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The latest episode of the Robots Podcast looks at the following scenario: Imagine being able to throw a hand-full of smart matter in a tank full of liquid and then pulling out a ready-to-use wrench once the matter has assembled. This is the vision of this episode's guests Michael Tolley and Jonas Neubert from the Computational Synthesis Laboratory run by Hod Lipson at Cornell University, NY. Tolley and Neubert give an introduction into Programmable Matter and then present their research on stochastic assembly of matter in fluid, including both simulation (see video above) and real-world implementation. Read on or tune in!

Erlang allows for massively scalable concurrency, often with millions of lightweight, thread-like components known as actors. Unfortunately, using Erlang requires rewriting all of your legacy code into a rather esoteric language. But there are other options, such as the little known CCR platform that was developed by .NET's robotics department. Actor based languages such as Erlang are able to achieve high degrees of parallelism by using the Actor model. Under this model the fundamental unit of concurrency is not a thread or fiber, but rather something much smaller. Known as a "process" in Erlang, each unit of concurrency has a base overhead of about 1200 bytes on a 32-bit system. By comparison, a thread on the Windows operating system defaults to 1 MB just for the stack, additional space is also needed for bookkeeping and thread local storage. Because they are so lightweight, an application can spawn literally millions of processes simultaneously.