The Insider News

Quote:

the “training sessions,” where the dogs did all their learning, took place within a computer. “We introduce a method for training a neural network policy in simulation,” the authors write, “and transferring it to a state-of-the-art legged system, thereby leveraging fast, automated, and cost-effective data generation schemes.” The artificial intelligence — here applied to a specific dog-sized machine named the ANYmal, but the method should work on any machine — learns all its tricks in the digital world, where there are no complicated and expensive parts to engineer and replace, then shows off its abilities in the real world.

Using this technique, the researchers improve on all previous attempts to manipulate such robots, achieving a new level of control and efficiency. In particular, ANYmal can now run up to 25 percent faster than ever, and it recovers from all fall it experienced in real-world testing. (Hence the abuse, above.)

MIT Technology Review[^]:

Quantum machines will deliver the next great leap forward in computing, but researchers building them can’t easily get some of the exotic components they need.

Engadget[^]:

AI and ML systems are turning the professional gambling world on its head.

Arne Mertz[^]:

The pImpl idiom is a useful idiom in C++ to reduce compile-time dependencies. Here is a quick overview of what to keep in mind when we implement and use it.