Kathryn Cramer writes, "Jesse Friedman, age 14, has developed some code for getting Wolfram Language to tell a few jokes. Although most of WL's jokes are not funny, the generative language tools are an interesting toy." Read the rest
In 1913, George Julius installed a building-sized, all mechanical odds-calculating computer at Auckland, NZ's Ellerslie racetrack, powered by huge iron weights that slowly pulled down bike chains over sprockets, driving the clockwork device as it "totalised" all the bets laid on horses at the track, keeping the odds in constant balance so that all the bettors were effectively betting against one another, in a system called "pari-mutuel" betting. Read the rest
Computing pioneer Paul Niquette's memoir begins with the tale of how he came to coin the term "software" in 1953, to the ridicule of his colleague, and how the idea of a computer whose code was separate from its machinery took hold and changed the way we think about computation forever. Read the rest
Ben Kraft teaches a unit on gerrymandering -- rigging electoral districts to ensure that one party always wins -- to high school kids in his open MIT Educational Studies Program course. As he describes the problem and his teaching methodology, I learned that district-boundaries have a lot more subtlety and complexity than I'd imagined at first, and that there are some really chewy math and computer science problems lurking in there. Read the rest
A. Peer, M. Ihmsen, J. Cornelis and M. Teschner's SIGGRAPH paper "An Implicit Viscosity Formulation for SPH Fluids," explored techniques for simulating the physics of smoothed-particle hydrodynamics -- solids that melt and squoosh into liquids and slimes. As interesting as the paper is, the video is a showstopper -- never have simulated anthropomorphic armadillo action-figures been so meltfully delightful! Read the rest
Literary podcaster Rick Kleffer writes, "I must admit that it was too much fun to sit down with John Markoff and talk (MP3) about his book Machines of Loving Grace. Long ago, I booted up a creaking, mothballed version of one of the first Xerox minicomputers equipped with a mouse to extract legacy software for E-mu. Fifteen years later I was at the first Singularity Summit; the book was a trip down many revisions of memory road."
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John Markoff’s ‘Machines of Loving Grace: The Quest for Common Ground Between Humans and Robot’ is a fascinating, character-driven vision of how the recent past created the present and is shaping the near future. The strong and easily understood conflict at the heart of this work gives readers an easy means of grasping the increasingly complicated reality around us. If we do not understand this history, the chances are that we will not have the opportunity to be doomed to repeat it.
Our technological ecology began in two computer labs in Stanford in the early sixties. In one lab, John McCarthy coined the term “Artificial intelligence” with the intention of creating a robot that could think like, move like and replace a human in ten years. On the opposite side of the campus, Douglas Englebart wanted to make it easier for scholars to collaborate using an increasingly vast amount of information. He called it IA, Intelligence Augmentation as a direct response to AI. Thus were born two very different design philosophies that still drive the shape of our technology today – and will continue to do so in the future.
"Unlearning Object-Oriented Programming," "Classical Software Studies," "Writing Fast Code in Slow Languages," "User Experience of Command Line Tools," and "Obsessions of the Programmer Mind." Read the rest
It's not making software that can solve our problems: it's figuring out how to pose those problems so that the software doesn't bite us in the ass. Read the rest
Josh Millard's Calvin and Markov uses a small perl script to mine transcripts of Calvin and Hobbes strips using Markov chains to make new, weird, computer humor. Read the rest
A meditation on the problem of updating bureaucracies' databases that presently only support reciprocal "husband-wife" relationships, but not "husband-husband" or "wife-wife". Read the rest
In "Inceptionism," scientists at Google Research describe their work training neural nets with sets of images, then tweaking the "layers" of neural net nodes to produce weird outcomes. Read the rest