Rather, genius is the subset of crazy recognized by society as useful. The moment of recognition is the point at which it becomes venerated instead of derided.

That's roughly correct, but IIRC Ray sold that company 30 years ago; it later went on to buy Nuance, and subsequently quite a few more speech-related companies before hooking up with Apple for Siri. So while your comment is correct, I'd be surprised if any of that initial technology was actually being used for Siri.

Google employees tend to be harsher on our current achievements than the general public. :-)

Thinking about it, I dont think so. Because if you ask google and also ask a folk that is an expert on something or loves the subject, the person will give you much better information and links.

You're all sorta right. I worked at Singularity University for 2 years. They do 2 things: 1. Educate fabulously wealthy people in expensive executive programs 2. Use that money to put on a YC-esk incubator during the program where people come to build companies that use the technology of their sponsors. Google was one of the first sponsors. Peter Norvig was on the Faculty for a couple years. So was Astro Teller who heads their special projects (Google X).

> Why would this not in alignment w/ Google's aim for such a position?

Singularity University helps you meet people who can help you facilitate engineering feats, in the sense that more money helps you facilitate engineering feats. That's okay in my book.

But, you're not going to end up with a working knowledge of mechanical engineering or computational neuroscience by hanging out at the Singularity University lectures.

People are surprised about at how far "Director of Engineering" can skew in that direction, they aren't surprised that Google is interested in the future.

> The people who attend the university are CEOs, CTOs... Directors of Engineering, etc. It's not for fringe kooks

A much larger percentage of CEOs, CTOs, D of E's depend on psychics and astrologers. So that helps define the strength of the "other powerful people follow him" defense.

I know. He has DRF, so I was just letting him know about a confusing typo.

I agree that there's useful information in the brain that we can extract. EEG isn't that method. I love fMRI as much as the next guy. fMRI isn't reading "brainwaves". It images a correlate of neuronal oxygen depletion which indicates metabolism and activity.

waves: http://en.wikipedia.org/wiki/Electroencephalography#Wave_pat...

versus this awesomeness: http://en.wikipedia.org/wiki/Hemodynamic_response#Functional...

> And I can't type as fast as I can talk.

Some of us can.

http://www.seanwrona.com/typeracer/profile.php?username=kanz...

Well, almost. Mobile interfaces certainly aren't helping. I am not sure how much I would like a vocal way of typing out code, but I suspect I wouldn't.

Much as Microsoft did in the 1990s.

And AT&T in the 1960s.

Manager to programmers: "Hey that weird free software guy thinks we put "backdoors" in our software, whatever that means. Maybe he's right and our competitor do this already!! ...Quick, code a backdoor into our system too, we don't want to fall behind!"

It's better to distinguish the singularity (semi-infinite rapid change caused by recursively self-improving AI) from AI.

the role is in MTV

prank Perf?

Of course, fluffster was directed at you and I know what Kurzweil did.

So he gave a tech-talk at Google, around 2008, and yes he had lots of graphs and such but during the Q&A session he kept retreating into generalized ideas rather than data. I recall the question about how he came up with his numbers for machines to hold a consciousness as one such exchange.

The impression I certainly got was that his approach is to theorize about something, then design experiments to test out his theory. As opposed to running a bunch of experiments and then figuring out a theory that would explain the collected data.

That said, I've got mad respect for his work and have enjoyed his talks and writings. Your comment though suggests you think 'theorist' is a negative in some connotation? Why is that?

> His tendency to handwave rather than retreat to data? What the heck are you talking about? Have you seen how many graphs he puts in his presentations?

The ability to present something in graph form does not mean that it isn't handwavy bafflegab rather than data.

One need look no further than his absurd joke of a "paradigm shifts"/"countdown to the singularity" graph.

The Rapture for nerds, as Ken MacLeod delightfully put it.

If one person develops a theory and makes ten predictions which turn out to be true; and if a second person observes the same ten things, and then develops a theory without knowing the first; then I consider this stronger evidence in favor of the first theory than of the second. (The second might e.g. be more elegant, in which case I might prefer it anyway.)

This is true whatever the observations are. If they're unsurprising, then we already had a good theory, in which case I question the need for the two new ones, but that applies to both equally.

