Richard Feynman -- lessons from Connection Machine

If I'd been a bit smarter, I could have lasted longer in Feynman's 1989 1986 Physics-X class. I was fighting to survive my 1st year at Caltech though, and I sacrificed it for the classes I was graded on.

If I'd been a bit wiser, I'd have given up on something else instead, but I was a kid.

Even with limited exposure I remember the Feynman-field effect. As long as he was nearby it all seemed simple, but once he left so did understanding. Inverse square law I think.

So this superb essay, by the founder of a 1980s era supercomputer firm, really strikes home.

I'm excerpting the bits we can draw lessons from, the essay deserves to be read in its entirety. Emphases mine. I admit some of the lessons are more applicable to persons with IQs over 200.

Long Now Essays - W. Daniel Hillis - Richard Feynman and The Connection Machine
... Richard's interest in computing went back to his days at Los Alamos, where he supervised the "computers," that is, the people who operated the mechanical calculators. There he was instrumental in setting up some of the first plug-programmable tabulating machines for physical simulation. His interest in the field was heightened in the late 1970's when his son, Carl, began studying computers at MIT...
...We were arguing about what the name of the company should be when Richard walked in, saluted, and said, "Richard Feynman reporting for duty. OK, boss, what's my assignment?" The assembled group of not-quite-graduated MIT students was astounded.
After a hurried private discussion ("I don't know, you hired him..."), we informed Richard that his assignment would be to advise on the application of parallel processing to scientific problems.
"That sounds like a bunch of baloney," he said. "Give me something real to do."
So we sent him out to buy some office supplies. While he was gone, we decided that the part of the machine that we were most worried about was the router that delivered messages from one processor to another. We were not sure that our design was going to work. When Richard returned from buying pencils, we gave him the assignment of analyzing the router...
... During those first few months, Richard began studying the router circuit diagrams as if they were objects of nature. He was willing to listen to explanations of how and why things worked, but fundamentally he preferred to figure out everything himself by simulating the action of each of the circuits with pencil and paper.
...Richard did a remarkable job of focusing on his "assignment," stopping only occasionally to help wire the computer room, set up the machine shop, shake hands with the investors, install the telephones, and cheerfully remind us of how crazy we all were...
...I had never managed a large group before and I was clearly in over my head. Richard volunteered to help out. "We've got to get these guys organized," he told me. "Let me tell you how we did it at Los Alamos."
Every great man that I have known has had a certain time and place in their life that they use as a reference point; a time when things worked as they were supposed to and great things were accomplished. For Richard, that time was at Los Alamos during the Manhattan Project. Whenever things got "cockeyed," Richard would look back and try to understand how now was different than then. Using this approach, Richard decided we should pick an expert in each area of importance in the machine, such as software or packaging or electronics, to become the "group leader" in this area, analogous to the group leaders at Los Alamos.
Part Two of Feynman's "Let's Get Organized" campaign was that we should begin a regular seminar series of invited speakers who might have interesting things to do with our machine. Richard's idea was that we should concentrate on people with new applications, because they would be less conservative about what kind of computer they would use. For our first seminar he invited John Hopfield, a friend of his from CalTech, to give us a talk on his scheme for building neural networks...
... Feynman figured out the details of how to use one processor to simulate each of Hopfield's neurons, with the strength of the connections represented as numbers in the processors' memory. Because of the parallel nature of Hopfield's algorithm, all of the processors could be used concurrently with 100\% efficiency, so the Connection Machine would be hundreds of times faster than any conventional computer...
... Feynman worked out the program for computing Hopfield's network on the Connection Machine in some detail. The part that he was proudest of was the subroutine for computing logarithms...
... Concentrating on the algorithm for a basic arithmetic operation was typical of Richard's approach. He loved the details. In studying the router, he paid attention to the action of each individual gate and in writing a program he insisted on understanding the implementation of every instruction. He distrusted abstractions that could not be directly related to the facts...
... To find out how well this would work in practice, Feynman had to write a computer program for QCD. Since the only computer language Richard was really familiar with was Basic, he made up a parallel version of Basic in which he wrote the program and then simulated it by hand to estimate how fast it would run on the Connection Machine...
