Two years ago, we spotted an interesting delivery drone concept at a military expo in Washington, D.C., called TACAD, or TACtical Air Delivery. The idea was to use gliders made out of cheap, disposable materials to deliver a substantial amount of supplies over long distances. You'd have to launch these gliders from larger aircraft, but they'd be able to deliver hundreds of kilograms of supplies over a hundred kilometers away, and then they'd just be left where they landed, simple as that. Like many concepts that we see at trade shows, we didn't necessarily expect much to come of this idea, but we're delighted to report that the folks behind it--Logistic Gliders Inc. (LGI), based in Dixon, Calif.--have recently concluded a successful series of flight tests with the U.S. Marine Corps. There are two different kinds of gliders that LGI is working on: The LG-1K, which can carry about 300 kg, and the larger LG-2K, which can carry over 700 kg.

The history of AI is often told as the story of machines getting smarter over time. What's lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies. In this six-part series, we explore that human history of AI--how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While it can be exciting to be swept up by the idea of super-intelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are. On 14 February 1946, journalists gathered at the Moore School of Engineering at the University of Pennsylvania to witness a public demonstration of one of the world's first general-purpose electronic digital computers: the Electronic Numerical Integrator and Computer (ENIAC).

GITAI is a robotics startup with offices in Japan and the United States that's developing tech to put humanoid telepresence robots in space to take over for astronauts. Today, GITAI is announcing a joint research agreement with JAXA (the Japanese Aerospace Exploration Agency) to see what it takes for robots to be useful in orbit, with the goal of substantially reducing the amount of money spent sending food and air up to those demanding humans on the International Space Station. It's also worth noting that GITAI has some new hires, including folks from the famous (and somewhat mysterious) Japanese bipedal robot company SCHAFT. A quick reminder about SCHAFT: The company was founded by members of the JSK Laboratory at the University of Tokyo in order to build a robot to compete in the DARPA Robotics Challenge Trials in 2013. SCHAFT won the DRC Trials by a substantial margin, scoring 27 points out of a possible 32, 7 more points than the second place team (IHMC).

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. Humans are very good at object generalization--even when we're very young, it takes just a few samples from a class of objects for us to be able to identify other objects that fit into the same class. The amount of training data that it takes for a human to be able to identify (say) a previously unseen coffee mug based on their previous coffee mug experience is tiny.

Last June, a team at Harvard Medical School and MIT showed that it's pretty darn easy to fool an artificial intelligence system analyzing medical images. Researchers modified a few pixels in eye images, skin photos and chest X-rays to trick deep learning systems into confidently classifying perfectly benign images as malignant. These so-called "adversarial attacks" implement small, carefully designed changes to data--in this case pixel changes imperceptible to human vision--to nudge an algorithm to make a mistake. That's not great news at a time when medical AI systems are just reaching the clinic, with the first AI-based medical device approved in April and AI systems besting doctors at diagnosis across healthcare sectors. Now, in collaboration with a Harvard lawyer and ethicist, the same team is out with an article in the journal Science to offer suggestions about when and how the medical industry might intervene against adversarial attacks.

Stanford University launched its Institute for Human-Centered AI on Monday. Known as Stanford HAI, the institute's charter is to develop new technologies while guiding AI's impact on the world, wrestle with ethical questions, and come up with helpful public policies. The Institute intends to raise US $1 billion to put towards this effort. The university kicked off Stanford HAI (pronounced High) with an all-day symposium that laid out some of the issues the institute aims to address while showcasing Stanford's current crop of AI researchers. The most anticipated speaker on the agenda was Microsoft co-founder Bill Gates.

A version of this article appears in the IEEE Robotics & Automation Magazine (Volume 26, Issue 1, March 2019). In mid-November, we received the sad news that Alphabet is closing SCHAFT, a spinoff of the University of Tokyo robotics lab. The decision comes one year after Boston Dynamics was sold to SoftBank, the company that also acquired Aldebaran Robotics (known for the Pepper and Nao robots). During the 2018 IEEE/Robotics Society of Japan International Conference on Intelligent Robots and Systems, we heard that Rethink Robotics, which created the collaborative robot industry and had a large impact on our view of robots in industrial applications, had closed its doors. Some months before, Jibo and Mayfield Robotics, makers of Kuri, were forced to shut down sales and operations.

The history of AI is often told as the story of machines getting smarter over time. What's lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies. In this six-part series, we explore that human history of AI--how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While it can be exciting to be swept up by the idea of super-intelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are. In the year 1770, at the court of the Austrian Empress Maria Theresa, an inventor named Wolfgang von Kempelen presented a chess-playing machine.

Last week, the 2020 Tokyo Olympic Games organizing committee announced the launch of the "Tokyo 2020 Robot Project." The project will involve the deployment of an assortment of robots to do useful things for visitors at the games, but so far, we've just seen specific details about two: Toyota's Human Support Robot (HSR) and Delivery Support Robot (DSR). These robots are supposed to be part of a "practical real-life deployment helping people," and the idea is that HSR and DSR will work together to assist disabled visitors, showing them to their seats and fetching food or other items that can be ordered with a tablet. The Toyota HSR is a mobile manipulator, able to move around and pick stuff up. It can do all kinds of things, provided that you can program it to do all of those things, which is not easy, especially if it's supposed to operate autonomously in an Olympic venue rather than a robotics lab.

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. This soft gripper from MIT is based on an origami "magic-ball." It's a "magic-ball gripper," and that hyphen placement is absolutely critical to it functioning appropriately.