It may be that Kurzweil is falling into the trap of misinterpreting his results to fit his theory, but that can be done just as well when you try to base a theory off existing data. On the other hand, the Texas sharpshooter fallacy can only happen if you collect data before coming up with your theory.

He's also an ACM Fellow, from it's first class - along with people like Knuth, Cerf, Rivest, Codd, etc.

Not to be a downer, but text-to-speech, speech recognition, music synthesis, and so forth are all fairly obvious applications of computer science that anyone could have pioneered without being a genius. Likewise, predicting self-driving cars is nothing science fiction has not already done.

I'm sure he is a smart guy, but I think we have put him on a pedestal when he probably is not as remarkable as we want him to be.

A software practitioner, you say? As a researcher in machine learning, I think you're wrong. I agree that recursively self-improving AI is not around the corner, but I think it could happen in a few decades.

Even if it has a 1% chance of happening in the next century, I would still allocate resources to thinking about how to mitigate the risks (and maybe look foolish if it never happens) than leave things to chance and end up regretting it. By which I mean, a runaway AI destroys humanity or other bad outcomes.

As for the moving target -- since a singularity, if it happens, would be very important, it definitely makes sense to talk about lots of different scenarios. Anyone who dismisses a plausible scenario just because that's not what Vernor Vinge said, or what Ray Kurzweil said -- well, they can safely be dismissed.

I'm fine with reusing quotes, but in this instance it seems like a rather ham-handed application of it.

The singularity reeks of religious concepts. Kurzweil even called his book "The Age of Spiritual Machines" before it was "The Singularity is Near." He literally thinks he's going to be able to live forever (and the technology to do so will be available within his own lifetime). Yada yada... basically what I'm saying is the the quote fits that book perfectly.

Now we're talking about his new book "How to Create a Mind", which is a theory about how the brain works and how reverse engineer it, and the quote doesn't seem to fit. I'm guessing someone was just trying to sound intelligent... but then why does the OP agree with them?

foul?

First of all, I would strongly encourage anyone who is interested to check out Kurzweil's 2009 predictions in his 1999 book Age of Spiritual Machines, rather than this Wikipedia synopsis. It puts his predictions in a much more accurate context. You can view much of it here: http://books.google.com/books?id=ldAGcyh0bkUC&pg=PA789&#...

Kurzweil also does a reasonably unbiased job of grading his own predictions here: http://www.kurzweilai.net/images/How-My-Predictions-Are-Fari...

Quite a few of your statements relate to technological adoption vs. technological capability, such as everyday use of speech recognition and ebooks. I clearly stated that Kurzweil is not perfect at predicting what technologies will catch on with consumers and organizations, nor is anyone for that matter. To me, and to most of the people reading this, the most interesting aspect of Kurzweil's predictions is always what technological capabilities will be possible, rather than the rate of technological adoption.

Some of your other statements conflate science fiction with what Kurzweil does: "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." Similarly, most of your other points attempt to make the case that because nascent research projects existed, all of his predictions should have been readily apparent. I'm sorry, but this is pretty much the same hindsight bias displayed by gavanwoolery and Kurzweil's worst critics. Basically, Kurzweil's predictions are incredulously absurd to you, until they become blindingly obvious.

You can point to obscure German R&D projects all you want (and who knows how advanced that prototype was, or how controlled the tests were), but I was blown away by the Google self driving car, as were most of the people on HN based on the enthusiasm it received here. I thought it would take at least a decade or so before people took it for granted, buy you've set a Wow-to-Meh record in under a year.

Once again, I strongly encourage you to fire up Youtube or dust off an old computer, and really try and remember exactly what the tech environment was really like in previous decades for the average consumer. Zip drives, massive boot times, 5 1/4 floppy disks, EGA, 20mb external hard drives the size of a shoe box, 30 minute downloads for a single mp3 file, $2,000 brick phones, jpgs loading up one line of pixels a second, etc.

