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Using Coffee to Treat Diabetes

This is the Freethink Dispatch, our rundown of the stories that mattered from the frontiers of a changing world. This week, engineers created brain-surgery robots that can work inside an MRI, scientists found a way to use coffee to treat diabetes, and a startup is making fresh produce that lasts twice as long. All that and more, plus a new episode of Freethink’s original hit series Superhuman about how doctors are reprogramming the immune system to kill untreatable cancers.

These stories made us think and got us inspired. We hope they’ll do the same for you.

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This AI can see you through walls

X-ray vision has long seemed like a far-fetched sci-fi fantasy, but over the last decade a team led by Professor Dina Katabi from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has continually gotten us closer to seeing through walls.

Their latest project, “RF-Pose,” uses artificial intelligence (AI) to teach wireless devices to sense people’s postures and movement, even from the other side of a wall.

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Opinions on #ArtificialIntelligence are a dime a dozen, unless you’re hearing from one of the field’s pioneers

Join us at D60, DARPA’s 60th anniversary symposium, to learn from Ron Brachman about how #AI rose to prominence.


Artificial Intelligence has experienced waves of excitement before, but we have never seen the kind of worldwide enthusiasm that we see now, especially in the commercial sector, where AI has become the central mission of some of the world’s most powerful tech companies. DARPA is known for being the first supporter of AI research and panelists will highlight the impetus DARPA provided to the field’s most central technological areas, and give insights about where the field is going next.

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How Artificial Intelligence Could Help Us Live Longer

Insilico and its researchers are the first in the world to use GANs to generate molecules.

“The GAN technique is essentially an adversarial game between two deep neural networks,” as Alex explains.

While one generates meaningful noise in response to input, the other evaluates the generator’s output. Both networks thereby learn to generate increasingly perfect output.

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