The advent of the Industrial Internet has raised the bar for security analysts and data scientists, a workforce whose number is quickly being dwarfed by the amount of connected machines. Now, machine learning and artificial intelligence professionals are teaming with traditional embedded vendors to help suppress the rising tide of cyber threats and Big Data. On their website, cyber security firm Norse Corporation generates a detailed, real-time map of cyber attacks occurring around the world, including the attack origin, attack type, and attack target (Figure 1). Hundreds of attacks are registered in any given minute, which, while disconcerting, pales in comparison with the number of systems being connected to the Industrial Internet. This brief exercise demonstrates a couple of things: 1) the quantity and speed of cyber threats that can be used to attack vulnerable, safety-critical industrial systems; and 2) the growing need for data scientists and security analysts1, as well as tools and technologies to support them as the Internet of Things (IoT) expands.

Called the structure-mapping engine (SME), the new model is capable of analogical problem solving, including capturing the way humans spontaneously use analogies between situations to solve moral dilemmas. Previous models of analogy, including prior versions of SME, have not been able to scale to the size of representations that people tend to use. Forbus's new version of SME can handle the size and complexity of relational representations that are needed for visual reasoning, cracking textbook problems, and solving moral dilemmas. To encourage research on analogy, Forbus's team is releasing the SME source code and a 5,000-example corpus, which includes comparisons drawn from visual problem solving, textbook problem solving, and moral decision making.

Northwestern Engineering's Ken Forbus is closing the gap between humans and machines. Using cognitive science theories, Forbus and his collaborators have developed a model that could give computers the ability to reason more like humans and even make moral decisions. Called the structure-mapping engine (SME), the new model is capable of analogical problem solving, including capturing the way humans spontaneously use analogies between situations to solve moral dilemmas. "In terms of thinking like humans, analogies are where it's at," said Forbus, Walter P. Murphy Professor of Electrical Engineering and Computer Science in Northwestern's McCormick School of Engineering. "Humans use relational statements fluidly to describe things, solve problems, indicate causality, and weigh moral dilemmas."

A fatal accident that occurred while Tesla's Autopilot technology was engaged may have a significant bearing on the future of automated driving. The National Highway Traffic Safety Administration said yesterday that it is investigating the accident, which occurred near Williston, Florida, last month when a Model S crashed into a trailer making a left turn in front of it. NHTSA's investigation does not mean the agency believes the technology contributed to the accident or is defective. But the incident will inevitably raise questions about the performance of the technology and the way drivers treat it. The auto industry will certainly watch closely to see how it may shape regulations and influence the public perception of automated-driving technology.

The man killed in a crash while using the autopilot function of a Tesla Model S electric vehicle posted a YouTube video a month before the fatal crash showing the technology saving him from another collision and wrote that he was "very impressed." I have done a lot of testing with the sensors in the car and the software capabilities," Joshua Brown, 40, of Canton, Ohio, wrote on April 5 in comments posted with the 41-second video. "I have always been impressed with the car, but I had not tested the car's side collision avoidance," he said. Then on May 7, Brown, a former Navy Seal, was killed when his Tesla crashed into a tractor trailer in Williston, Fla. Federal regulators said Thursday they had opened an investigation into the fatality, thought to be the first in the auto industry involving an autonomous driving feature. The National Highway Traffic Safety Administration said its Office of Defects Investigation was conducting a preliminary evaluation of the autopilot function. The agency is expected to issue guidelines for autonomous vehicles this month. Automakers do not need to have autonomous driving functions approved by NHTSA but must certify their vehicles meet safety standards. Calling Brown's death "a tragic loss," Tesla said it was the first-known fatality involving its autopilot feature. The technology, which is in public beta testing and must be activated by the driver, has been used in 130 million miles of driving without a fatality, the company said. The crash took place at 3:40 p.m. May 7 on U.S. Route 27A during clear and dry conditions, according to the accident report from the Florida Highway Patrol. Brown's vehicle was headed east when a tractor trailer driven by Frank Baressi of Palm Harbor, Fla., traveling in the opposite direction, made a left turn onto a side street. The Tesla's roof hit the underside of the tractor trailer. The car skidded under the truck and off the road, plowing through two wire fences before crashing into a utility pole, the accident report said. Baressi told the Associated Press that Brown was "playing'Harry Potter' on the TV screen" in the car when the crash took place. Kim Montes, a spokeswoman for the Florida Highway Patrol, told The Times that a portable DVD player was found in the Tesla but said she did not know whether it had been in use. "At the time of the impact, we don't know what the status of that DVD player was.

Video Friday is your weekly selection of awesome robotics videos, collected by your unibrowed Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two 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. We don't usually lead Video Friday with a long talk, but Nic Radford was at Campus Party in Mexico to talk about Valkyrie and the DRC. It's a tremendous talk, with lots of candid detail and video that we've never seen before.

Pretty much every cinematic portrayal of artificial intelligence has been less than encouraging. HAL 9000 kills the crew members on the Discovery in 2001: A Space Odyssey, making us all a little bit afraid of handing the reins over to computers. Sonny kills his creator in I, Robot, increasing worldwide scepticism about the integration of humans and their smart robots. Even real life AI has given us pause. For example, when an IBM computer defeated Russian chess Grandmaster Garry Kasparov in the 1990s, it was definitely a cause for concern.

We've shown a few times here how you can run R code on data in the cloud with Azure ML Studio, and even how to enable that code as a web service to be called from other applications. But what if you want to run code in a compiled language, like C? Fortunately, you can take advantage of R's built-in support for compiled code, and call it from a package you upload to Azure ML. (A similar process works for Python.) You can read the details in the blog post, Running Compiled Code on Azure ML in R and Python.

"What do I type?" is the big question making chatbots hard to use. So today Facebook Messenger is giving chatbot developers new "Quick Reply" buttons and persistent menu options to make their bots easier to navigate. Messenger bots can also now send videos, audio, GIFs, and files so they can encompass wider range of use cases. People can now rate bots with one to five stars to teach developers how to improve, though there's no word on the chatbot analytics Facebook has promised. And if customers opt in, developers will be able to connect these customers' accounts to Messenger accounts to allow more seamless communication with them.

Your phone's artificial intelligence knows you almost as well as you know yourself (maybe even better). So when it suggests ways to get through tomorrow's calendar, you trust its advice," Shankland writes. "Get ready, people: It's not that far off." "Since the first AI research effort 60 years ago at a Dartmouth College conference, humanity has been heading toward computer-based systems that can eventually learn and adapt for themselves," Shankland writes. "Super-capable AI will have its downside.