Computers can beat humans at sophisticated tasks like the game Go, but can they also drive a car, … [+] speak languages, play soccer, and perform a myriad of other tasks like humans? Here’s what AI can learn from biology.
A few years back, DeepMind’s Demis Hassabis famously prophesized that AI and neuroscience will positively feed into each other in a “virtuous circle.” If realized, this would fundamentally expand our insight into intelligence, both machine and human.
We’ve already seen some proofs of concept, at least in the brain-to-AI direction. For example, memory replay, a biological mechanism that fortifies our memories during sleep, also boosted AI learning when abstractly appropriated into deep learning models. Reinforcement learning, loosely based on our motivation circuits, is now behind some of AI’s most powerful tools.
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Every major galaxy is home to a supermassive black hole, and our own Milky Way is no exception. Astronomers recently found something unexpected near this massive object — 4 mysterious objects, each similar to a pair of bizarre bodies spotted in recent years in this same region of the galaxy.
Our local supermassive black hole, Sagittarius A* (Sgr A*, pronounced Sag A star), contains roughly 4 million times as much mass as the Sun. Not far from this black hole, members of a newly-discovered class of objects are caught in a gravitational dance with a massive body.
A little over a year ago, Caltech’s Lihong Wang developed the world’s fastest camera, a device capable of taking 10 trillion pictures per second. It is so fast that it can even capture light traveling in slow motion.
But sometimes just being quick is not enough. Indeed, not even the fastest camera can take pictures of things it cannot see. To that end, Wang, Bren Professor of Medical Engineering and Electrical Engineering, has developed a new camera that can take up to 1 trillion pictures per second of transparent objects. A paper about the camera appears in the January 17 issue of the journal Science Advances.
The camera technology, which Wang calls phase-sensitive compressed ultrafast photography (pCUP), can take video not just of transparent objects but also of more ephemeral things like shockwaves and possibly even of the signals that travel through neurons.
ESA’s technical heart has begun to produce oxygen out of simulated moondust.
A prototype oxygen plant has been set up in the Materials and Electrical Components Laboratory of the European Space Research and Technology Centre, ESTEC, based in Noordwijk in the Netherlands.
“Having our own facility allows us to focus on oxygen production, measuring it with a mass spectrometer as it is extracted from the regolith simulant,” comments Beth Lomax of the University of Glasgow, whose Ph.D. work is being supported through ESA’s Networking and Partnering Initiative, harnessing advanced academic research for space applications.
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This is the boat of the future and we are sailing.
Thanks to Eric Klien Brent Ellman and others.
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Xenobots have been called the world’s first “living robots”. They are made entirely of living tissue, and can be programmed to move towards a certain object.
We all subconsciously learn complex behaviors in response to positive and negative feedback, but how that works in the brain remains a century-long mystery. By examining a powerful variant of reinforcement learning, dubbed distributional reinforcement learning, that outperforms original methods, the team suggests that the brain may simultaneously represent multiple predicted futures in parallel. Each future is assigned a different probability, or chance of actually occurring, based on reward.
Here’s the kicker: the team didn’t leave it as an AI-inspired hypothesis. In a collaboration with a lab at Harvard University, they recording straight from a mouse’s brain, and found signs of their idea encoded in its reward-processing neurons.
But a new figure blows all of these out of the water. Last week, British renewable energy developer SSE announced construction of Dogger Bank Wind Farm off the eastern coast of England in the North Sea.
With a capacity of 3.6 gigawatts (GW), Dogger Bank will be three times bigger than the world’s biggest existing wind farm, the nearby 1.2 GW Hornsea One.
Located near a seaside town called Ulrome, which is 195 miles north of London, Dogger Bank will have three separate sites—Creyke Beck A, Creyke Beck B, and Teesside A—each with a 1.2 GW capacity, and construction is slated to take two years.
