After Uber's fatal self-driving crash last month in Tempe, Arizona, most observers had two basic question: Why did the car not see Elaine Herzberg crossing the street and stop before hitting her? And how can we stop this happening again, to someone else? The ride-hailing company has indefinitely suspended its testing program, and is cooperating with the National Transportation Safety Board's investigation of the crash. The NTSB hasn't revealed any findings yet, but the lidar--the laser-shooting sensor that should have spotted Herzberg, even in the dark--is an obvious focus. Maybe it had a blind spot, or lacked the resolution to identify Herzberg as a pedestrian.

Apple has announced the creation of Daisy, a robot specifically designed to quickly disassemble several different iPhone models and recycle parts that can be used again, the company detailed in a Thursday press release. Daisy is actually a bit of a composite itself--the robot is made up of parts from another recycling robot, Liam, that was created in 2016, the release said. Daisy will be used first in the US and Europe and then expand worldwide. According to Apple's release, Daisy will be able take apart nearly 200 iPhones per hour, pushing the company closer to its goal of ending its reliance on mining for vital smartphone materials like cobalt. From every 100,000 iPhones Daisy disassembles, the release said, Apple will be able to harness about 1 kg of gold, 7.5kg of silver, almost two tons of aluminum, and 11kg worth of certain rare-earth elements and minerals like cobalt, palladium, tungsten, tantalum, and tin.

Robots and AI have been the talk of town in recent years. Many organizations, such as Foxconn, Amazon, and Siemens, have taken to deploying industrial robots in the workforce for very specific tasks, such as product packaging, assembly, supply chain operations, and so on, automating the manual work traditionally done by the human workers. A survey conducted by the International Federation of Robotics forecasted that by 2018, up to 1.3 million robots will be in service worldwide, with China accounting for more than one-third of all installed. In addition to industrial robots, many other technology giants also made headway building personal robot assistants that we will likely welcome into our homes in the near future. However, with more robots working and living among people and taking more responsibilities in the business environment, we ought to ask ourselves – are these robots adequately secured?

While China's two aircraft carriers, the Liaoning and the nearly completed CV-17, have ski ramps that would likely limit them to vertical take-off and landing (VTOL) drones, the next Chinese carrier, CV-18, will likely have electromagnetic catapults. Those catapults would enable CV-18 and its nuclear-powered successors to launch heavier and faster drones propelled by turbofan engines. It's likely the drones Shi mentions will be sophisticated, heavier versions of today's systems. The Lijian, for example, uses a flying wing body (just like the B-2 bomber and X-47B drone) and has two bomb bays that could accommodate 2 tons of artillery. A carrier variant would have reinforced landing gears and structures to handle the forces involved in catapult launch and assisted recovery. They may also have larger fuel tanks for extended range.

A startup company in California is using machine learning and artificial intelligence to advise fire departments about how to plan for earthquakes and respond to them. The company, One Concern, hopes its algorithms can take a lot of the guesswork out of the planning process for disaster response by making accurate predictions about earthquake damage. It's one of a handful of companies rolling out artificial intelligence and machine learning systems that could help predict and respond to floods, cyber-attacks and other large-scale disasters. Nicole Hu, One Concern's chief technology officer, says the key is to feed the computers three main categories of data. The first is data about homes and other buildings, such as what materials they're made of, when they were built and how likely they are to collapse when the ground starts shaking.

The governor, a first-term Republican, has come under mounting pressure from Missouri politicians of both parties to resign since he was charged in an unrelated investigation with criminal invasion of privacy. He was accused in that case of taking a compromising photo of a woman with whom he was involved without her consent and threatening to use it as blackmail.

Andrei Iancu, director of the U.S. Patent and Trademark Office (USPTO), says that the courts have strayed on the issue of patent eligibility, including signaling he thought algorithms using artificial intelligence were patentable as a general proposition. That came in a USPTO oversight hearing Wednesday (April 18) before a generally supportive Senate Judiciary Committee panel. Both Iancu and the legislators were in agreement that more clarity was needed in the area of computer-related patents, and that PTO needed to provide more precedential opinions when issuing patents so it was not trying to reinvent the wheel each time and to better guide courts. At issue are Supreme Court decisions that Iancu said had injected "a degree of uncertainty" into that area of law. He said PTO would come up with guidelines to help better define what is patent-eligible, but that it was a challenge that needed to be addressed by Congress and stakeholders as well.

As I've blogged about at length in this space, the US economy won't see sustained growth unless we can boost productivity. And there are a few different theories out there for why productivity growth has been so sluggish since the mid-2000s. Maybe ideas are becoming harder to find, maybe productivity has increased and we aren't measuring it correctly, or maybe productivity growth is here but it's just not evenly distributed yet. If that last theory is correct, and there's some reason to think it is (per a Commerce Department study, the digital sector has grown at an average annual rate of 5.6% over the last decade, compared to 1.5% overall), then the relevant question for policymakers is how to get these innovations to spread throughout the rest of the economy. That's where the new McKinsey report "Notes from the AI Frontier" comes in.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Playground cofounder and CTO Peter Barrett discusses why the firm is betting big on the future of robots. Robots are finally learning how to open doors.

When Amazon first introduced developer tools that let people build stuff for Alexa, the company made a conscious decision to call these functions "skills" rather than apps. It was a subtle way of making Alexa seem capable, and also, suggesting to developers that building these skills would be a low lift. With just a "few lines of code," Amazon promised, "you can build entirely new experiences designed around voice." Amazon says most Echo users in the US have tried these third-party skills at least once, but getting them to work can be tricky. Alexa's voice skills often require super specific queries, and until Amazon started paying attention to the discovery process, taking the time to find new skills felt like a non-essential burden. Now, Amazon has decided to make Alexa's skills all about you: your dad jokes, your homework, your birthday.