Okay, so this is cool:
Neuroscientists stimulate the brain with brief pulses of energy and then record the echoes that bounce back. Dreamless sleep and general anaesthesia return simple echoes; brains in conscious states produce more complex patterns. Then comes a little inspiration from data compression:
Excitingly, we can now quantify the complexity of these echoes by working out how compressible they are, similar to how simple algorithms compress digital photos into JPEG files. The ability to do this represents a first step towards a "consciousness-meter" that is both practically useful and theoretically motivated.
This made me think of Chris Ford's StrangeLoop 2015 talk about using compression to understand music. Using compressibility as a proxy for complexity gives us a first opportunity to understand all sorts of phenomena about which we are collecting data. Kolmogorov complexity is a fun tool for programmers to wield.
The passage above is from an Aeon article on the study of consciousness. I found it an interesting read from beginning to end.
A week or so ago I tweeted that Carver Mead was blowing my mind: an electron a mile long! I read about that idea in this Spectator interview that covers both Mead's personal life and his professional work in engineering. Well worth a read.
Mead is not satisfied with the current state of physics and biology, or at least with the incomplete theories that we seem to have accepted in lieu of a more coherent conceptual understanding of how the world works. Ultimately, he sides with Einstein in his belief that there is a more coherent explanation:
I think Einstein was being a scientist in the truest sense in his response to the Copenhagen interpretation. He said that none of us would be scientists if deep down we didn't believe there is a set of regularities in the operation of physical law. That is a matter of faith. It is not something anybody has proven, but none of us would be scientists if we didn't have that faith.
Like Einstein, Mead believes that unpredictability at the lowest levels of a system does not imply intrinsic uncertainty. We need a different view that brings regularities to the forefront of our theories.
I also like this line from near the end of the interview:
People don't even know where to put the decimal point.
Mead says this as part of his assurance that artificial intelligence is nowhere near the level of what even the fruit fly can do, let alone the human brain. A lot has happened in AI during fifteen years since this interview; a computer program even beats our best players in Go now. Still, there is so much that we don't understand and cannot replicate.
I wonder if Mead's "decimal point" aphorism also might apply, metaphorically, to his view of the areas of science in which we have settled for, or are currently stuck with, unsatisifying theories. Our mathematical models cover a lot of ground, decimal point-wise, but there is still a simpler, more coherent picture to see. Maybe, though, that is the engineer in Mead showing through.
The last sentence of each of these passages reminds me of some of the students over the years.
First this, from Paul Callaghan's The Word Chain Kata:
One common way to split problems is via the "generate and test" pattern, where one component suggests results and the other one discards invalid ones. (In my experience, undergrad programmers are experts in this pattern, although they tend to use it as a [software development] methodology--but that's another story.)
When some students learn to program for the first time, they start out by producing code that looks like something they have seen before, trying it out, and then tinkering with it until it works or until they become exasperated. (I always hope that they act on their exasperation by asking me for help, rather than by giving up.) These students usually understand little bits of the code locally, but they don't really understand the program or function as a whole. Yet, somehow, they find a way to make it work.
It's surprising how far some students can get in a course of study by programming this way. (That's why Callaghan calling the approach a methodology made me smile.) It's unfortunate, too, because eventually the approach hits a wall when problems and domains become more challenging. Or when they run into a course where they program in Racket, in which one misplaced parenthesis can cause an otherwise perfect piece of code to implode. Lisp-like languages do not provide a supportive environment for this kind of "programming by wandering around".
And then there's this, from Andy Hertzfeld's fun little story about the writing of the classic manual Inside Macintosh:
Pretty soon, I figured out that if Caroline had trouble understanding something, it probably meant that the design was flawed. On a number of occasions, I told her to come back tomorrow after she asked a penetrating question, and revised the API to fix the flaw that she had pointed out. I began to imagine her questions when I was coding something new, which made me work harder to get things clearer before I went over them with her.
In this story, Caroline is not a student, but a young new writer assigned to the Mac documentation team. Still, she reminds me of students who are as delightful to work with as generate-and-test programmers can be frustrating. These students pay attention. They ask good questions, ones that often challenge the unstated assumptions underlying what we have explained before. At first, this can seem frustrating to us teachers, because we have to formulate answers for things that should be obvious. But that's the point: they aren't obvious, at least not to everyone, and us thinking they are obvious is inhibiting our teaching.
