I'm not (quite) dead and intend to go back to posting stuff every now and then. Last July, I've also started a new job, as an assistant professor in the Department of Statistics at Harvard University, after having spent two years in Oxford. At some point, I might post something on the cultural difference between the European English and American communities of statisticians. In the coming weeks, I'll tell you all about a new paper entitled Coupling of Particle Filters, co-written with Fredrik Lindsten and Thomas B. Schön from Uppsala University in Sweden. We are excited about this coupling idea because it's simple and yet brings massive gains in many important aspects of inference for state space models (including both parameter inference and smoothing).

Celestion loudspeakers have powered the performances of many noted guitar and bass players, including legends such as Jimi Hendrix. Deciding whether a loudspeaker is good enough for professional musicians is a lengthy and painstaking process. Each speaker has its own unique sound based on a combination of sonic characteristics, such as midrange character and brightness. Evaluating a musical instrument loudspeaker involves subjective judgement about whether it generates a "good" sound. Only engineers with years of experience can reliably make that decision, and then only after repeated listening to a single loudspeaker and comparing the sounds it produces with those produced by a reference speaker.

In July 2016 was the first case where Police officers in Dallas, United States, used a robot to kill an armed suspect during a Black Lives Matter protest. The device was not autonomous, but in the future it could be. And although there are many cases of remote warfare within militaries, such as the case with drones, this was the first occasion where such technology was used in public. There are real concerns around artificial intelligence causing chaos like the scenarios depicted in Hollywood movies such as Terminator, Robocop, Iron Man and iRobot in the future.

The three cutting-edge frameworks showcased in these talks from MesosCon North America demonstrate the amazing power and flexibility of Apache Mesos for solving large-scale problems. Perhaps you have noticed, in our Apache Mesos series, the importance of frameworks. Mesos frameworks are the essential glue that make everything work in a Mesos cluster, the layer between Mesos and your applications. They perform a multitude of tasks, including launching and scaling applications, monitoring and health checks, configuration management, and scheduling. In these talks, you'll learn how: Netflix uses Mesos to power their recommendation engines.

Late last year, I wrote about an interesting project from the US Defense Department to create a robotic jazz player. They developed a machine that is capable of performing a trumpet solo after picking up cues from fellow (human) musicians. "The goal of our research is to build a computer system and then hook it up to robots that can play instruments, and can play with human musicians in ways that we recognize as improvisational and adaptive," the researchers said. At the heart of this kind of project is a big data fueled pattern match, whereby machines learn what to do next by studying huge numbers of previous examples from human musicians. A similar project has been undertaken by researchers at Google.

She paints and writes poetry. She's also an artificial intelligence from the movie Her, which imagines how a juiced-up Siri will change our lives. Now, tech companies large and small are racing to make this a reality. You've heard the jargon: AI, machine learning, deep learning, neural networks, natural language processing. AI, simply put, is an attempt to make computers as smart, or even smarter than human beings.

This talk presents unsupervised analysis techniques that can be applied to collections of unstructured text documents for the purpose of discovering hidden topical trends, correlations or anomalies in their data. The techniques presented are applicable to a wide range of document types including news stories, technical blogs, customer feedback forms, congressional records, and legal documents, among many, many others. The talk will include introductory descriptions of the processing techniques needed to pre-process text data, discover salient multi-word phrases, and learn latent topic models describing the topical content of a collection of text data. The primary focus of the talk will be on analytic techniques that can be applied to the output of a latent topic model to extract trending topics over time, uncover topical correlations with other document features or meta-data, and discover anomalies in a text corpus. To illustrate these techniques, examples using news wire and congressional record data will demonstrate how important events in news wire data and anomalous congressional actions and interesting correlations can be discovered automatically using the presented unsupervised techniques.

Many models used by police are about the size of a backpack.

From Harry Potter and Romeo and Juliet to the stories of Oedipus and Icarus, almost every tale told conforms to one of just six plots, researchers have claimed. A major new analysis of over 1,700 stories identified the core plots'which form the building blocks of complex narratives'. Researchers used complex data-mining to locate words linked to positive or negative emotion in each story to reveal the set of arcs. A major new analysis of over 1,700 stories identified the core plots'which form the building blocks of complex narratives'. Shown, the plot of Harry Potter and the Deathly Hallows, which researchers found has the'rise, fall rise' plot.

Karissa Mitchell knows what it's like to stand out in a crowd, which is why she identifies with Elsa, the main character of Disney's animated film "Frozen," so well. Like Elsa, who faces criticism for having trouble controlling her unique powers, 9-year-old Karissa, of Stillwater, New York, was born missing her right hand and most of her wrist. But thanks to a group of Siena College students who 3-D printed a "Frozen"-themed prosthetic arm for Karissa, the little girl is feeling more confident in her skin. "Karissa really identifies with Elsa because she knows what it's like to be different from everyone else," Maria Mitchell, Karissa's mother, said in a Siena College news release. "She doesn't want to be seen as different, which has made her extremely determined to do things as well, if not better, than others."