Kurzweil’s Next Book: Creating An Artificial Mind
singularityhub.com
singularityhub.com
1. The wetware is nifty but it's not what makes up intelligence.
The differences between sapient and non-sapient species are slight at the level of genetic code. The changes enabling intelligence are also very recent. The changes seem to be focused around the number and distribution of cortical columns in the neo-cortex, which are all remarkably similar regardless of the sensory input they are ultimately connected to. (This is why Hawkins' work is so exciting)
2. A huge portion of what we consider intelligence is a product of language and culture.
Neglected and wild children are barely sapient in a way that we would understand (though with care they can become so). Our minds are largely constructs of a transmissible set of patterns external to our biology.
3. The blue brain project is a ten year project
While I don't think we need molecular level or even synaptic level modeling to understand the software embodied in our brains, we have a hard target to be able to model, in large part, the human brain.
4. The large numbers in the brain are no longer scary
100 billion neurons and 100 trillion synaptic connections used to seem like an absurd scale for study. Now we regularly deal with billions of rows in databases and petabytes of storage. Not only that, the transmission speeds in the brain are so slow, if we need to replicate anything like the connectivity of the brain we can do it over a massive and distributed area. There's simply no need to cram an intelligence into a single box or server farm.
5. AI research has narrowed a great deal.
Whereas we had 50 tangents twenty years ago research is beginning to focus on two key aspects of learning. A. Large data sets for statistical analysis (e.g. Google) and B. Hierarchical representations of input. (e.g. Hawkins)
6. PR2 (Willow Garage)
I'll go out on a limb here and say that a shared open source robotics platform is the best thing to happen to AI research in 50 years. People forget the sheer number of hours experiencing the world it takes for the brain to acquire sapience. By supplying a common framework for experiencing the world the PR2 will enable the kind of long term learning necessary for intelligence to emerge.
I'm not the OP, but Matt Ridley's book The Rational Optimist, just released a few days ago, has much more on this. Selection here:
http://online.wsj.com/article/SB2000142405274870369180457525...
Edit: Reread what you wrote. It's possible, of course, that the first strong AI will be the result of a robot that crawls around putting stuff in its metaphorical mouth for two years like a human baby. But it seems unlikely, given the alternatives. Connecting something to the web gives it way more data than giving it a camera and treads.
1. The variety, detail and coherency of input available from interacting with the real world is more likely to give rise to intelligence.
2. Learning (above reflex modification and simple US-CS associations) appears to be based on feedback from behavior.
If I want to understand how a wooden block works, for example, a great way to learn about it is to pick it up and play with it. The richness of this experience and the speed which minor modifications to behavior produce reinforcement are difficult to replicate without a body.
You're right that for an intelligence to develop as humans' do, it needs constant feedback. But there are billions (?) of humans on the web...there are ways for an AI to get feedback.
Okay, though. I do see your point...human-like strong AI might grow better in a robot body than as pure software, other things being equal. It's a maybe, for a subset of AIs (those that develop like human intelligences), but fair enough.
Note that this idea is distinct from computers that solve complex problems on our behalf. Creating something with its own desires, ambitions, and emotions, just like us, except vastly more powerful, is there any reason to think something good will result from introducing such a thing into our environment? Does it ever go well for a species when a more intelligent species enters its niche and competes for resources?
As smart as Kurzweil is, I am always shocked that he takes for granted that such a development will be good for humanity. He scarcely gives a thought to the philosophical ramifications of a human being crossing over into a completely digital reality.
I think the question of whether super human intelligence is good for humanity is at least as important as the engineering questions about how to build one.
Overall, I'm finding these singularity fantasies philosophically entertaining, but I'll keep saying that's sick, or disgusting.
I know that's a metaphor, but I feel the better metaphor is another species. These machines are likely to be different from us in significant and important ways, and they are likely to have interests we do not share, and the ability to achieve those interests with or without our consent.
There was an SF author singularity panel discussion recently:
http://www.antipope.org/charlie/blog-static/2010/02/what-i-d...
Alastair Reynolds made the great point that the singularity's /identity/ needn't be its own. You could fix it to something / someone else, and have it use its mental power on behalf of someone else. It might not even know it exists.
Actually it sounded great at the time but, surely, if it had a balky human it would make a mental model of the difference between what it wanted to do and what it could do, and reach /some/ conclusion. If it knew about people I guess it could make a good guess. Hrm, I guess it'd be like our own ids, like the apostle Paul said - "I don't do that which I want to do, and do that which I don't want to do". So the creature would come up with a notion of 'singularity frailty' and 'original ineffectuality', perhaps.
tl;dr - I agree with Jeff Hawkins about the future of AI
The human mind is the product of billions of years of parallel computation and experimentation. Raw horsepower is probably the easy part.
Human / animal muscles are also the product of billions of years of experimentation, and a few decades of steam power research trounced them with ease. Just because it's old doesn't mean it's inherently incredibly good and hard to replicate.
A lot of people seem to think that if you build a machine of sufficient raw horsepower that intelligence will magically emerge. Maybe, but I suspect it's not nearly so easy.