Inside Giant Atom Smasher, Physicists See the Impossible

In case you didn’t realize it, photons are tiny little bits of light.

When you turn on a lamp, gigantic numbers of photons spring from that bulb and slam into your eyes, where they are absorbed by your retina and turned into an electrical signal so that you can see what you are doing.

Even your own body generates photons, but all the way down in infrared energies, so you need night vision goggles to see them.

In a new experiment inside the world’s most powerful atom smasher, researchers got a glimpse of the impossible: photons bumping into each other.

The catch? These photons were a little off their game, meaning they weren’t acting like themselves and instead had temporarily become “Virtual.” By studying these super-rare interactions, physicists hope to reveal some of the fundamental properties of light and possibly even discover new high-energy physics, like grand unified theories and supersymmetry.

Usually, it’s a good thing that photons don’t interact with each other or bounce off each other, because that would be a total madhouse with photons never going anywhere in any sort of straight line.

Every once in a while – extremely, incredibly rarely – one of those photons would briefly turn into a pair composed of a positron and an electron; then, another photon would see one of those positrons or electrons and talk to it.

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Inside the ‘Black Box’ of a Neural Network

Neural networks have proven tremendously successful at tasks like identifying objects in images, but how they do so remains largely a mystery.

On Wednesday, Carter’s team released a paper that offers a peek inside, showing how a neural network builds and arranges visual concepts.

Olah’s team taught a neural network to recognize an array of objects with ImageNet, a massive database of images.

Neural networks are composed of layers of what researchers aptly call neurons, which fire in response to particular aspects of an image.

Researchers trying to understand how neural networks function have been fighting a losing battle, he points out, as networks grow more complex and rely on vaster sums of computing power.

As an illustration, Olah pulls up an ominous photo of a fin slicing through turgid waters: Does it belong to a gray whale or a great white shark? As a human inexperienced in angling, I wouldn’t hazard a guess, but a neural network that’s seen plenty of shark and whale fins shouldn’t have a problem.

Neural networks are generally excellent at classifying objects in static images, but slip-ups are common-say, in identifying humans of different races as gorillas and not humans.

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Dr. Elon & Mr. Musk: Life Inside Tesla’s Production Hell

The previous year, Musk had made an audacious announcement: His company, which was known-fetishized, actually-for its luxurious electric vehicles, would soon begin manufacturing a new sedan that it planned to sell for just $35,000, putting it within reach of the middle class.

Musk began walking in the crowd, slapping hands while his bodyguard occasionally yelled “No selfies, just high-fives.” Musk phoned other executives.

Musk himself would later estimate that Tesla was burning though up to $100 million a week as thousands of employees tried to build Musk’s dreadnought.

A previous employee remembered Musk saying that Tesla’s goal was to save the world.

At the party, Musk was scheduled to give the first 30 Model 3 customers-most of them employees-their automobiles.

Todd Maron, Tesla’s general counsel, said in defense of Musk that “There’s a lot of people outside Tesla who will sort of sugarcoat what they actually think of your performance, or of an issue, because they don’t really want to have the hard conversation.” Musk “Is someone who, I think, puts a lot of effort into forcing himself to be fully honest, and when he genuinely thinks someone has failed at something, he will let you know that he thinks you have failed at that and that the company requires that you do better so that we can achieve our mission and succeed.”

In January 2018, shareholders agreed to compensate Musk as much as $55 billion over the next 10 years, but only if the Musk continues to lead the company and hits 12 milestones, including a market capitalization of $650 billion, roughly 10 times what it’s worth today.

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