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The BS-Industrial Complex of Phony A.I.

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Re: The BS-Industrial Complex of Phony A.I.

#351

This happened right before the first AI Winter in the late 80s: AI (in the form of expert systems) solved a number of hard problems and was hyped as being able to solve every problem. Reality set in when we figured out: 1. It didn't scale and 2. Getting 80% of the problem solved was easy, but getting that last 20% was very, very hard. Maybe several orders of magnitude harder than the first 80%. Nowadays we don't seem…

The best self driving systems do not have trouble dealing with bicyclists. The one time it happened with Uber was a combination of user errors starting with a very serious misconfiguration of the system.

Also, AGI and self-driving cars have almost nothing in common. Driving cars is a very narrow AI task.

Re: The BS-Industrial Complex of Phony A.I.

#352

Earlier quoted context omitted.

The examples I gave are classic AI algorithms that are very easy to look up on wikipedia. They do not compute any statistics. I'm not sure what you mean about "neuron weights that are statistically optimised". Modern-era, deep neural nets train their weights with backpropagation, which is basically an application of the chain rule, from calculus. They do not use statistics for that. For example, calculating the mean…

He means that neural networks are applied statistics in that they solve a statistical regression problem. It's not conceptually different from classical methods of regression like least squares. The phrase "statistically optimized" is certainly a funky one, but regression is certainly as much a part of statistics as the two problems you mentioned.

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Re: The BS-Industrial Complex of Phony A.I.

#353

Earlier quoted context omitted.

The examples I gave are classic AI algorithms that are very easy to look up on wikipedia. They do not compute any statistics. I'm not sure what you mean about "neuron weights that are statistically optimised". Modern-era, deep neural nets train their weights with backpropagation, which is basically an application of the chain rule, from calculus. They do not use statistics for that. For example, calculating the mean…

He means that neural networks are applied statistics in that they solve a statistical regression problem. It's not conceptually different from classical methods of regression like least squares. The phrase "statistically optimized" is certainly a funky one, but regression is certainly as much a part of statistics as the two problems you mentioned.

That doesn't sound like what the OP was saying.

Re: The BS-Industrial Complex of Phony A.I.

#354

In my opinion the term intelligence itself is misplaced for machine learning tasks. Every problem that is solved with ML and "big data" appears to me to be a perception problem (which wouldn't be surprising because the mechanism is inspired by human vision, not cognition, which it lends itself to naturally). As a specific example, a few months ago or so openai released their text generation tool and branded it as "to…

Right, that tool makes gibberish and didn't understand much of anything.

AI research actually started by focusing on symbolic AI but eventually it was found to be too difficult to define all of the symbols. See the Cyc project.

AGI as a field aside from narrow AI/narrow ML has been making useful but not mind-blowing progress for decades. The sidebar and recent posts/post history on Reddit r/agi has useful links for learning about the field. Also more and more posts on r/machinelearning are providing more general purpose tools that address some problems like better semantic understanding.

There is a promising strain of research that is focusing on core AGI requirements. One of the big challenges is bridging the gap between low level sensory information and high level concepts. This is known as the symbol grounding problem. In my mind the approaches tackling that type of challenge have a lot of promise. And the amount of research in that area is growing.

Re: The BS-Industrial Complex of Phony A.I.

#355
post #327
post #248

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With the same amount of training/data as NNs? I doubt it...

Do you take into account billions of years of training due to evolution?

Technically that’s network architecture, not training data... admittedly though humans are “pre-trained” from birth.

Re: The BS-Industrial Complex of Phony A.I.

#356
post #252

Earlier quoted context omitted.

>> Accidentally (?) she managed to create the best representation of AI I have seen in art: all that counts is that you call it AI even if it is a simple algorithm. Backpropagation, which most researchers will agree is an AI algorithm, is a "simple algorithm". So are many other AI algorithms, some of which are simple enough to be understood so well that most people don't recognise them as AI anymore: search algorithm…

> Backpropagation, which most researchers will agree is an AI algorithm, is a "simple algorithm". As time rolls on and we see more articles like this one calling out the "AI BS" - which I agree should be called out... I worry that a new "winter" will set in, and funding will be cut, and research towards how biological neural networks actually work vis-a-vis artificial neural networks will suffer. Because from what I…

a lot of people think it will mirror how the internet was. Lots of hype, people threw money at it while not really understanding it but when the profits didn't roll in, the winter came. People forget how tech was desolate, and it wasn't just 2001. probably from 2001 to somewhere in 2005? Anyhow, those who figured out how to make use of the internet well were incredibly successful. Once the winter was over tech has been among the hottest industries for a long time.

