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Ray Kurzweil joins Google

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141–150 of 170 posts

Re: Ray Kurzweil joins Google

#141

Earlier quoted context omitted.

For several hundred years, inventors tried to learn to fly by creating contraptions that flapped their wings, often with feathers included. It was only when they figured out that wings don't have to flap and don't need feathers that they actually got off the ground. It's still flight, even if it's not done like a bird. Just because nature does it one way doesn't mean it's the only way. (On a side note, multilayer per…

> aren't all that different from how neurons work Nobody knows how neurons actually work: http://www.newyorker.com/online/blogs/newsdesk/2012/11/ibm-b... . We are missing vital pieces of information to understand that. Show me your accurate C. Elegans simulation and I will start to believe you have something. Perhaps in a hundred years, this is the argument: for several hundred years, inventors tried to learn to buil…

> Show me your accurate C. Elegans simulation and I will start to believe you have something.

http://openworm.org/

If you think they are insufficiently accurate, submit a pull request.

Re: Ray Kurzweil joins Google

#142
post #104

Earlier quoted context omitted.

> I just can't see Kurzweil being in the same league as Peter Norvig. The problem with Peter Norvig is that he comes from a mathematical background and is a strong defender the use of statistical models that have no biological basis.[1] While they have their use in specific areas, they will never lead us to a general purpose strong AI. Lately Kurzweil has come around to see that symbolic and bayesian networks have be…

For several hundred years, inventors tried to learn to fly by creating contraptions that flapped their wings, often with feathers included. It was only when they figured out that wings don't have to flap and don't need feathers that they actually got off the ground. It's still flight, even if it's not done like a bird. Just because nature does it one way doesn't mean it's the only way. (On a side note, multilayer per…

> For several hundred years, inventors tried to learn to fly by creating contraptions that flapped their wings...

To quote Jeff Halwkings "This kind of ends-justify-the-means interpretation of functionalism leads AI researchers astray. As Searle showed with the Chinese Room, behavioral equivalence is not enough. Since intelligence is an internal property of a brain, we have to look inside the brain to understand what intelligence is. In our investigations of the brain, and especially the neocortex, we will need to be careful in figuring out which details are just superfluous "frozen accidents" of our evolutionary past; undoubtedly, many Rube Goldberg–style processes are mixed in with the important features. But as we'll soon see, there is an underlying elegance of great power, one that surpasses our best computers, waiting to be extracted from these neural circuits.

...

For half a century we've been bringing the full force of our species' considerable cleverness to trying to program intelligence into computers. In the process we've come up with word processors, databases, video games, the Internet, mobile phones, and convincing computer-animated dinosaurs. But intelligent machines still aren't anywhere in the picture. To succeed, we will need to crib heavily from nature's engine of intelligence, the neocortex. We have to extract intelligence from within the brain. No other road will get us there. "

As someone with a strong background in Biology who took several AI classes at an Ivy League school, I found all of my CS professors had a disdain for anything to do with biology. The influence of these esteemed professors and the institution they perpetuate is what's been holding the field back. It's time people recognize it.

Re: Ray Kurzweil joins Google

#143
post #94

Earlier quoted context omitted.

I just can't see Kurzweil being in the same league as Peter Norvig. Sure, he did some interesting work a long time ago, before he got weird. I can't see this working out well for Google, unless they just want a famous figurehead.

I'm more reluctant to trash Kurzweil, but this image hiring policy is taking on the look of some sort of bizarre Victorian menagerie where they keep old famous computer scientists in wrought iron cages for Googlers' amusement. It's like the Henry Ford museum, but they're collecting people. That's more than a little weird.

Much as Microsoft did in the 1990s.

And AT&T in the 1960s.

Re: Ray Kurzweil joins Google

#144
post #85

Earlier quoted context omitted.

I think it's pretty obvious, but let me quote Neal Stephenson: >I can never get past the structural similarities between the singularity prediction and the apocalypse of St. John the Divine. This is not the place to parse it out, but the key thing they have in common is the idea of a rapture, in which some chosen humans will be taken up and made one with the infinite while others will be left behind. Poll Americans (…

> Poll Americans (most of whom are Christian). Close to half will tell you the end of the world and thus the rapture is going to happen in their own lifetime. Christians have been believing that the rapture was around the corner for literally the last 2000 years. Arrogant if you ask me. A bit of theological nitpicking: the notion of a pre-millenial 'Rapture' is a late development in Protestant theology that appears f…

I guess I was grouping the second coming in there too. Good point.

Re: Ray Kurzweil joins Google

#145
post #104

Earlier quoted context omitted.

