Apple has acquired German eye tracking company SensoMotoric Instruments (SMI), MacRumors reported Monday. SMI has been working on eye-tracking and vision related technology since its inception in 1991. It became active in the virtual reality segment in 2016 when it announced an eye-tracking development kit for the HTC Vive VR headset. In the report, MacRumors cited the power of attorney signed by German law firm Hiking Kühn Lüer Wojtek giving power to Delaware-based shell company Vineyard Capital Corporation to represent it in all business related to the acquisition. Curiously, the agreement has been signed by Gene Levoff, Apple's vice president of corporate law, which indicates Vineyard Capital Corporation might be one of the shell companies owned by Apple that it uses to hide its acquisitions.

If Amazon has its way, cities around the US will have vertical drone centers shaped like giant beehives in the middle of downtown districts, allowing the online retailer to coordinate speedy deliveries by unmanned aircrafts. The company has filed for a patent for "multi-level fulfillment centers" that would accommodate the landing and takeoff of drones in dense urban settings, the latest example of Amazon's futuristic vision of reshaping the way people receive packages. The application filed with the US Patent and Trademark Office, which was written in 2015 and published last week, included a number of drawings of drones flying in and out of tall cylinder-shaped buildings that Amazon wants to locate in central metropolitan areas. The centers would allow Amazon to shift away from the traditional model of large single-story warehouses that temporarily store packages before they are shipped to customers. Those buildings are typically located on the outskirts of urban areas and are not convenient for deliveries into cities where populations continue to swell, the company noted.

Elon Musk has hired a new director of AI research at Tesla, and it may signal a plan to rethink the way its automated driving works. This week, Musk poached Andrej Karpathy, an expert on vision, deep learning, and reinforcement learning, from OpenAI, a nonprofit that Musk and others are funding that's dedicated to "discovering and enacting the path to safe artificial general intelligence." After Stanford, Karpathy interned with DeepMind, where reinforcement learning is a major focus. Appointing Karpathy a Tesla's director of AI research indicates something else about the challenge of autonomous driving: there's some distance left to go before it's solved (see "What to Know Before You Get in a Self-Driving Car").

This week, U.S. drone companies met with President Trump to discuss industry regulations. NPR's Melissa Block talks with April Glaser of Recode about how these companies actually want more regulation.

An ordinary smart meter gives your local utility useful information about how much energy you are using--every hour, or even as often as every minute. This helps utility planners efficiently adjust electricity generation to meet demand or encourage reductions in demand when necessary. But machine learning systems, looking at that data, can tell something else about your home besides its energy use--they can tell if you are home, or if you are not. That's what University of California at Berkeley researchers Ming Jin, Ruoxi Jia, and Costas Spanos found out. That information, Jin says, is also useful for utilities--they can call or show up to perform necessary maintenance when you are home, and not waste personnel time trying to reach you.

For all its heat, the fire that is Uber in 2017 hasn't scorched everything. While the nigh-apocalyptic past six months have felled founder and CEO Travis Kalanick, and sparked questions about its ability to keep its employees safe, let alone happy, Uber's self-driving car program seems to be doing just fine. It's a rare but vital bit of good news for Uber, for which autonomy is an existential question. If another company figures out how to operate a taxi service without paying drivers and Uber cannot, it's lights out, unicorn. "What would happen if we weren't a part of that future?

It takes up to 24 minutes for a signal to travel between Earth and Mars. If you're a Mars rover wondering which rock to drill into, that means waiting at least 48 minutes to send images of your new location to NASA and then receive marching orders. It's a lot of idle time for a robot that cost $2.6 billion to build. That's why engineers are increasingly giving spacecraft the ability to make their own decisions. Space robots have long been able to control certain onboard systems--to regulate power usage, for example--but artificial intelligence is now giving rovers and orbiters the ability to collect and analyze science data, then decide what info to send back to Earth, without any human input.

Rats are nimble navigators, able to find their way around, under, and over obstacles, and through the tightest spaces. Roboticists have long dreamed of giving their creations similar navigation skills. To be useful in the real world, robots must be able to find their way around on their own. Some are already learning to do that in homes, offices, warehouses, hospitals, and hotels--and in the case of self-driving cars, entire cities. Despite that progress, robots still struggle to perform the tasks for which they're designed even under mildly challenging conditions.

That is until last year, when Microsoft built one that could. Automatic speech recognition, or ASR, is an area that has gripped the firm's chief speech scientist, Xuedong Huang, since he entered a doctoral program at Scotland's Edinburgh University. "I'd just left China," he says, remembering the difficulty he had in using his undergraduate knowledge of the American English to parse the Scottish brogue of his lecturers. "I wished every lecturer and every professor, when they talked in the classroom, could have subtitles." In order to reach that kind of real-time service, Huang and his team would first have to create a program capable of retrospective transcription.