To be clear, I'm not a Kurzweil fanboy. He's not some omniscient oracle, bringing down the future on stone tablets from the mount. What he is is a meticulous, thoughtful, and voracious researcher of technological R&D and trends, and a reasonably competent communicator of his findings. I'm very familiar with the track records of others who try and pull off a similar feat, and he's not perfect, but he's far and away the best barometer out there for the macro trends of the tech industry. If his findings were so obvious, why is everyone else so miserable at it? Furthermore, his 1999 book was greeted with the same skepticism and incredulity that all of his later books were.

For some of your other points, I've included links below:

Research has been initiated on reverse engineering the brain - Kurzweil was clearly talking about an undertaking like the Blue Brain project. Henry Markram, the head of the project, is predicting that around 2020 they will have reverse engineered and simulated the human brain down to the molecular level:

http://www.ted.com/talks/henry_markram_supercomputing_the_br...

http://en.wikipedia.org/wiki/Blue_Brain_Project

A 1000 dollar pc can perform about a trillion calculations per second. -- This happened. This is also an extension based on Moore's law and so in some sense predicted a decade previous. Pretty much all of Kurzweil's predictions boil down to Moore's law, which he would be the first to admit. I'm not sure what you're trying to say.

Autonomous nanoengineered machines have been demonstrated and include their own computational controls. - If you read his prediction in context, he's clearly talking about very primitive and experimental efforts in the lab, which we are certainly closing in on:

http://www.kurzweilai.net/automated-drug-design-using-synthe...

http://en.wikipedia.org/wiki/Nadrian_Seeman - If you've been following any of Nadrian Seeman's work on nanobots constructed with DNA, Kurzweil's predictions seem pretty close

http://wyss.harvard.edu/viewpressrelease/101/researchers-cre...

http://www.kurzweilai.net/a-step-toward-creating-a-bio-robot...

http://www.aalto.fi/en/current//news/view/2012-10-18/

Three-dimensional chips are commonly used. - I guess you could quibble over them being a few years late:

http://www.bbc.co.uk/news/technology-17785464

http://www.pcmag.com/article2/0,2817,2384897,00.asp

This might be of some interest. http://fora.tv/2012/10/14/Stuart_Armstrong_How_Were_Predicti...

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.

That's the DR bit.

The TL-Did-actually-read-and-am-summarising-this-for-people-who-won't is exactly the opposite of what you've just stated.

He exhibits foresight bias.

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 perceptrons aren't all that different from how neurons work - hence the term "artificial neural network". But they also bridge to a pure mathematical/statistical background. The divide between them is not clear-cut; the whole point of mathematics is to model the world.)

" the use of statistical models that have no biological basis."

this is irrelevant

This is like saying a computer using an x86 processor is different, from the point of view of the user than an ARM computer, beyond differences in software

Or like saying DNA is needed for "data storage" in biological systems and not another technology

Sure, you can get inspiration from biology, but doesn't necessarily mean you have to copy it.

""I need to meet up" to Chinese. Google translates it to 我需要满足, meaning "I need to satisfy". This is where statistical translations fail, "

It's not really a fault of statistical translations (more likely quality of data issue), even though it has its limitations. Besides, google translation has been successful exactly because it's better than other existing methods (and Google has the resources, both in people and data to make it better)

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) requirements due to the lack of an object in the sentence and context. Situations like this where the input is very short and noisy is obviously going to be a weakness of statistical systems for a long time to come, but looking at technologically how far we are from mastering biological systems, I think it's safe to say this is going to be the way of doing it for a while, and will be very successful in translating properly structured texts if proper context can be provided. Currently statistical translations have (almost) no awareness of context beside some phrase-based or hierarchical models. Many people are probably not factoring in the fact, that with exponentially more data, and exponentially higher computing power, a model can utilize the context of a whole book while translating just a sentence from that book - which is actually still much less than what human translators utilize in terms of context. While translating a sentence, I might even have to utilize what was on the news the night before to infer the correct context. We are currently definitely far from feeding this kind of information to our models, so I'd say this kind of criticism towards statistical translation is very unfair.

I believe your summary suffers from selection bias.

I think most people have views that are controversial. Only when one is famous do others hear about those controversial views. Furthermore, just about every famous project has its distractors, leading to controversy.