> I just can't see Kurzweil being in the same league as Peter Norvig. The problem with Peter Norvig is that he comes from a mathematical background and is a strong defender the use of statistical models that have no biological basis.[1] While they have their use in specific areas, they will never lead us to a general purpose strong AI. Lately Kurzweil has come around to see that symbolic and bayesian networks have be…

Obviously Google translate is not error free, nor is any statistical translation system going to be comparable to a human translator in the very near future, but you're underestimating the current development of statistical translation. Granted, I'm not a native speaker but I think "I need to meet up" is not even a sentence with proper grammar. Underlying model probably predicted something like meeting (satisfying) r…

"We need to meet up" also translates incorrectly "我们需要满足". In fact, I did not originally use a fragment, I wrote a full sentence that Google repeatedly incorrectly translated. I only used a fragment here to simply my example.

To avoid the wrath of the Google fan boys, a better example would have been the pinnacle of statistical AI : The category was "U.S. Cities" and the clue was: "Its largest airport is named for a World War II hero; its second largest for a World War II battle." The human competitors Ken Jennings and Brad Rutter both answered correctly with "Chicago" but IBM's supercomputer Watson said "Toronto."

Once again, Watson, a probability based system failed where real intelligence would not.

Google has done an amazing job, with their machine translation considering they cling to these outdated statistical methods. And just like with speech recognition has found out over the last 20 years, they will continue to get diminishing returns until they start borrowing from nature's own engine of intelligence.

Re: Ray Kurzweil joins Google

#146
post #142

Earlier quoted context omitted.

For several hundred years, inventors tried to learn to fly by creating contraptions that flapped their wings, often with feathers included. It was only when they figured out that wings don't have to flap and don't need feathers that they actually got off the ground. It's still flight, even if it's not done like a bird. Just because nature does it one way doesn't mean it's the only way. (On a side note, multilayer per…

> For several hundred years, inventors tried to learn to fly by creating contraptions that flapped their wings... To quote Jeff Halwkings "This kind of ends-justify-the-means interpretation of functionalism leads AI researchers astray. As Searle showed with the Chinese Room, behavioral equivalence is not enough. Since intelligence is an internal property of a brain, we have to look inside the brain to understand what…

I'll bite. Tell us, concretely, what is to be gained from a biological approach.

Honestly I imagine we'd find more out from philosophers helping to spec out what a sentient mind actually is than we would from having biologists trying to explain imperfect implementations of the mechanisms of thought.

Re: Ray Kurzweil joins Google

#147
post #134
post #98

Earlier quoted context omitted.

I don't mean to pick on you (and I certainly didn't downvote you), but you seem like a posterboy for just how easy it is to take inventions and innovation for granted after the fact. I find it instructive to occassionally go to Youtube and load up commericals for Windows 95, 3.1, the first Mac, etc., or even to dust off and boot up an old computer I haven't touched for decades. Not to get too pretentious, but it's a…

"Predicting that self-driving cars would occur in ten years in the late 90s is pretty extraordinary" There have been predictions of self-driving cars for more than half a century. It's in Disney's "Magic Highway" from 1958, for example. There was an episode of Nova from the 1980s showing CMU's work in making a self-driving van. Researching now, Wikipedia claims: "In 1995, Dickmanns´ re-engineered autonomous S-Class M…

Man, those are actually some pretty tame predictions, especially if most of them were already in some form of production. I guess the future ain't all it's cracked up to be.

Re: Ray Kurzweil joins Google

#148
post #142

Earlier quoted context omitted.

> For several hundred years, inventors tried to learn to fly by creating contraptions that flapped their wings... To quote Jeff Halwkings "This kind of ends-justify-the-means interpretation of functionalism leads AI researchers astray. As Searle showed with the Chinese Room, behavioral equivalence is not enough. Since intelligence is an internal property of a brain, we have to look inside the brain to understand what…

I'll bite. Tell us, concretely, what is to be gained from a biological approach. Honestly I imagine we'd find more out from philosophers helping to spec out what a sentient mind actually is than we would from having biologists trying to explain imperfect implementations of the mechanisms of thought.

I'm short on time, so please forgive my rushed answer.

It will deliver on all of the failed promises of past AI techniques. Creative machines that actually understand language and the world around it. The "hard" AI problems of vision and commonsense reasoning will become "easy". You need to program a computer the logic that all people have hands or that eyes and noses are on faces. They will gain this experiences and they learn about our world, just like their biological equivalent, children.

Here's some more food for thought from Jeff Hawkins:

"John Searle, an influential philosophy professor at the University of California at Berkeley, was at that time saying that computers were not, and could not be, intelligent. To prove it, in 1980 he came up with a thought experiment called the Chinese Room. It goes like this:

Suppose you have a room with a slot in one wall, and inside is an English-speaking person sitting at a desk. He has a big book of instructions and all the pencils and scratch paper he could ever need. Flipping through the book, he sees that the instructions, written in English, dictate ways to manipulate, sort, and compare Chinese characters. Mind you, the directions say nothing about the meanings of the Chinese characters; they only deal with how the characters are to be copied, erased, reordered, transcribed, and so forth.