... By the end of that summer of 1983, Richard had completed his analysis of the behavior of the router, and much to our surprise and amusement, he presented his answer in the form of a set of partial differential equations. To a physicist this may seem natural, but to a computer designer, treating a set of boolean circuits as a continuous, differentiable system is a bit strange. Feynman's router equations were in terms of variables representing continuous quantities such as "the average number of 1 bits in a message address." I was much more accustomed to seeing analysis in terms of inductive proof and case analysis than taking the derivative of "the number of 1's" with respect to time. Our discrete analysis said we needed seven buffers per chip; Feynman's equations suggested that we only needed five....
... The first program run on the machine in April of 1985 was Conway's game of Life.
... The notion of cellular automata goes back to von Neumann and Ulam, whom Feynman had known at Los Alamos. Richard's recent interest in the subject was motivated by his friends Ed Fredkin and Stephen Wolfram, both of whom were fascinated by cellular automata models of physics...
... we were having a lot of trouble explaining to people what we were doing with cellular automata. Eyes tended to glaze over when we started talking about state transition diagrams and finite state machines. Finally Feynman told us to explain it like this,
"We have noticed in nature that the behavior of a fluid depends very little on the nature of the individual particles in that fluid. For example, the flow of sand is very similar to the flow of water or the flow of a pile of ball bearings. We have therefore taken advantage of this fact to invent a type of imaginary particle that is especially simple for us to simulate. This particle is a perfect ball bearing that can move at a single speed in one of six directions. The flow of these particles on a large enough scale is very similar to the flow of natural fluids."
This was a typical Richard Feynman explanation. On the one hand, it infuriated the experts who had worked on the problem because it neglected to even mention all of the clever problems that they had solved. On the other hand, it delighted the listeners since they could walk away from it with a real understanding of the phenomenon and how it was connected to physical reality.
We tried to take advantage of Richard's talent for clarity by getting him to critique the technical presentations that we made in our product introductions... Richard would give a sentence-by-sentence critique of the planned presentation. "Don't say `reflected acoustic wave.' Say [echo]." Or, "Forget all that `local minima' stuff. Just say there's a bubble caught in the crystal and you have to shake it out." Nothing made him angrier than making something simple sound complicated...
... as the machine and its successors went into commercial production, they were being used more and more for the kind of numerical simulation problems that Richard had pioneered ... Figuring out how to do these calculations on a parallel machine requires understanding of the details of the application, which was exactly the kind of thing that Richard loved to do.
For Richard, figuring out these problems was a kind of a game. He always started by asking very basic questions like, "What is the simplest example?" or "How can you tell if the answer is right?" He asked questions until he reduced the problem to some essential puzzle that he thought he would be able to solve. Then he would set to work, scribbling on a pad of paper and staring at the results. While he was in the middle of this kind of puzzle solving he was impossible to interrupt. "Don't bug me. I'm busy," he would say without even looking up. Eventually he would either decide the problem was too hard (in which case he lost interest), or he would find a solution (in which case he spent the next day or two explaining it to anyone who listened). In this way he worked on problems in database searches, geophysical modeling, protein folding, analyzing images, and reading insurance forms.
The last project that I worked on with Richard was in simulated evolution. I had written a program that simulated the evolution of populations of sexually reproducing creatures over hundreds of thousands of generations. The results were surprising in that the fitness of the population made progress in sudden leaps rather than by the expected steady improvement. The fossil record shows some evidence that real biological evolution might also exhibit such "punctuated equilibrium," so Richard and I decided to look more closely at why it happened. He was feeling ill by that time, so I went out and spent the week with him in Pasadena, and we worked out a model of evolution of finite populations based on the Fokker Planck equations. When I got back to Boston I went to the library and discovered a book by Kimura on the subject, and much to my disappointment, all of our "discoveries" were covered in the first few pages. When I called back and told Richard what I had found, he was elated. "Hey, we got it right!" he said. "Not bad for amateurs."
...Actually, I doubt that it was "progress" that most interested Richard. He was always searching for patterns, for connections, for a new way of looking at something, but I suspect his motivation was not so much to understand the world as it was to find new ideas to explain. The act of discovery was not complete for him until he had taught it to someone else...

I'm struck that Feynman was good at giving up on problems where he wasn't making progress. That's something most of us, albeit on a far more modest scale, find hard to do. We run the risk of pouring efforts down a project with a limited chance of success. Feynman knew there were always other interesting problems, problems that were likely to be easier to solve.

I didn't know about his interest in cellular automata, or that he was a friend of Wolfram's.

I knew Hopfield too -- I took one or two of his courses. I don't recommend Caltech for any undergrad with an IQ belong 160, but it is a fantastic place to be a graduate student.