Robots just helped shed light on a maritime tragedy. The US Coast Guard, National Transportation Safety Board and Woods Hole Oceanographic have used both an autonomous underwater vehicle (AUV) and a fiber-controlled craft to find the voyage data recorder of the El Faro, a cargo ship that sank near the Bahamas during Hurricane Joaquin last October. That's no mean feat when its remains are 15,000 feet deep, and the recorder is roughly the size of a coffee can. The recovery should not only help explain the exact circumstances of the El Faro's final moments, but provide some closure to the families of the 33 crew members that lost their lives.

In 2007, Stephanie Costello had a boring office job with a lot of downtime that she spent online. She recalls the day she read one of those articles on MSN.com that have become a staple of the Internet: how to make extra money online. These types of articles often appear in the soft-news sections of MSN, Yahoo and other sites, usually with the message that there is money being left on the table. Costello was intrigued at the prospect of cutting through the boredom of her day with the opportunity to pick up a little extra cash. She went to the website, Mechanical Turk, where companies can post tiny tasks and workers can find and perform them online. It was free to register--no call for an "investment" up front, which indicated that it was not on its face a scam. And she began making money immediately. Costello is a trailblazer of sorts. She was one of the early workers to join Mechanical Turk, the first online, crowd-based, micro-labor platform.

Creativity is alive and well at Samsung, which is developing several cool devices in its labs, including a home companion robot called Otto. The multi-talented robot can answer questions and double as a part-time security system when needed. It is expected to be demonstrated at the Samsung Developer Conference this week in San Francisco. Functionally, Otto is similar in some ways to Amazon Echo, featuring an interactive speaker that can answer questions, order products and play music. But the robot also includes a "head" that hosts a high-definition camera and a display.

A recurring claim at security conferences is that'security is a big data / machine learning (ML) / artificial intelligence (AI) problem'. This is unfortunately wildly optimistic, and wrong in general. While certain security problems can be addressed by ML/AI algorithms, in general the problem of detecting a malicious actor amidst the vast trove of information collected by most organisations, is not one of them. Our faith in AI is based on personal experience ('everything cloud is big data and good') and the memes of the consumerisation era. It is tempting to project this optimism into an enterprise context: the idea that it ought to be possible to sift through large amounts of data to find signs of an attack of breach is intuitively reasonable.

Now that energy storage technologies are coming close to commercial reality, decades of work should result in artificial intelligence (AI) emerging as the third key technology in the transformation of the electricity sector. Combined with scalable generation and storage, it will blur the distinction between suppliers and consumers, with excess local generation being fed into the grid so that entities from individual homeowners to business and municipalities will become "producer-consumers" or "prosumers". Demand management systems will also have a role to play. The introduction of multiple players of widely varying consumption and production patterns connecting into a single nationwide grid is impossible until we have software able to predict and manage energy flows to ensure that supply and demand balance at all times. There are obvious drivers also for energy storage at small scale, particularly for remote locations. Apart from the potential for autonomy, and the ability to smooth draw from the grid (avoiding or at least reducing demand-based charges), local storage could relieve grid congestion and add flexibility to power generation requirements, potentially improving network stability.

Austin-based SparkCognition, a startup applying artificial intelligence and machine learning to the cybersecurity market, has raised 6M in a Series B funding round. The funding came from CME Ventures, Verizon Ventures, The Entrepreneurs' Fund (TEF), and Alameda Ventures. The startup--led by Amir Husain--said the Series B was oversusbcribed. SparkCognition says it has developed machine learning technology which it is applying to both Internet-of-Things (IoT) and cyber security, to automatically detect and identify attacks in IoT infrastructure.

Austin-based SparkCognition, a startup applying artificial intelligence and machine learning to the cybersecurity market, has raised 6M in a Series B funding round. The funding came from CME Ventures, Verizon Ventures, The Entrepreneurs' Fund (TEF), and Alameda Ventures. The startup--led by Amir Husain--said the Series B was oversusbcribed. SparkCognition says it has developed machine learning technology which it is applying to both Internet-of-Things (IoT) and cyber security, to automatically detect and identify attacks in IoT infrastructure.

I recently read an article on robotics by a fellow intern. He cited an example of a flying bird robot developed by Festo Industries' Bionic Learning Network. It is an autonomous ornithopter. While this is certainly an impressive achievement, because they have deciphered the flight of birds, something even more interesting has been going on in the field of machine learning. What is difficult is making them learn how to do things on their own and improve their performance independently.

Volvo XC90 Drive Me is the brand's latest experimental self-driving car (Photo: Volvo) Volvo and Ford are teaming with Google and ride-sharing giants Uber and Lyft to advance the interests of self-driving cars. On Tuesday the companies announced the Self-Driving Coalition for Safer Streets, a group that aims to push the development of self-driving vehicles among lawmakers, regulators, civic groups, businesses and local governments. The group's spokesman is David Strickland, chief of the National Highway Traffic Safety Administration from 2010 to 2014. The coalition plans to work with policymakers to facilitate the deployment of self-driving cars, Strickland said in a statement, including creating "one clear set of federal standards" for autonomous vehicles. The U.S. Department of Transportation reports that last year there were 33,000 fatalities on U.S. roads.

Alphabet Inc's Google unit, Ford Motor Co, the ride-sharing service Uber and two other companies said on Tuesday they are forming a coalition to push for federal action to help speed self-driving cars to market. Sweden-based Volvo Cars, which is owned by China's Zhejiang Geely Holding Group Co, and Uber rival Lyft also are part of the Self-Driving Coalition for Safer Streets. The group said in a statement it will "work with lawmakers, regulators and the public to realize the safety and societal benefits of self-driving vehicles." The coalition said David Strickland, the former top official of the U.S. National Highway Traffic Safety Administration (NHTSA), the top U.S. auto safety agency that is writing new guidance on self-driving cars, will be the coalition's counsel and spokesman. "The best path for this innovation is to have one clear set of federal standards and the coalition will work with policymakers to find the right solutions that will facilitate the deployment of self-driving vehicles," Strickland said in the statement.