Security was greater than ever at the French festival, with stepped up efforts to restrict access and even an anti-drone system. France remains under a state of emergency since the November 2015 Paris attacks. This is also the first festival held since the nearby Nice attack last year that killed 86 people.

IMEC's neuromorphic chip is not the first that is able to self-train by association (see BrainChip provides details of neural network architecture) however, it is novel in that it has used the variable resistance of memory devices to function in a manner similar to biological synapses. The use of memory in this way – IMEC is researching the use of ReRAM and MRAM – offers up to two orders more energy efficiency than use of logic, according to An Steegan, executive vice president of semiconductor technology and systems at IMEC. IMEC's goal is to develop manufacturing process technology and machine learning building blocks to make artificial intelligence sufficiently energy efficient that it can be integrated into sensors. IMEC's chip has learned to compose music and the rules for the composition are learnt on the fly.

Begun by the legendary and often demanding Stanley Kubrick and finished by the equally legendary Steven Spielberg, AI Artificial Intelligence is a futuristic retelling of the classic 1881 Florentine Italian tale Pinocchio by Carlo Collodi. Of course most modern children and adults are only familiar with the Disney animated rendition which can be considered a Readers Digest Condensed version of the original story. Kubrick is often demanding in that if he can't make it happen and appear the way he wants it, he will abandon an idea or even an entire project. For instance, since he could not use the available technology at the time, to recreate Stephen King's topiaries come to life in The Shining, he abandoned the idea to a daunting maze. Similarly, he felt he did not have the creative team necessary to replicate a robot boy so real that it is nearly human, not without using a human child actor, but because of ET and Jurassic Park, he did feel his friend Spielberg was up to the task. The ambitious result is one of the best science fiction films ever made, one which I believe stands shoulders to Kubrick's 2001 A Space Odyssey.

Artificial intelligence algorithms can now replace social media marketing agencies, paint a "new Rembrandt", project the image of a perfect mother, compose commercially viable music and even direct ads, trailers and short films. Just how worried should creatives be? According to Matt Webb, global chief technology officer at Mirum, an AI algorithm is theoretically capable of mining data from a brand and a brief and combining it with information gathered to solve problems. In that sense, AI could conceivably answer a creative brief, he concludes. The reasoning and processes used to teach AI to compose music turn out to be remarkably similar.

This is a project I've been working on for a few months, and I recently got a job offer to do similar work so all progress on the project is about to halt. Figured this would be the best time if ever to submit it here, so I'd love to hear any feedback/suggestions. In addition to being a project exploring conversation models in TensorFlow, it is also a good reference for anyone looking to get a simple app deployed on a website using their TensorFlow models. I experimented with both Heroku and Google AppEngine but stuck with GAE. For anyone looking to play with sequence to sequence models and/or write your own, this project would be a good reference (imo).

When the Netflix series House of Cards premiered in 2013, it quickly became the most downloaded content in the company's history – a statistic that came as no surprise to Netflix executives. They had previously examined a vast pool of Netflix data on subscribers' viewing habits and determined that the show was likely to become a hit even before they purchased it. The wisdom behind Netflix's sure-fire choice came from machine learning, which, loosely defined, is the ability of computers to learn on their own (without being programmed) by using algorithms that churn through large quantities of data. Machine learning's talents aren't limited to picking the next TV blockbuster, either. Consider some of the more down-to-earth uses that we already take for granted today.

In the last two years, the number of machine-learning (ML) startups has skyrocketed, and companies (in truth or in hype) increasingly predicate their value proposition on artificial intelligence (AI). Although ML and AI in healthcare and finance have garnered a tremendous amount of venture investment and press, other areas, such as marketing and business intelligence, have the potential to more quickly impact profitability, and are less fettered by regulation. As of last year, there wasn't serious consensus or research into current and future AI marketing trends, so we decided to poll and interview over 50 ML and AI marketing executives. The goal: to determine the industries and applications with the most promise. The full ML-in-marketing survey, conducted over three months, sheds light on various noteworthy trends and patterns; below, after defining some terms, I've highlighted three major findings.

Just a few months after GoPro threatens to close its entertainment doors, DJI is ready to step in. The drone-cum-camera company has just announced that it's launching a Smart TV app that'll stream plenty of aerial content and 4k videos captured from DJI drones and cameras. The app will initially be made available on Samsung's Tizen TVs and Apple TV. This is yet another instance in which DJI and GoPro have overlapping businesses. GoPro started with cameras and moved into drones, while DJI went from making drones and then moved into the camera business (The DJI Phantom Vision 2 was the first to ditch GoPro cameras for its own). GoPro has also been trying to make inroads as an entertainment company for a few years now -- indeed, there's a GoPro channel on Xbox, PS4, Roku, Samsung and LG TVs, as well as Virgin America's in-flight entertainment center.

At the Think About! conference staged in Warsaw by Ringier Axel Springer, the eastern Europe joint venture of Ringier and Axel Springer, I talked about the changes that AI, artificial intelligence, will bring to the profession of journalism in the future. You can already find AI in a huge amount of online products, for example in thematic pages that are almost completely automatically generated. The articles appear in a narrow thematic context, such as political or cultural content, but the possibilities here are almost endless. And with personalized content from online content providers, such as Axel Springer's news platform for Samsung smartphones, UPDAY, an algorithm learns from the user which issues and format he or she prefers, and constantly improves the personal selection of this content.

In spite of all the current hype, AI is not a new field of study, but it has its ground in the fifties. If we exclude the pure philosophical reasoning path that goes from the Ancient Greek to Hobbes, Leibniz, and Pascal, AI as we know it has been officially started in 1956 at Dartmouth College, where the most eminent experts gathered to brainstorm on intelligence simulation. It went then through two main'winter' periods, in which investments and interested drastically declined, and back in the nineties it looked like pursuing the creation of an artificial intelligence system was a public shame and a waste of energy. However, as in the movie "The Curious Case of Benjamin Button", the more time it passed the more AI became actual and relevant. Luckily enough, in 1993 this period ended with the MIT Cog project to build a humanoid robot, and with the Dynamic Analysis and Replanning Tool (DART) -- that paid back the US government of the entire funding since 1950 -- and when in 1997 DeepBlue defeated Kasparov at chess, it was clear that AI was back to the top.