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Comment Re:There are ideas. Here's one. (Score 1) 230

Agreed - the early days of neural nets surprised a lot of people with their ability to "learn" optical character recognition. Then they kind of fizzed out. Numenta is doing some interesting stuff with video processing, but it's a slow grinding progress, not an explosive revolution like Moore's Law. The "nets" can be massive for low cost now, but there's apparently not much (orders of magnitude) more to be gotten from them.

Not that this particular theory is going anywhere, but a fun one I've heard is a sort of "survival of the fittest pattern replication" where an "event" is encoded as a repeating pattern of discharges. Multiple (hundreds even thousands) of groups of neurons take up variations of the theme and the dominant pattern(s) are the ones passed on to the next level of processing, where a similar process occurs - transforming the previous levels' patterns into new patterns on the current level. It's a departure from the resource starved ideas of early digital processing where you have one fragile chance to get the right answer processed through the system. Instead, hordes of parallel processing units reach consensus, with lots of potential outcomes considered and discarded in favor of the eventual result.

Some kind of departure, as different as "fittest patterns" is from AND and OR gates, is likely to be the next big step.

Comment Re:There are ideas. Here's one. (Score 1) 230

I'd say that the neural net model is "good enough" for maze navigation performance - if the net is programmed with "cat avoidance" then it, too, can deal with the cat: for purposes of navigation. For purposes of optical recognition of "cat" and evolving to learn why they should be avoided, that's probably a stretch for neural nets.

In the end, I would expect AI to do things differently, otherwise we've just replicated the wetware. Doing things using the same internal mechanisms might be a shortcut to achieving "artificial cognition", but I think there's better odds of finding a novel approach first.

Are we at ground zero? Absolutely not. But 40 years in, I don't think we're even 10% along the road to human level artificial intelligence. But, study your Kurzweil, the next 90% could come in much less than 40 years.

Comment Re:There are ideas. Here's one. (Score 1) 230

My point in this area would be: does our knowledge allow us to generate desired outcomes in novel subjects with any level of certainty?

For instance: we know with great certainty that you can stimulate the optic nerve and cause the subject to "see things" (and also: not see things that are really there).

On the other hand, with respect to cognition, can we do anything that simulates (reconstructs) a biological cognition system?

Can we learn a maze the way a rat does? I think so. Neural nets with reward and punishment inputs can perform approximately the same.

Can we process language the way a person does? I think not. We've had the eliza program for decades, and doubtless there are many around today that are orders of magnitude complex, but can they learn, adapt, and handle novel situations the way (some) people can?

Comment Daily adjustments? (Score 1) 233

Instead of having a special case every few years, how about going ahead and making a millisecond of adjustment every day as needed? The adjustments could start with 0 or 1 milliseconds, and as the oceans slosh us ever slower, we could start making 1 or 2 millisecond adjustments every day at midnight.

Would also keep the stars better aligned to the official time.

Comment Re:If it ever takes off, no stopping it (Score 1) 62

On the spread of genetic modification:

Whether the agent is engineered by Skynet, Osama II, or the NSA, somebody (anybody) could create a virus that sweeps the world like an annoying, seemingly harmless, flu bug. One that makes the children of every couple who were ever infected have blue eyes, or fingernails that glow in the dark after they eat peanuts, or other things....

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