Take Stephen Hawking as an example. He doesn't believe there was a god who created the universe. That's a controversial view to many. But when an non-famous atheist says exactly the same thing, few take notice, so you don't hear about those people.

Take Alan Kay as another example. He's one of the key people behind OLPC, which given its criticism could be considered controversial. But name any big project which has neither criticism nor controversy.

Ole Kirk Christiansen founded Lego. He was visionary in that he saw a future in plastic bricks as toys for children. What were his controversial views? I have no clue. But he probably had some. Perhaps his motto "Only the Best is Good Enough" is controversial to someone who believes that that second best may be good enough for some cases.

The degree of controversy is obviously diminished when someone has been successful. But I'll take a stab at the last question...

As for controversy with LEGO's founder: 1. Structuring the company around "doing good" instead of profitability and other more "corporate values". Google gets flack for this to this day, and LEGO almost went broke following this tenet until they revamped the corporate structure to follow profitability instead. 2. Use of plastics instead of wood, deviating from the company's original product base. Surely, that's what paved the way for LEGO, but I'm sure it was somewhat controversial switch in some circles, not least of which were carpenters and some employees. 3. LEGO's many legal battles and use of patents might be construed as controversial in some circles.

More to the point of the OP, it's hard to be a visionary if your view does not in any way shape or form deviate from the norm. Deviation from the norm is what sets the visionary apart, hence it's some times said that visionaries are controversial, because this deviation from the norm more often than not causes controversy in the areas in which they are deviating.

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.

>Tell us, concretely, what is to be gained from a biological approach.

Here it is from the horse's mouth: http://youtu.be/15sh05wrQ6Y#t=16m34s

An interesting set of questions to follow up this fair hypothesis are:

Is it better or worse than existing religions? In what way? Societally? Individually? Scientifically?

Is it better or worse than no religion? In what way? Societally? Individually? Scientifically?

Religion is arrogant, for sure. And it all started when some of our very distant ancestors decided to bury their dead instead of leaving them in a pile of trash. Which, interestingly, is considered one of the defining points where we became "humans" rather than just intelligent monkeys.

> It wouldn't be so bad if Kurzweil's dates didn't line up conveniently with his own mortality.

His age had probably little influence on his predictions. The Maes-Garreau law, as fun as it sounds, is probably not true[1]

> So combine that with the concept of a) eternal life, b) meeting your relatives in heaven (Kurzweil is planning to resurrect his dead father), and c) AI and post humans that are essentially godlike.

I'm personally skeptical of b), except for frozen people (cryonics). If entropy wiped out the information, there's no way to resurrect someone. a) and c) however seem to be merely obvious consequences of Friendly AI (I assume immortality and wicked IQ are good things). And intelligence explosion is quite plausible. You're a bit quick to dismiss those ideas just because they happen to pattern-match religion. (Now, I agree more with this[2] than with the specifics of Kurzweil ideas.)

> As far as I know, neither is God.

Current physics are reductionist. A supernatural God wouldn't fit into that. Current physics are deterministic (modulo the many-world lingering controversy), and universal. Miracles, as direct violations of the laws of physics, wouldn't fit into that. A Lord Outside the Matrix, maybe, but that's a different beast.

[1]: http://lesswrong.com/lw/e36/ai_timeline_predictions_are_we_g... [2]: http://intelligenceexplosion.com/primer.html

> That's not optimism. It's wishful thinking. If you can't see that it has all the fundamentals of a religion, I'm not sure what else to say.

Fundamentals of religion are irrelevant. The difference between singularity and rapture is that the first one - if we'll reach it - will be of human creation. Of our science and technology, not of supermagical powers. We can pretty much see the steps there, even though we haven't executed them all. Maybe it will take 200 years, not 50, but we will get there (unless we blow ourselves up before that).

Highlighting similarities between religion and singularity has no more merit than saying that addition is bad because Hitler and Stalin did it.

> 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 first in the 1600s and doesn't achieve mainstream popularity until the late 20th Century. Prior to that, Christian eschatalogical expectations were for the return of Christ to establish a just government once and for all.

Your larger point is still valid, but the application of the notion of a 'Rapture' is mostly anachronistic in any context other than the last hundred years.