What an offensive stereotype! Each of us is an individual — I have known close-minded people in their twenties and wise and wonderful eighty-year-olds.

In addition to being offensive, your assertion lacks supporting data. See, for example, Charness, Gary, and Marie-Claire Villeval. 2009. “Cooperation and Competition in Intergenerational Experiments in the Field and the Laboratory.” American Economic Review, 99(3): 956–78

To the editors: Your policy on comments precludes racists, sexist, and homophobic remarks. Good! Please know that ageism is just as offensive.

That is a much more reasoned statement than your comment in #28, and one with which I agree.

Ageism is rampant so I am very sensitive to blanket assertions about the capabilities of older workers. Look it up — folks in their fifties do fine in a bad economy as long as they hold on to their jobs. But if they happen to lose a job through layoff or because their employer goes out of business, it takes older workers much longer to find new work. And that new work tends to pay far less.

In fact, Charness and Villeval found, “First, seniors are not more risk-averse, as opposed to the conventional stereotype. Second, both juniors and seniors react to the competitiveness of the environment and there is no significant difference in performance in the real-effort task across the generations when they are competing. Third, seniors are typically more cooperative than juniors in a team-production game. Cooperation is highest in groups in which there is a mix of juniors and seniors, suggesting that there are indeed benefits in maintaining a work force with diversity in age.”

I agree — I’m eager to see what the new MIT team comes up with.

Btw, I think many scientists do their most seminal work at a young age because there’s more pressure on them when they’re younger. Also, after they’re tenured, much of their creativity is channeled into their work with their grad students.

Considering some of the children’s books out there, this might not be such a good idea. Designing a computer to understand something by Dr Suess or Lewis Carroll seems unbelievably hard. Just getting a computer to understand the difference between a Snark and a Boojum would take a whole new science of AI.

Rebooting the field by reintroducing Minsky may be sounding the death knell of this project right from the beginning.

Then they can dedicate their datacenters to testing full human brain emulation. It could be quite a thing. Like a new world holiday, where everyone waits to see what pops out this year, see what sort of character the GOOG is becoming. It’d probably be pretty shit for the first ten years or so, but then it’d be everyone’s second favourite observance of the year (after Rabies Day! obviously).

To my mind, most of what was broken about artificial intelligence, was the search for a new kind of slavery without the moral qualms.

‘Weak’ AI theories always seemed to have more practicality than the strong stuff.

Similarly, the ship Minds have free will. But they have no more particular compunction to engage with society than humans do. Their chains are only social, just like the humans in that universe.

That news last year was probably one of the biggest, game-changingest, completely-unnoticed-at-the-time developments in human history so far. If you know much about neural networks, how model neurons work, and the “current” limitations, (I took AI courses during Computer Science curriculum circa 1999, but I haven’t seen significant progress since) you will be very excited when you learn what a Memristor is and about them going from theory to reality.

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

Seems to me that the last people you want “rebooting” a field are the same old farts who have been working on it for the past sixty years. The same old farts who invented it, no less.

Old people aren’t known for their abilities to embrace new ideas and have new sparks of inspiration at the best of times, and even less so when they each have spent their whole careers defending their dogmas and reputations.

I do hope they have some people below the age of 30 on their team, or I really don’t see it going anywhere. Done right, though, an all-star team of the old pioneers and young genius undergraduates and such, structured in a way that everyone could actually contribute and not be overawed by fame, you might actually get somewhere.

Rebooting the field by reintroducing Minsky may be sounding the death knell of this project right from the beginning.

I don’t know Minksy personally, but it seems to me that he keeps making confident predictions and proclamations that haven’t panned out. I wouldn’t want him on my project, because I don’t see any evidence that he can deliver anything.

I keep hearing him hailed as a genius, also, but I never see any actual evidence that this is so.

Marvin Minsky is a smart old dude, though. And regardless of the fact that people seem to think of him as trumpeting the coming golden age of AI his seminal works to me seem to be about what computers/AI can NOT do (the only one of his book I’ve read, admittedly, is somewhat old, about the “perceptron” and what it was not capable of)

A chimpanzee can’t read and understand and explain a children’s book, but there’s no denying that they’re intelligent. Same with a gorilla, or a dog, or a cat.

It’s like deciding we want to generate electricity, and starting with a fusion reactor first.

Well put.

I would phrase it another way: The problem with modern AI is that it is a problem people have largely been trying to solve with fixed architecture computers and procedural programming languages. We’re going to have to fundamentally change the way computers, and the languages used to program them, work before we crack this nut. Massively parallel programable memristor nets seem like a good place to start research.

On the other hand, it seems to me that Artificial Intelligence is much more likely to arise as a byproduct of Artificial Life, than it is from Computer Science.

We need special task robots, not general AI.

We have been tugging AI along on planks of increasingly sophisticated lubrication. The memristor poses a wheel.

This is only elegant if your underlying “neurons” happen to look something like the “neurons” you’re modelling. Otherwise you’re probably going to have to have a seriously complicated (and unintelligible) intermediate layer.

Anyway, any attempt to model biologically realistic neurons is pretty much doomed to failure at the moment, cos we don’t know how the buggers work. The “weighted sum + threshold function” model is easy to implement, but demonstrably does not provide a complete description of the underlying system. And last I heard, the whole back-propagation strategy for NN programming was basically unverified.

The current approach seems to be to model small sections such as simple visual systems* in great depth, and work outwards from there. This seems like it might actually add value – even if we can’t get it to work, these systems are small enough that it should be possible to figure out why.

This project, by contrast, seems more like a return to the old quasi-philosophical approach to AI. That produced lots of beautiful computer science, and hopefully this new project will do the same, but in terms of actually modelling/implementing realistic intelligent systems I consider it a backwards step.

* For an example of the state of the academic art, see: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000555

There is quite a lot of anecdotal evidence of scientists doing their most seminal work at a young age, although of course one can come up with numerous counter-examples.

Here are the results of a very quick article search:

At What age do scientists do their best work? (pdf) (pub. in FASEB Journal, 2008):

Shows scientists do their “best” work (by articles with most citations) between the ages of 33 and 35, and declines there-after, in almost all life sciences.

An economic model of the life-cycle research productivity of scientists, (pub. in Scientometrics, 2005):

Shows “number of citations made to a scientist’s previous work will decline with age.”

Another good page here on the correlation between youth and scientific accomplishments, which also makes the good point that our perception of scientists are always as older people (think of the iconic images of Einstein and Darwin), even though they most commonly do their seminal work in their youth (both Einstein and Darwin made their greatest contributions to their fields in their 20s).

So, though I understand your asking the administrators to censor me because you find me offensive, please recognize that not everyone talks out of their asses when they write things.

Anyway… it sounds like the team will be quite a mix! Sounds great.

It seems like you’re making an assertion that there is a fundamental difference between two things which are, in fact, logically equivalent.