A.I. and Robotics Take Another Wobbly Step Forward

CWmike writes to tell us that artificial intelligence and robotics have made another wobbly step forward with the most recent robot from Stanford. "Stair" is one of a new breed of robot that is trying to integrate learning, vision, navigation, manipulation, planning, reasoning, speech, and natural language processing. "It also marks a transition of AI from narrow, carefully defined domains to real-world situations in which systems learn to deal with complex data and adapt to uncertainty. AI has more or less followed the 'hype cycle' popularized by Gartner Inc.: Technologies perk along in the shadows for a few years, then burst on the scene in a blaze of hype. Then they fall into disrepute when they fail to deliver on extravagant promises, until they eventually rise to a level of solid accomplishment and acceptance."

Comments

Re:Hype?

[sleeponthemic]

Robotics is a lot like graphical photorealism/virtual reality. People have been predicting it for decades, but the actual nuance of such an achievement is much more complex than most are able to comprehend. As such, we're perpetually surrounded by the hype.

Re:People perception

[religious freak]

But being that a standard computer has the brain power of a bug, it isn't surprising that AI meets the hype.

I was thinking it was a clever use of the first part of the last sentence to invalidate the last part of the last sentence.

Surely there's money in this?

[Lexta]

As an undergraduate Computer Engineer who intends to major in AI I would be really interested in knowing if anyone knew whether the companies mentioned in this article (Google, Walmart etc...) actually do hire people with a specialization in AI? And if so how do u get recognized?? Or is it all just copied and pasted from researchers who work in all the Universities they mentioned?
I guess the root of my question is, by pursuing AI are you pushing yourself into becoming an academic for the rest of your life?

Re:People perception

[im_thatoneguy]

It could even be argued that the ability to navigate a room is the same set of problem solving skills that informs all other intelligence.

It's spacial understanding combined with analyzing the capabilities of the agent to complete the task. Include a door and you have extremely complex problem solving and learning abilities.

Hyper Cycle

[computechnica]

We are still waiting for V.R. to reemerge from the Hype Cycle.

The three types

[linhares]

Disclosure: I am a Hofstadterian, so I am biased here.

There are basically three types of AI-peoples: The neverlands, the hype masters, and the hope monks. The neverlands, like Searle, deny that intelligence is a product of information-processing. Searle has made it into a sport the claims that AI will never happen because it does not have the "causal powers of the brain".

Then there are these types, like those reported here. Hypeware at its best. Look, it's alive, it's (F*CKING GASP) becoming self aware, etc hype hype hype ad-nauseum. But look at its innards _very_ closely, and it's pretty empty in there.

There are so many pitfalls involved that it's impossible to mention all faulty premises involved in each project. But just for starters, consider this: when we program a machine to deal with the number 2, it usually goes into binary form 10 and there it stays, ready for manipulation. But how plausible is this psychologically? NOT AT ALL! When _we think_ of a "2", hordes of disparate, subliminar images come to mind, such as the gestalt of the digit, the sound of it, the fact that it's a prime (if you're math inclined), a couple (if you're a therapist), even-ness, odd-ness, the words "two" "too", and a huge number of semi-visible mental imagery.

Whenever you see a hyped AI project, just consider how it deals with the numeral 2. Most likely it's a _fake_. The process through which it goes through is not psychologically plausible. Which means that it will fail to understand human concepts.

Some projects with machine learning actually make it a habit of finding _meaning_ in highly correlated words (i.e., words that tend to occur together in documents). That is a _joke_. Meaning NEVER comes from correlation. If it did, "lawyer" and "telephone" would have much more to do than "lawyer" and "vampire", or "politician" and "scumbag".

Sorry for the rent, but I work hard to understand fucking hard issues and to see these folks being slashdotted with nothing to show for just begs for a rant. If you want to see really serious research, take a look a Douglas Hofstadter's "Fluid Concepts and Creative Analogies" and/or google for Kemp's MIT thesis.

Re:The three types

[Simon Brooke]

Disclosure: I am a Hofstadterian, so I am biased here.

There are basically three types of AI-peoples: The neverlands, the hype masters, and the hope monks. The neverlands, like Searle, deny that intelligence is a product of information-processing. Searle has made it into a sport the claims that AI will never happen because it does not have the "causal powers of the brain".

Then there are these types, like those reported here. Hypeware at its best. Look, it's alive, it's (F*CKING GASP) becoming self aware, etc hype hype hype ad-nauseum. But look at its innards _very_ closely, and it's pretty empty in there.

I think you'd find that if we could look into the functioning of the human mind in as much detail as we can look into an AI program, you'd find that it's pretty empty in there, too. I believe that intelligence is an emergent property of a lot of fairly simple processes. Yes, that's a matter of belief, not of proof.

There are so many pitfalls involved that it's impossible to mention all faulty premises involved in each project. But just for starters, consider this: when we program a machine to deal with the number 2, it usually goes into binary form 10 and there it stays, ready for manipulation. But how plausible is this psychologically? NOT AT ALL! When _we think_ of a "2", hordes of disparate, subliminar images come to mind, such as the gestalt of the digit, the sound of it, the fact that it's a prime (if you're math inclined), a couple (if you're a therapist), even-ness, odd-ness, the words "two" "too", and a huge number of semi-visible mental imagery.

Whenever you see a hyped AI project, just consider how it deals with the numeral 2. Most likely it's a _fake_. The process through which it goes through is not psychologically plausible. Which means that it will fail to understand human concepts.

A machine does not have to reproduce the mechanisms of the human mind in order to display intelligence; it has to emulate the performance. If the inputs are similar and the outputs are similar what happens in the middle is unimportant.