POLITICO Establishes Global AI Forum for Business Leaders and Policymakers with Accenture as Founding Partner First in series of AI summits will take place on March 19-20, 2018 in Brussels, Belgium BRUSSELS; March 8, 2018 – POLITICO, with Accenture Applied Intelligence as the founding partner, is launching a global artificial intelligence (AI) forum to help business leaders and government policymakers understand the impact of AI innovation and to inform responsible use of AI. As AI-based decisions have an increasing impact on human lives, the initiative aims to empower decision-makers to build a framework for governance in pivotal and unchartered territory. The initiative will hold a series of AI summits and roundtables in multiple cities in Europe and the US. The first AI Summit will take place on March 19-20, 2018 in Brussels, Belgium. Carlos Moedas, European Union Commissioner for Research Science and Innovation, and John Delaney, US Congressman and founder of the bipartisan AI Caucus, are two keynote participants of the event.

"This use of AI with HSBC's card program is one of the first in the loyalty sector and demonstrates that artificial intelligence and machine learning are the future of business," said Jesse Wolfersberger, senior director, decision sciences, Maritz Motivation Solutions. "We're going to witness more companies using AI to engage people in new and innovative ways. We are proud to have a proprietary AI system that makes loyalty programs smarter and more efficient and can result in significant operational cost savings for businesses." Maritz's AI algorithm, also known as machine learning, predicts the rewards a loyalty program member is likely to redeem over the next year. The AI then suggests a redemption category to promote to each member and calculates the percentage of clients likely to redeem in different categories.

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. After William Gibson coined the term cyberspace in his 1984 novel Neuromancer, it almost immediately entered our everyday vocabulary. A play on information theorist Norbert Wiener's idea of cybernetics, cyberspace became shorthand for the world inside our networked computers, that digital landscape where we met to chat, play games, and exchange intimate secrets. Today, cyber is part of our political language, too, used to describe everything from digital warfare to online intelligence gathering. What often gets forgotten about the origin story of this term is that Gibson wasn't just talking the future of computers, but of a world where tech corporations rule every aspect of our lives.

For the last four weeks, I've been living in an Orwellian nightmare. One in which I have to watch every word I say because "they" are always listening. And by "they", I mean Alexa, Siri and Google. It seemed like a good idea - get seven smart speakers and test them in a real house to see how they affected our listening habits and daily routine. At times, they've been pretty helpful. If we're running low on biscuits, one of us can bark, "Hey Siri, add Hob Nobs to the shopping list" and a reminder appears on our phones.

Hi, I was asked to make some funny machine learning project that could detect how similar are you to a celebrity? Is there a easy pre-trained model that could do it? I'm ML practitioner and mostly worked with Keras and tensorflow so some simple model would be nice. The model doesn't have to be very accurate, this is just for a funny event, that we're having.

The Variational Autoencoder (VAE) has proven to be an effective model for producing semantically meaningful latent representations for natural data. However, it has thus far seen limited application to sequential data, and, as we demonstrate, existing recurrent VAE models have difficulty modeling sequences with long-term structure. To address this issue, we propose the use of a hierarchical decoder, which first outputs embeddings for subsequences of the input and then uses these embeddings to generate each subsequence independently. This structure encourages the model to utilize its latent code, thereby avoiding the "posterior collapse" problem which remains an issue for recurrent VAEs. We apply this architecture to modeling sequences of musical notes and find that it exhibits dramatically better sampling, interpolation, and reconstruction performance than a "flat" baseline model. An implementation of our "MusicVAE" is available online.

We here summarize our experience running a challenge with open data for musical genre recognition. Those notes motivate the task and the challenge design, show some statistics about the submissions, and present the results.

New concerns over how artificial intelligence videos could spread fake news and even prompt a war. Forget fake news for a moment. Artificial intelligence is now able to generate a convincing video of a celebrity or public figure. For illicit purposes, these videos are called deepfakes and show a celebrity superimposed into an adult movie. A programmer finds existing video and audio for a known figure, then the AI takes over and creates a brand new version.

Wu has used the drones in two ways for his dramatic, surreal photos. In the first technique, he attached LED lamps to 3D Robotics drones and set them off on GPS-controlled flights. He took the photos with a medium format Phase One camera while the drone was stationary, experimenting with the height, angle and distance from the subject. Once back home, he layered the photos together until the image matched his vision. For later photos, he created time-lapse exposures while the drones ran in set circles around the rock pinnacles, tracing out "halos" in the sky.

It's March, which means winter is ending, the clocks decide to lose an hour and the luck of the Irish is celebrated. Seen as a beacon of new technology and emerging trends, this year's event is no different. Let's dive into the world of blockchain-controlled sentient robots that will diversify technology with a list of the emerging technical trends of 2018. With computers getting faster and GPU's being re-purposed, we're seeing an explosion of innovation, from machine-learning models to validate brand creative to those that create unique art and music. Companies like IBM and Getty Images are asking how they can apply large scale AI to the creative process, and what that means for their business.