01/17/18 — In collaboration with several Berkeley Engineering faculty, the Berkeley-based startup institute The House has formed a new AI-focused startup accelerator.
12/20/17 Economist — At the annual Neural Information Processing Systems conference this month, thousands of researchers flocked to Long Beach to devour algorithms, keynotes by famous speakers and all things artificial intelligence, prompting EECS associate professor Ben Recht to lament the event's growing corporatism.
12/18/17 MIT Tech Review — Artificial intelligence expert and Berkeley Engineering alum Andrew Ng (Ph.D.'03 EECS) is on a mission to AI-ify manufacturing, starting with partners like Foxconn.
12/06/17 — Berkeley researchers, led by EECS assistant professor Sergey Levine, have developed a learning technology that enables robots to imagine the future of their actions so they can figure out how to manipulate objects they have never encountered before.
11/20/17 SF Chronicle — "Slaughterbots," a not-so-futuristic video warning against the development of autonomous weapons, has gone viral. Co-created by EECS professor Stuart Russell and the Future of Life Institute, it was released this week at the United Nations Convention on Conventional Weapons in Geneva.
11/07/17 — Robots today must be laboriously programmed by writing computer code, but imagine donning a VR headset and virtually guiding a robot through a task instead. That's the vision of EECS professor Pieter Abbeel and three of his students.
11/06/17 New York Times — As the tech industry hunts for new ways to quicken the development of artificially intelligent machines, Berkeley researchers are focusing on machine-learning algorithms that will help robots learn new tasks based on things they've learned before. "Computers are going to invent the algorithms for us, essentially," says EECS professor Pieter Abbeel.
10/18/17 TechCrunch — Toy maker Mattel has teamed up with Berkeley-born Dash Robots to create Kamigami, a robotics platform that lets kids build their own six-legged robotic bugs from foldable plastic sheets.
10/16/17 — In a new report from Berkeley's Real-Time Intelligent Secure Execution Lab (RISELab), leading researchers outline challenges in systems, security and architecture that may impede the progress of artificial intelligence, and propose new research directions to address them.
09/12/17 New York Times — Robotics researchers in Berkeley Engineering's AUTOLAB are using neural networks and machine learning to teach robots to grab things they have never encountered before - a remarkable achievement that could drive significant changes for some of the world's biggest businesses.
08/24/17 — Berkeley Engineering professors Pieter Abbeel and Michael Jordan, both experts in machine learning, have been appointed as joint faculty in IEOR in addition to their primary appointments in EECS (and Statistics for Jordan).
08/17/17 New York Times — IEOR professor and roboticist Ken Goldberg discusses the problems of robots and uncertainty: getting machines to mimic the way humans intuitively plan for their next action and deal with events they've never before experienced.
08/17/17 MIT Tech Review — EECS assistant professor Anca Dragan is working to distill complicated or vague human behavior into simple mathematical models that robots can understand. Her visionary work has landed her a spot on MIT Tech Review's 35 Innovators Under 35 list.
07/18/17 IEEE Spectrum — Thanks to some mechanical fine-tuning and the clever addition of a pair of thrusters, Salto-1P, the tiny jumping robot from EECS professor Ronald Fearing's Biomimetic Millisystems Lab, is leaping longer, faster and higher than ever. Prepare to be amazed.
05/25/17 Engadget — When you first played Super Mario Bros, you probably started by exploring, not by racing through the game. Berkeley computer scientists have imparted that same sense of curiosity into their algorithm in a move that could drastically advance the field of artificial intelligence.
05/25/17 MIT Technology Review — A dexterous multi-fingered robot, developed by IEOR professor Ken Goldberg and his team, practiced by using virtual objects in a simulated world, showing how machine learning and the cloud could revolutionize manual work.
05/09/17 WBUR — In this radio piece, IEOR professor Ken Goldberg participates in a panel discussion on what the future might look like as sensing, automation and robotics become more prevalent.