Someone outside the room slips a piece of paper through the slot. On it is written a story and questions about the story, all in Chinese. The man inside doesn't speak or read a word of Chinese, but he picks up the paper and goes to work with the rulebook. He toils and toils, rotely following the instructions in the book. At times the instructions tell him to write characters on scrap paper, and at other times to move and erase characters. Applying rule after rule, writing and erasing characters, the man works until the book's instructions tell him he is done. When he is finished at last he has written a new page of characters, which unbeknownst to him are the answers to the questions. The book tells him to pass his paper back through the slot. He does it, and wonders what this whole tedious exercise has been about.

Outside, a Chinese speaker reads the page. The answers are all correct, she notes— even insightful. If she is asked whether those answers came from an intelligent mind that had understood the story, she will definitely say yes. But can she be right? Who understood the story? It wasn't the fellow inside, certainly; he is ignorant of Chinese and has no idea what the story was about. It wasn't the book, 15 which is just, well, a book, sitting inertly on the writing desk amid piles of paper. So where did the understanding occur? Searle's answer is that no understanding did occur; it was just a bunch of mindless page flipping and pencil scratching. And now the bait-and-switch: the Chinese Room is exactly analogous to a digital computer. The person is the CPU, mindlessly executing instructions, the book is the software program feeding instructions to the CPU, and the scratch paper is the memory. Thus, no matter how cleverly a computer is designed to simulate intelligence by producing the same behavior as a human, it has no understanding and it is not intelligent. (Searle made it clear he didn't know what intelligence is; he was only saying that whatever it is, computers don't have it.)

This argument created a huge row among philosophers and AI pundits. It spawned hundreds of articles, plus more than a little vitriol and bad blood. AI defenders came up with dozens of counterarguments to Searle, such as claiming that although none of the room's component parts understood Chinese, the entire room as a whole did, or that the person in the room really did understand Chinese, but just didn't know it. As for me, I think Searle had it right. When I thought through the Chinese Room argument and when I thought about how computers worked, I didn't see understanding happening anywhere. I was convinced we needed to understand what "understanding" is, a way to define it that would make it clear when a system was intelligent and when it wasn't, when it understands Chinese and when it doesn't. Its behavior doesn't tell us this.

A human doesn't need to "do" anything to understand a story. I can read a story quietly, and although I have no overt behavior my understanding and comprehension are clear, at least to me. You, on the other hand, cannot tell from my quiet behavior whether I understand the story or not, or even if I know the language the story is written in. You might later ask me questions to see if I did, but my understanding occurred when I read the story, not just when I answer your questions. A thesis of this book is that understanding cannot be measured by external behavior; as we'll see in the coming chapters, it is instead an internal metric of how the brain remembers things and uses its memories to make predictions. The Chinese Room, Deep Blue, and most computer programs don't have anything akin to this. They don't understand what they are doing. The only way we can judge whether a computer is intelligent is by its output, or behavior.

Re: Ray Kurzweil joins Google

#149

The problem is, and I don't want to be mean about it, is that Kurzweil is a crackpot and charlatan. This is not to take away from his intelligence or his technical achievements, which are indisputable. However, even Nobel prize winners can be outright crackpots and crazies (Nobel disease). I don't know exactly what Google's motives are here, I suspect it's something less than actually bringing about some of his, let'…

If I were Google, I would hire him just to mumble into a recorder all day. Then have a small team decipher and escalate possible ideas.

Re: Ray Kurzweil joins Google

#150
post #148

Earlier quoted context omitted.

I'll bite. Tell us, concretely, what is to be gained from a biological approach. Honestly I imagine we'd find more out from philosophers helping to spec out what a sentient mind actually is than we would from having biologists trying to explain imperfect implementations of the mechanisms of thought.

I'm short on time, so please forgive my rushed answer. It will deliver on all of the failed promises of past AI techniques. Creative machines that actually understand language and the world around it. The "hard" AI problems of vision and commonsense reasoning will become "easy". You need to program a computer the logic that all people have hands or that eyes and noses are on faces. They will gain this experiences and…

First, I don't feel this answers angersock's question concerning concrete applications of cognitive neuroscience to artificial intelligence.

Second, despite running into it time and again over the years, Searle's Chinese room argument still does not much impress me. It seems to me clear that the setup just hides the difficulty and complexity of understanding in the magical lookup table of the book. Since you've probably encountered this sort of response, as well as the analogy from the Chinese room back to the human brain itself, I'm curious what you find useful and compelling in Searle's argument.

I remain interested in biological approaches to cognition and the potential for insights from brain modelling, but I don't see how it's useful to disparage mathematical and statistical approaches, especially without concrete feats to back up the criticism.

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