A new technique for machine learning that allows computers to use algorithms that turn 2D images into 3D is stirring a lot of excitement in the worlds of games, computer graphics and AI. The approach relies on “neural rendering,” which uses a neural network to generate 3D imagery from multiple 2D snapshots. A merger of concepts from the worlds of computer graphics and artificial intelligence, neural rendering gained steam in 2020 when researchers at Google and UC Berkeley demonstrated how a neural network could photorealistically capture a scene in 3D after ingesting several 2D snapshots. Continue reading Algorithms Use NeRFs to Instantly Convert 2D Images to 3D

A conference on “Robots for Good” sought to allay increased fears that robot overlords will soon rule the world and make humans redundant in the workforce. UC Berkeley professor Ken Goldberg, who heads a robotics lab there, spoke about his “radically hopeful vision of the future.” Robots will not replace humans, he said, but rather enable people to focus on what they do best: creativity, innovation, empathy and other inherent human traits. Goldberg also put the fear of robots in historical perspective. Continue reading CES 2020: ‘Robots for Good’ Advocates See Hopeful Future