick it on a PC, and > then down to an Ipod, but that would not seem a reasonable first requirement > to an AGI. > > James Ratcliff I think that future AGI will be vastly larger and more powerful than Google. Already today there is information and computing power on the Internet equivalent to thousands of human brains. But we don't know how to use it intelligently. The purpose of compression is to evaluate such systems. The first problem is understanding natural language. But what is "understanding" to a computer? One simple way to test understanding in humans is to see if they can predict successive words in a text stream. If a computer can do this, then it can also compress it. The second problem is vision. Lossy image compression already models the lower levels of visual perception in humans. It has to. To improve compression, it must model the higher levels, for example, to recognize the same face from different angles or different expressions. We are close to compressing text to 1 bpc. Google is also close to natural language understanding; it can answer simple questions up to a few words. But we are still very far from compressing video to 10 bps, and we are also very far from being able to search or classify video. -- Matt Mahoney, [EMAIL PROTECTED] ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=fabd7936
