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The idea is to offer the predictions for the structure of practically every protein with a known sequence of amino acids free of charge. “We believe that this is the most important contribution to date that artificial intelligence has contributed to scientific knowledge,” he said following the publication of DeepMind’s research in the medical journal Nature.

DeepMind, a company bought by Google, predicts with unprecedented precision the 3D structure of nearly all the proteins made by the human body.

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Rick Osterloh casually dropped his laptop onto the couch and leaned back, satisfied. It’s not a mic, but the effect is about the same. Google’s chief of hardware had just shown me a demo of the company’s latest feature: computational processing for video that will debut on the Pixel 6 and Pixel 6 Pro. The feature was only possible with Google’s own mobile processor, which it’s announcing today.

He’s understandably proud and excited to share the news. The chip is called Tensor, and it’s the first system-on-chip (SoC) designed by Google. The company has “been at this about five years,” he said, though CEO Sundar Pichai wrote in a statement that Tensor “has been four years in the making and builds off of two decades of Google’s computing experience.”

That software expertise is something Google has come to be known for. It led the way in computational photography with its Night Sight mode for low light shots, and weirded out the world with how successfully its conversational AI Duplex was able to mimic human speech — right down to the “ums and ahs.” Tensor both leverages Google’s machine learning prowess and enables the company to bring AI experiences to smartphones that it couldn’t before.

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The US military’s AI experiments are growing particularly ambitious. The Drive reports that US Northern Command recently completed a string of tests for Global Information Dominance Experiments (GIDE), a combination of AI, cloud computing and sensors that could give the Pentagon the ability to predict events “days in advance,” according to Command leader General Glen VanHerck. It’s not as mystical as it sounds, but it could lead to a major change in military and government operations.

The machine learning-based system observes changes in raw, real-time data that hint at possible trouble. If satellite imagery shows signs that a rival nation’s submarine is preparing to leave port, for instance, the AI could flag that mobilization knowing the vessel will likely leave soon. Military analysts can take hours or even days to comb through this information — GIDE technology could send an alert within “seconds,” VanHerck said.

The most recent dry run, GIDE 3, was the most expansive yet. It saw all 11 US commands and the broader Defense Department use a mix of military and civilian sensors to address scenarios where “contested logistics” (such as communications in the Panama Canal) might pose a problem. The technology involved wasn’t strictly new, the General said, but the military “stitched everything together.”

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The paper’s authors said they’ve created an endlessly challenging virtual playground for AI. The world, called XLand, is a vibrant video game managed by an AI overlord and populated by algorithms that must learn the skills to navigate it.

The game-managing AI keeps an eye on what the game-playing algorithms are learning and automatically generates new worlds, games, and tasks to continuously confront them with new experiences.

The team said some veteran algorithms faced 3.4 million unique tasks while playing around 700000 games in 4000 XLand worlds. But most notably, they developed a general skillset not related to any one game, but useful in all of them.

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