AI might end up the same, enter a winter. people will talk about how silly endevours into AI where, but a few companies will really figure it out and a huge explosion will occur and people will wonder how anyone did anything without AI. something like that

for those who forgot what that winter was like: 1999 2:10: your not a pure internet company... (insinuating thats bad) https://www.youtube.com/watch?v=GltlJO56S1g&t=316s

.com bubble burst somewhere March, 2001

2002 2:22: netflix represents one of the few success stories of an otherwise desolute tech sector https://www.youtube.com/watch?v=YBLAwGhyV5k

2004 who in their right mind brings a company to market in the doldrums of august in a down tech... https://www.youtube.com/watch?v=HxOoeCHc47Q

Re: The BS-Industrial Complex of Phony A.I.

#357

Earlier quoted context omitted.

>> The list of discrete tasks (games, decision making once the parameters are defined) a computer can't do is a very short list. > I'd be interested in knowing what coungerarguments the people downvoting this comment might know of, which I apparently don't. I didn't downvote, but I will cite artistic endeavours. How long until a film crew of computers can shoot, edit and score a documentary or film that would be inte…

I don't think that you need to limit creativity to the arts, which is unfair to machines because art really depends on human emotional quirks. That is even kind of the whole point of art. What about technical inventions? Can AI invent, let's say, the process to produce aluminum? Or planar semiconductors? Or a rocket engine? These are also creative works. (I do think that AGI soon claims are rubbish)

Agree completely, just used art as its an easy example.

Re: The BS-Industrial Complex of Phony A.I.

#358

Earlier quoted context omitted.

So like, a sociopath, then? I guess we do know that those can exist.

Yeah, sure. The orthogonality thesis essentially implies than a GAI randomly plucked out of space of possible minds will likely be considered sociopathic by our standards. That is, if we can comprehend its thinking at all. "Not sociopath" is a very particular set of values.

> a GAI randomly plucked out of space of possible minds

Sorry, but I don't think you have any rational basis for imagining what the "space of possible minds" represents. The only minds with human-level intelligence we know of are human minds that have (with variation) human values.

The claim you're making is analogous to saying "any extraterrestrial life we find won't be carbon-based because out of the space of all possible substrates for life, carbon is a very particular one", but that's an ill-founded supposition because we have a sample of N=1 and maybe carbon-based life is the only kind of life there is.

Maybe a true GAI mind will be "like us", maybe it won't be, but we don't have anywhere near enough data to speak with confidence about it.

Re: The BS-Industrial Complex of Phony A.I.

#359

Earlier quoted context omitted.

If navigating the world were that easy we wouldn't be (non-A)GI. The bulb on the end of our spine doesn't use 1/5th of our oxygen (or whatever huge amount it is) intake because it makes our foreheads look sexy. An auto-auto (I'm using that term unabashedly for "self-driving cars", you can too) has to be able to perceive and understand that the car in the next lane with the mattress poorly tied down might, at any mome…

That bulb is there because of politics, and because speak sounds sexy. There are many animals capable of navigating the world even better than us (most fly, for obvious reasons) that don't have anything near the size of our brains.

We don't employ orangutans as chauffeurs. ;-P

On second thought I bet you could make a decent auto-auto out of a dog's brain... https://villains.fandom.com/wiki/Rat_Things_(Snow_Crash)

Re: The BS-Industrial Complex of Phony A.I.

#360
post #69

Earlier quoted context omitted.

Agreed. This paragraph (in an otherwise insightful essay) was particularly jarring: "Remarkable things are happening in the field of artificial (general) intelligence. Deep learning algorithms have proven to be better than humans at spotting lung cancer." This is very emphatically narrow AI.

Pattern matching is not intelligence. Calling it AI rather than ML is disingenuous. Tell me when a generic algorithm can solve many different games on different environments at the very least.

Pattern matching is certainly intelligence - classical AI was focused on identifying patterns and reacting to them with techniques like decision trees.

You can make a fairly convincing argument that intelligence is nothing more than a hierarchical system of pattern matchers.

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