Last semester, I had one team of students in my compilers class that embodied this attitude. They asked questions no one had ever bothered to ask me before. At first, I thought, "How can these guys not understand such basic material?" Like Hertzfeld, though, pretty soon I figured out that their questions were exposing holes or weaknesses in my lectures, examples, and sample code. I began to anticipate their questions as I prepared for class. Their questions helped me see ways to make my course better.
As along so many other dimensions, part of the challenge in teaching CS is the wide variation in the way students study, learn, and approach their courses. It is also a part of the great fun of teaching, especially when you encounter the Carolines and Averys who push me to get better.
"This weekend I enjoyed Peter Hessler's interview of McPhee in The Paris Review, John McPhee, The Art of Nonfiction No. 3."
That's a direct quote from this blog. Don't remember it? I don't blame you; neither do I. I do remember blogging about McPhee back when, but as I read the same Paris Review piece again last Sunday and this, I had no recollection of reading it before, no sense of déjà vu at all.
Sometimes having a memory like mine is a blessing: I occasionally get to read something for the first time again. If you read my blog, then you get to read my first impressions for a second time.
I like this story that McPhee told about Bob Bingham, his editor at The New Yorker:
Bingham had been a writer-reporter at The Reporter magazine. So he comes to work at The New Yorker, to be a fact editor. Within the first two years there, he goes out to lunch with his old high-school friend Gore Vidal. And Gore says, What are you doing as an editor, Bobby? What happened to Bob Bingham the writer? And Bingham says, Well, I decided that I would rather be a first-rate editor than a second-rate writer. And Gore Vidal draws himself up and says, And what is wrong with a second-rate writer?
I can just hear the faux indignation in Vidal's voice.
McPhee talked a bit about his struggle over several years to write a series of books on geology, which had grown out of an idea for a one-shot "Talk of the Town" entry. The interviewer asked him if he ever thought about abandoning the topic and moving on to something he might enjoy more. McPhee said:
The funny thing is that you get to a certain point and you can't quit. Because I always worried: if you quit, you'll quit again. The only way out was to go forward, to learn your way and write your way out of it.
I know that feeling. Sometimes, I really do need to quit something and move on, but I always wonder whether quitting this time will make it easier to do next time. Because sometimes, I need to stick it out and, as McPhee says, learn my way out of the difficulty. I have no easy answers for knowing when quitting is the right thing to do.
Toward the end of the interview, the conversation turned to the course McPhee teaches at Princeton, once called "the literature of fact". The university first asked him to teach on short notice, over the Christmas break in 1974, and he accepted immediately. Not everyone thought it was a good idea:
One of my dear friends, an English teacher at Deerfield, told me: Do not do this. He said, Teachers are a dime a dozen -- writers aren't. But my guess is that I've been more productive as a writer since I started teaching than I would have been if I hadn't taught. In the overall crop rotation, it's a complementary job: I'm looking at other people's writing, and the pressure's not on me to do it myself. But then I go back quite fresh.
I know a lot of academics who feel this way. Then again, it's a lot easier to stay fresh in one's creative work if one has McPhee's teaching schedule, rather than a full load of courses:
My schedule is that I teach six months out of thirty-six, and good Lord, that leaves a lot of time for writing, right?
Indeed it does. Indeed it does.
On this reading of the interview, I marked only two passages that I wrote about last time. One came soon after the above response, on how interacting with students is its own reward. The other was a great line about the difference between mastering technique and having something to say: You demonstrated you know how to saddle a horse. Now go find the horse.
That said, I unconsciously channeled this line from McPhee just yesterday:
Writing teaches writing.
We had a recruitment event on campus, and I was meeting with a dozen or so prospective students and their entourages. We were talking about our curriculum, and I said a few words about our senior project courses. Students generally like these courses, even though they find them difficult. The students have never had to write a big program over the course of several months, and it's harder than it looks. The people who hire our graduates like these courses, too, because they know that these courses are places where students really begin to learn to program.
In the course of my remarks, I said something to the effect, "You can learn a lot about programming in classes where you study languages and techniques and theory, but ultimately you learn to write software by writing software. That's what the project courses are all about." There were a couple of experienced programmers in the audience, and they were all nodding their heads. They know McPhee is right.