Please make Pull Requests for good resources, or create Issues for any feedback! Seq2Seq solves the traditional fixed-size input problem thatEffective Approaches to Attention-based Neural Machine Translation prevents traditional DNNs from mastering sequence based tasks such as translation and question answering. It has been shown to have state of the art performances in English-French and English-German translations and in responding to short questions. Seq2Seq was first introduced in late 2014 by 2 papers (Sequence to Sequence Learning with Neural Networks and Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation) from Google Brain and Yoshua Bengio's group. The two papers took a similar approach in machine translation, in which Seq2Seq was developed upon.

In late 2015, our Chief Customer Officer, Joe Gagnon, and I, met with the IT Director, and the COO of Radisson Blu Edwardian in London. A long-term customer of Aspect's, we were there to share what we have been so diligently working on over the past year: our vision for re-imagining customer service that would combine the best of all forms of consumer interaction types, and the best of what we and the industry have been able to develop in next generation CX technology. In essence, the vision for re-imagining customer service has at its core how to use Interactive Text Response (ITR), or what is also known as "bots" to provide the ability to let customers self-serve on text channels at blazing-fast speeds with a User Interface that resembles that of a natural conversation with a person. Needless to say, it didn't require much convincing that this approach would provide an opportunity to "surprise and delight" in their prestigious hotel chain. With over 2 billion people using texting and messaging solutions extensively today, offering service over these channels just makes sense. Furthermore, it has the promise of saving cost through smart automation while providing a state-of-the-art customer experience, or in the words of the COO: "I want this by Monday."

Well; US DoE and EPA has already been using AI for a very, very long time in monitoring and proactively acting on any waste release. I was one of the lead architects and developers of the solution. As computers get smarter, scientists look at new ways to enlist them in environmental protection.

Although the game between AlphaGo AI and legendary chess master Lee Sedol ended over a month ago, the event's influence is opening doors for companies seeking to explain the significance of AI technology. Fu Sheng, CEO Cheetah Mobile who predicted Lee would win the game, is one of them. At the company's global media conference held Tuesday, Fu announced that Cheetah Mobile, the Beijing-based startup best known for its utility apps, is going to open a robotics division with a 50 million USD investment designated for artificial intelligence development. Fu says he is going to lead the team himself. "AI technology is maturing and there's no doubt that human labor is going to be replaced by robots", he said, adding that deep learning and AI will offer a chance to bypass competitors and disrupt the industry landscape.

Every year Sergey Brin and Larry Page write a letter to their stakeholders, giving an overview of the company and where it is headed. This year, post the re-organisation that made Sundar Pichai CEO of Google and Alphabet became the parent company, the founder's letter was written by Pichai. The letter has some clues to where Google services are headed. Search is going to get more contextual awareness, personal demographic factors, location characteristics and environmental variables will all start changing search results. Search will not just get more personal, but also consider the time and activity.

In the last part we introduced Classification, which is a supervised form of machine learning, and explained the K Nearest Neighbors algorithm intuition. In this tutorial, we're actually going to apply a simple example of the algorithm using Scikit-Learn, and then in the subsquent tutorials we'll build our own algorithm to learn more about how it works under the hood. To exemplify classification, we're going to use a Breast Cancer Dataset, which is a dataset donated to the University of California, Irvine (UCI) collection from the University of Wisconsin-Madison. UCI has a large Machine Learning Repository.

The question of human existence -whether as a species in general or just in the working world- has generated quite some concern around the world. Famous technologists and successful entrepreneurs such as Stephen Hawking, Elon Musk or Jaan Tallinn have responded with organisations like Future of Life Institute and OpenAI. They strive to protect human life from intelligent machines taking over the world. Thanks to Paul O'Connell, founder and organiser of the Uprise Festival in Amsterdam, I had the opportunity to dive a bit deeper into this issue. As part of the Festival -already in its 3rd edition and coming to Dublin later this year- I was able to bring to the audience a panel of guest speakers with the goal of answering one bold question: are humans still relevant?

What will we do with all the data we accumulate from photos? On a daily basis, Internet juggernauts like Google, Yahoo, Facebook or Microsoft use highly sophisticated deep learning engines to better understand the content of billions of images uploaded, liked and shared. For now, it is to better serve advertising, but what else can be done? For one, we could generate custom-made photos. Automated photo generating A.I. using all the knowledge acquired about photography -- including which image types helps sell more products, which dominant colors appeal to viewers, and which composition is the most effective -- would build a perfect photo according to your needs.

Artificial intelligence researcher and Managing Director of Microsoft's Redmond, Washington, research lab Eric Horvitz has just won the ACM-AAAI Allen Newell Award, Microsoft shared on a blog post today. The award acknowledges his groundbreaking contributions in artificial intelligence and human-computer interaction as well as "his persistent focus on using those discoveries as the basis for practical applications that make our lives easier and more productive." Horvitz first got interested in practical applications of artificial intelligence when he was pursuing his Ph.D. on principles of bounded rationality, as he wanted to "understand how computing systems immersed in the real world could make the best decisions in time-critical situations." Since then, Horvitz has combined multiple computer science disciplines through his work and he has been leading the research in exploring the interrelationships between artificial intelligence and fields like decision science, cognitive science, and neuroscience. Horvitz even collaborated with NASA's Mission Control Center to help them providing flight engineers with the most valuable information about space shuttle systems under intense time pressure.

Jamie Metzl is a Senior Fellow for Technology and National Security at the Atlantic Council. After 4 billion years of evolution by one set of rules, our species is about to begin evolving by another. Overlapping and mutually reinforcing revolutions in genetics, information technology, artificial intelligence, big data analytics, and other fields are providing the tools that will make it possible to genetically alter our future offspring should we choose to do so. Nearly everybody wants to have cancers cured and terrible diseases eliminated. Most of us want to live longer, healthier and more robust lives. Genetic technologies will make that possible. But the very tools we will use to achieve these goals will also open the door to the selection for and ultimately manipulation of non-disease-related genetic traits -- and with them a new set of evolutionary possibilities.