State of the art music recommender systems mainly rely on either Matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction by learning from temporal sequences of user actions. Despite advances in deep learning for song recommendation, none has taken advantage of the sequential nature of songs by learning sequence models that are based on content. Aside from the importance of prediction accuracy, other significant aspects are important, such as explainability and solving the cold start problem. In this work, we propose a hybrid deep learning structure, called "SeER", that uses collaborative filtering (CF) and deep learning sequence models on the MIDI content of songs for recommendation in order to provide more accurate personalized recommendations; solve the item cold start problem; and generate a relevant explanation for a song recommendation. Our evaluation experiments show promising results compared to state of the art baseline and hybrid song recommender systems in terms of ranking evaluation.

A remarkable feature of human beings is their capacity for creative behaviour, referring to their ability to react to problems in ways that are novel, surprising, and useful. Transformational creativity is a form of creativity where the creative behaviour is induced by a transformation of the actor's conceptual space, that is, the representational system with which the actor interprets its environment. In this report, we focus on ways of adapting systems of learned representations as they switch from performing one task to performing another. We describe an experimental comparison of multiple strategies for adaptation of learned features, and evaluate how effectively each of these strategies realizes the adaptation, in terms of the amount of training, and in terms of their ability to cope with restricted availability of training data. We show, among other things, that across handwritten digits, natural images, and classical music, adaptive strategies are systematically more effective than a baseline method that starts learning from scratch.

A new app from the former head of video-sharing app Vine hopes to repeat the success of the cult social network by making it easier to shoot and edit short clips. Trash hopes that its secret weapon will be "computational cinematography": the app, which entered closed beta on Monday, uses machine learning "to automate the un-fun parts of video editing", automatically processing video to cut together short clips with a consistent mood and feel. A similar approach, computational photography, has already radically changed smartphone photography, enabling features such as the Pixel's Night Sight and iPhone's Portrait Mode. Trash's co-founder, Hannah Donovan, who was Vine's last general manager before the service was shut down by its owner, Twitter, said she hoped the approach would lower the barrier of entry to video editing. "We're analysing the video for a bunch of different things," Donovan said.

They say "behind every good man, there is a woman," but in the world of blockbuster movies, the best allies to have by your side are often of the robotic persuasion. Always ready to dig you out of a rough spot, or march gung-ho into a battle, the movie robot sidekick has become a staple in modern sci-fi and action/adventure. Sure, there have been some bad-ass solo robots over the years like Optimus Prime, Ava of Ex-Machina fame, and even Robocop (although, technically he's a cyborg), but we're here celebrating the sidekick. The robots that make the best partners in crime. Whether it's intergalactic co-pilots, shape-shifting planetary protectors, or time-travelling androids, join us as we count down the 10 best movie robot sidekicks.

Artificial intelligence is a unique part of the emerging tech landscape, with years of science fiction shaping our expectations of AI capabilities. Today, the reality is that AI is much more of an enabling technology than an end user product. Understanding how to use AI requires understanding the data requirements, the programming model, and the nature of the outputs. These elements, which are described further in Emerging Business Opportunities in AI, CompTIA's latest research exploring the adoption of emerging technology, add more complexity to an already complicated IT environment. For solution providers wondering how to best serve their clients, deciding on the right business model and level of investment can be a challenge.

Plate from Muybridge's Animal Locomotion series published in 1887. Deep learning has become the dominate lens through which machines understand video. Yet video files consume huge amounts of storage space and are extremely computationally demanding to analyze using deep learning. Certain use cases can benefit from converting videos to sequences of still images for analysis, enabling full data parallelism and vast reductions in data storage and computation. Representing video as still imagery also presents unique opportunities for non-consumptive analysis similar to the use of ngrams for text.

Since their introduction more than a decade ago, smartphones have been equipped with cameras, allowing users to capture images and video without carrying a separate device. Thanks to the use of computational photographic technologies, which utilize algorithms to adjust photographic parameters in order to optimize them for specific situations, users with little or no photographic training can often achieve excellent results. The boundaries of what constitutes computational photography are not clearly defined, though there is some agreement that the term refers to the use of hardware such as lenses and image sensors to capture image data, and then applying software algorithms to automatically adjust the image parameters to yield an image. Examples of computational photography technology can be found in most recent smartphones and some standalone cameras, including high dynamic range imaging (HDR), auto-focus (AF), image stabilization, shot bracketing, and the ability to deploy various filters, among many other features. These features allow amateur photographers to produce pictures that can, at times, rival photographs taken by professionals using significantly more expensive equipment.

Our USP in the PR market is to research to find the next influential technology and business leader who can support POC data to the media. In today's digital thunderstorm of news, publications, are more than ever, reliant on the principles of journalism. That is why we are excited to announce we have been nominated for Best Integrated Agency in the 2019 Prolific London Awards. Our mission to create dynamic client campaigns through digital innovation, keeps us at the forefront of leading business and technology media conversations and we are proud to share this nomination with our dedicated international team. Our work with UK based WAN Data Acceleration company Bridgeworks Ltd., has produced a thriving external communications strategy to attract multi-million dollar business contracts in global markets like the US, Europe and South Africa.

In the lead-up to the 2016 election, very few predicted the degree to which online misinformation would disrupt the democratic process. Now, as we edge closer to 2020, there is a heightened sense of vigilance around new threats to truth in our already fragile information ecosystem. At the top of the list of concerns is no longer Russian bots, but deepfakes, the artifical intelligence-manipulated media that can make people appear to do or say things that they never did or said. The threat is being taken so seriously that last Thursday, the House intelligence committee held Congress's first hearing on the subject. In his opening remarks, Representative Adam Schiff, the committee chairman, talked of society being "on the cusp of a technological revolution" that will qualitatively transform how fake news is made.

There are many never-ending debates between Republicans and Democrats. Impeach vs. don't impeach; capital punishment vs. life in prison; wall vs. no wall; legalizing marijuana vs. not; self-driving cars vs. human drivers; Red Sox vs. Yankees; takeout vs. home-cooked; or Gone With the Wind vs. any other movie. All of these issues are stunningly important, right up to the second where cataclysm falls and creates a nightmare scenario that so many fear. That cataclysm is a complete loss of electricity and every mode of convenience and survival we take for granted. IS NORTH KOREA'S EMP THREAT REAL OR'SOMETHING OUT OF A JAMES BOND MOVIE'?