Iron Maiden might not have released original music for half a decade, but YouTuber Funk Turkey has employed artificial intelligence to create a track in imitation of the band entitled'Power Gravy'. The generated lyrics open: "8 and 40 souls became the number of the Moon / when you're debating witches and the clouds In His Majesty's Craft", while the chorus concerns the titular'Power Gravy'. "Vocals are… hard," Connor wrote on YouTube. "Bruce Dickinson is very hard to emulate/impersonate, so I just did the best I could and hope it's not awful. That man has golden pipes. It sounds like a South Park parody, but then again, it is a parody, so… uhhhh… don't take it too seriously."

Personal assistant AI systems such as Siri, Cortana, and Alexa have become widely used as a means to accomplish tasks through natural language commands. However, components in these systems generally rely on supervised machine learning algorithms that require large amounts of hand-annotated training data, which is expensive and time consuming to collect. The ability to incorporate unsupervised, weakly supervised, or distantly supervised data holds significant promise in overcoming this bottleneck. In this paper, we describe a framework that leverages user engagement signals (user behaviors that demonstrate a positive or negative response to content) to automatically create granular entity labels for training data augmentation. Strategies such as multi-task learning and validation using an external knowledge base are employed to incorporate the engagement annotated data and to boost the model's accuracy on a sequence labeling task. Our results show that learning from data automatically labeled by user engagement signals achieves significant accuracy gains in a production deep learning system, when measured on both the sequence labeling task as well as on user facing results produced by the system end-to-end. We believe this is the first use of user engagement signals to help generate training data for a sequence labeling task on a large scale, and can be applied in practical settings to speed up new feature deployment when little human annotated data is available.

This was a busy year for robotics! The 10 most read Robohub articles in 2017 show an increased interest in machine learning, and a thirst to learn how robots work and can be programmed. Highlights also include the Robohub Podcast, which just celebrated its 250th episode (that's 10 years of bi-weekly interviews in robotics), the Robot Launch Startup Competition, and our yearly list of 25 women in robotics you need to know about. Finally, we couldn't skip over some of the remarkable events of 2017, including a swarm of drones flying over Metallica, and Sophia "gaining citizenship".

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 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. Two Cassies give you a tour of Agility Robotics, where they mostly don't believe in furniture: Final assembly can be done in just over a minute and a half, as long as you're willing to be sped up a little bit: Speaking of Cassies (and we do like speaking of Cassies), Michigan Robotics just got theirs (No. 001!) and we're expecting GREAT THINGS: My question now is whether all the robots are going to be called "Cassie," or whether each will (eventually) be renamed when it arrives at its destination. My other question now is whether the first Cassie was "000" or "001," and also why don't they think they'll be making more than a thousand Cassies, because that seems pessimistic.

Metallica's European WorldWired tour, which opened to an ecstatic crowd of 15,000 in Copenhagen's sold-out Royal Arena this Saturday, features a swarm of micro drones flying above the band. Shortly after the band breaks into their hit single "Moth Into Flame", dozens of micro drones start emerging from the stage, forming a large rotating circle above the stage. As the music builds, more and more drones emerge and join the formation, creating increasingly complex patterns, culminating in a choreography of three interlocking rings that rotate in position. This show's debut marks the world's first autonomous drone swarm performance in a major touring act. Unlike previous drone shows, this performance features indoor drones, flying above performers and right next to throngs of concert viewers in a live event setting.