You don't understand anything until you learn it more than one way.
Marvin Minsky
Societies need rules that make no sense for individuals. For example, it makes no difference whether a single car drives on the left or on the right. But it makes all the difference when there are many cars!
With the appearance of communications networks and interconnected computers, we got the world wide web, and it changed the lives of most people, I think.
Sometimes a problem will seem completely insurmountable. Then someone comes up with a simple new idea, or just a rearrangement of old ideas, that completely eliminates it.
When David Marr at MIT moved into computer vision, he generated a lot of excitement, but he hit up against the problem of knowledge representation; he had no good representations for knowledge in his vision systems.
In general we are least aware of what our minds do best.
No computer has ever been designed that is ever aware of what it's doing; but most of the time, we aren't either.
The degree of intelligence that a man or a machine can show depends on many qualities of the ways that knowledge, goals, and problem-solving techniques are represented and put together, and not so much on the fine details.
Kubrick's vision seemed to be that humans are doomed, whereas Clarke's is that humans are moving on to a better stage of evolution.
It's degrading or insulting to say somebody is a good person or has a soul. Each person has built this incredibly complex structure, and if you attribute it to a magical pearl in the middle of an oyster that makes you good, that's trivializing a person and keeps you from thinking of what's really happening.
The basic idea in case-based, or CBR, is that the program has stored problems and solutions. Then, when a new problem comes up, the program tries to find a similar problem in its database by finding analogous aspects between the problems.
There are three basic approaches to AI: Case-based, rule-based, and connectionist reasoning.
Around 1967 Dan Bobrow wrote a program to do algebra problems based on symbols rather than numbers.
There was a failure to recognize the deep problems in AI; for instance, those captured in Blocks World. The people building physical robots learned nothing.
By the way, it was his simulations that helped out in Jurassic Park - without them, there would have been only a few dinosaurs. Based on his techniques, Industrial Light and Magic could make whole herds of dinosaurs race across the screen.
I suspect that pleasure is mainly used to turn off parts of the brain so you can keep fresh the memories of things you're trying to learn. It protects the short-term memory buffers. That's one theory of pleasure.
I heard that the same thing occurred in a scene in Alien, where the creature pops out of the chest of a crewman. The other actors didn't know what was to happen; the director wanted to get true surprise.
Some people believe that you should die, and some people think dying is a nuisance. I'm one of the latter. So I think we should get rid of death.
I believe that everyone has to construct a mental model of what they are and where they came from and why they are as they are, and the word soul in each person is the name for that particular mish-mash of those fully formed ideas of one's nature.
If you just have a single problem to solve, then fine, go ahead and use a neural network. But if you want to do science and understand how to choose architectures, or how to go to a new problem, you have to understand what different architectures can and cannot do.
I believed in realism, as summarized by John McCarthy's comment to the effect that if we worked really hard, we'd have an intelligent system in from four to four hundred years.
We all admire great accomplishments in the sciences, arts, and humanities - but we rarely acknowledge how much we achieve in the course of our everyday lives.
We wanted to solve robot problems and needed some vision, action, reasoning, planning, and so forth. We even used some structural learning, such as was being explored by Patrick Winston.
This is a tricky domain because, unlike simple arithmetic, to solve a calculus problem - and in particular to perform integration - you have to be smart about which integration technique should be used: integration by partial fractions, integration by parts, and so on.
Stanley Kubrick knew we had good graphics around MIT and came to my lab to find out how to do it. We had some really good stuff. I was very impressed with Kubrick; he knew all the graphics work I had ever heard of, and probably more.
Once when I was standing at the base, they started rotating the set and a big, heavy wrench fell down from the 12 o'clock position of the set, and got buried in the ground a few feet from me. I could have been killed!
I think Lenat is headed in the right direction, but someone needs to include a knowledge base about learning.
I started working at a point in history when digital computers were becoming mature, and before that, there were no such machines.
I think every person either inherits or eventually makes up their own idea of what they are and who they are and what caused the world to be, and it seems to me that these stories of creation myth, adopted by different cultures - most of them are less insightful than the stories made up by individual poets and writers.
We humans are not the end of evolution, so if we can make a machine that's as smart as a person, we can probably also make one that's much smarter. There's no point in making just another person. You want to make one that can do things we can't.
General fiction is pretty much about ways that people get into problems and screw their lives up. Science fiction is about everything else.
