Monday, January 25, 2016

Marvin Minsky, RIP

Glenn Rifkin (via Dan Bricklin, Hacker News, Slashdot):

Well before the advent of the microprocessor and the supercomputer, Professor Minsky, a revered computer science educator at M.I.T., laid the foundation for the field of artificial intelligence by demonstrating the possibilities of imparting common-sense reasoning to computers.

“Marvin was one of the very few people in computing whose visions and perspectives liberated the computer from being a glorified adding machine to start to realize its destiny as one of the most powerful amplifiers for human endeavors in history,” said Alan Kay, a computer scientist and a friend and colleague of Professor Minsky’s.

[…]

Professor Minsky’s scientific accomplishments spanned a variety of disciplines. He designed and built some of the first visual scanners and mechanical hands with tactile sensors, advances that influenced modern robotics. In 1951 he built the first randomly wired neural network learning machine, which he called Snarc. And in 1956, while at Harvard, he invented and built the first confocal scanning microscope, an optical instrument with superior resolution and image quality still in wide use in the biological sciences.

Philip Greenspun:

Marvin questioned many of the assumptions around Academia. He would show up to deliver a formal talk with a stack of notes and pick from them more or less at random. I wish that I could say that the results were amazing due to his dazzling intellect, but unfortunately the lack of an organized outline made these talks less than satisfying. Marvin was at his best in small groups or working one-on-one with others at MIT. What I remember most about him was his genial skepticism. If two people were arguing, rather than take one side, Marvin could show that both were operating from an assumption about the world that perhaps wasn’t necessary or true. He was a bit of a modern-day Socrates.

Update (2016-01-28): Paul Whitmore Sas:

Another defining characteristic of his mind was its utterly stochastic trajectory. No one, and certainly not Marvin, could discipline his curiosity cum hubris. SoM class lectures rode roughshod over a thousand topics, and left many stacks unpopped. The book, which exemplifies a horde of daemons tackling random splinters of cognition, was rumored to have been assembled from shards collected together with Hillis’ help.

Update (2016-01-29): Adam C. Engst:

I’ll remember him as a TidBITS reader and for his openness and kindness. Although plans to meet up at Macworld Boston never came to fruition, I exchanged email with him back in 1992 about Apple’s Casper voice recognition technology (see “Casper Speaks,” 9 March 1992), which evolved into a system called PlainTalk (see “Bossing Your Mac with PlainTalk,” 28 August 2000).

Stephen Wolfram (via Hacker News):

Being no expert on such things (and without the web to look anything up!), I called Marvin to ask what to do. What ensued was a long discussion about the possibility of developing microrobots that could chase mealybugs away. Fascinating though it was, at the end of it I still had to ask, “But what should I actually do about Margaret’s plants?” Marvin replied, “Oh, I guess you’d better talk to my wife.”

[…]

Marvin immediately launched into talking about how programming languages are the only ones that people are expected to learn to write before they can read. He said he’d been trying to convince Seymour Papert that the best way to teach programming was to start by showing people good code.

Update (2016-01-30): Scott Aaronson:

For example, in his and Papert’s 1968 book Perceptrons—notorious for “killing neural net research for a decade,” because of its mis- or over-interpreted theorems about the representational limitations of single-layer neural nets—the way Minsky and Papert proved those theorems was by translating questions about computation into questions about the existence or nonexistence of low-degree polynomials with various properties, and then answering the latter questions using MATH. Their “polynomial method” is now a mainstay of quantum algorithms research (having been brought to the subject by Beals et al.), and in particular, has been a mainstay of my own career.

Update (2016-03-17): Steven Levy:

Minsky quotes in fortune cookies.

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