Superconducting materials can do amazing things that appear to defy the laws of physics, but their major drawback is that superconducting properties don’t appear unless a material is cooled to near absolute zero.

Superconductors that would work at (or near)  room temperatures would, without exaggeration, would change the world and would have massive implications for quantum computing.   

Liv Boeree shares this exclusive behind-the-scenes interview with the scientists who just unearthed one of the holy grails of physics: a room-temperature superconductor!

Their discovered material — carbonaceous sulfur hydride — shows superconductivity at 15 degrees Celsius, a temperature FAR above all previous records. It takes us a huge step closer to the long-sought goal of creating electrical systems with perfect efficiency, which would transform the world’s energy grids, computation and transportation systems entirely.

 

While in Seattle a few weeks ago, I had the chance to see the Spheres for myself.

Wall Street Journal explores the Spheres, Amazon’s giant biodomes in downtown Seattle, allow employees to escape the office to work and brainstorm surrounded by nature.

Take a tour with NBBJ architect John Savo as he shows off the features of the workspace, including a five-story living wall with 25,000 plants. Photo Illustration: Drew Evans/The Wall Street Journal.

A quantum computer isn’t just a more powerful version of the computers we use today; it’s something else entirely, based on emerging scientific understanding — and more than a bit of uncertainty.

Enter the quantum wonderland with TED Fellow Shohini Ghose and learn how this technology holds the potential to transform medicine, create unbreakable encryption and even teleport information.

Can’t get enough? Here’s another video.

I always knew that reinforcement learning would teach us more about ourselves than any other kind of AI approach. This feeling was backed up in a paper published recently in Nature.

DeepMind, Alphabet’s AI subsidiary, has once again used lessons from reinforcement learning to propose a new theory about the reward mechanisms within our brains.

The hypothesis, supported by initial experimental findings, could not only improve our understanding of mental health and motivation. It could also validate the current direction of AI research toward building more human-like general intelligence.

It turns out the brain’s reward system works in much the same way—a discovery made in the 1990s, inspired by reinforcement-learning algorithms. When a human or animal is about to perform an action, its dopamine neurons make a prediction about the expected reward.

Siraj Raval has a new video out with more of an artistic flair about the hidden mathematics in the beauty of nature. Brilliant. Simply brilliant.

Show this one to the haters when they tell you that there’s no use for math in the “real world.”