DeepMind created five versions of their AI, AlphaStar, and trained them. Their training included footage of human games. A deep neural network trained directly from raw game data by supervised learning and reinforcement learning, said the DeepMind bloggers. AlphaStar, added Coldewey, learned from watching humans play at first, "but soon honed its skills by playing against facets of itself."Facets of itself.
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Next up, another item related to botnets and brain-nets, like who wants to be a millionaire but for everything; I'll call it "crowding", but I'm waiting for a better word, which will come in 5 or 6 years, because this will be happening everywhere. It's the wisdom of the crowd, plus artificial intelligence.
Instantaneous crowdsourcing is the way the article refers to it. Real-time remote backup (made of real people) for an otherwise automated system. In this case, that system is air traffic control, and it is built on top of what we've learned so far with automotive traffic control, via the ridesharing explosion happening right now.
The problem is obvious. A car can now drive on its own pretty darn well. But there will always be an extenuating circumstance, an exception to the algorithm, the trolleyology of a real world, high risk situation. And that's where humans have to come in.
Software in the vehicle would analyze real-time vehicle data and electronically guesses 10-30 seconds into the future to estimate the likelihood of a "disengagement"—a situation where the car's automated systems could need human help.
If the likelihood exceeds a pre-set threshold, the system contacts a remotely located control center and sends data from the car.
The control center's system analyzes the car's data, generates several possible scenarios and shows them to several human supervisors, who are situated in driving simulators.
The humans respond to the simulations and their responses are sent back to the vehicle.
The vehicle now has a library of human-generated responses that it can choose from instantaneously, based on information from on-board sensors.
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This stuff freaks me the out, because there is only one thing on this Earth more powerful than the human brain, and that's more than one human brain, connected together, and operating in real time. That's scarier than AI; it's the combination of humans and artificial intelligence. Semibots is a decent word for it, because it's a little bit of both.
And what's more, we lack the framework for predicting what happens when these hybrid neural networks mature. It's called the science of sync, and it should describe and predict the nature of emergent, synchronized complex networks, except that it doesn't, either because we don't understand it enough, or because such things are impossible to predict.
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I'm not sure how this will pan out in the near term, but keep in mind there are aspirations for an internet in outerspace; the One-Web satellite constellation was just deployed.
Combine that with the emergent synchronization of the human-robot union described above, and we're getting just beyond the point in our future where we can still grasp what the heck is going on.
Notes:
AlphaStar hungry for world domination in StarCraft II fights
Jan 2019, phys.org
Air traffic control for driverless cars could speed up deployment
Feb 2019, phys.org
OneWeb satellite internet mega-constellation set to fly
Feb 2019, BBC
Physicists discover surprisingly complex states emerging out of simple synchronized networks
Mar 2019, phys.org
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