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| Image Source: Technology Review |
I thought these articles were related, and I admit somewhat intriguing. The first regards Buzz, which is described in the paper's abstract as "a novel programming language for heterogeneous robot swarms," though I'm not sure if "swarm" is the operative word they should have had in their description. The second is a post on Technology Review titled: "Teaching Machines to Understand Us." [Ahem] We have a few that can - well, extrapolate to some extreme thought processes - I'm thinking of the recent shots fired in the Jade Helm 15 military exercises [1], and outrageous behavior encouraged by conspiracy provocateurs (that haven't participated). It doesn't help that some very good science fiction has speculated on this quite a bit, and a few of my fellow humans can't delineate between fantasy and reality. [2]
Abstract
We present Buzz, a novel programming language for heterogeneous robot swarms. Buzz advocates a compositional approach, offering primitives to define swarm behaviors both from the perspective of the single robot and of the overall swarm. Single-robot primitives include robot-specific instructions and manipulation of neighborhood data. Swarm-based primitives allow for the dynamic management of robot teams, and for sharing information globally across the swarm. Self-organization stems from the completely decentralized mechanisms upon which the Buzz run-time platform is based. The language can be extended to add new primitives (thus supporting heterogeneous robot swarms), and its run-time platform is designed to be laid on top of other frameworks, such as Robot Operating System. We showcase the capabilities of Buzz by providing code examples, and analyze scalability and robustness of the run-time platform through realistic simulated experiments with representative swarm algorithms. [3]
The first time Yann LeCun revolutionized artificial intelligence, it was a false dawn. It was 1995, and for almost a decade, the young Frenchman had been dedicated to what many computer scientists considered a bad idea: that crudely mimicking certain features of the brain was the best way to bring about intelligent machines. But LeCun had shown that this approach could produce something strikingly smart—and useful. Working at Bell Labs, he made software that roughly simulated neurons and learned to read handwritten text by looking at many different examples. Bell Labs’ corporate parent, AT&T, used it to sell the first machines capable of reading the handwriting on checks and written forms. To LeCun and a few fellow believers in artificial neural networks, it seemed to mark the beginning of an era in which machines could learn many other skills previously limited to humans. It wasn’t. [4]
1. Jade Helm: The Insanity that Ate Texas, Jim Wright, Stonekettle Station
2. Why Operation Jade Helm 15 is freaking out the Internet — and why it shouldn’t be, Dan Lamothe, Washington Post
3. Physics arXiv:
Buzz: An Extensible Programming Language for Self-Organizing Heterogeneous Robot Swarms, Carlo Pinciroli, Adam Lee-Brown, Giovanni Beltrame
4. Teaching Machines to Understand Us, Tom Simonite
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