The original GAN paper by Goodfellow et al did not work for discrete data because of the inability to the backproagate gradient to the generator. Have there been any recent developments in this directions since, allowing the adversarial idea to be implemented for discrete data? And still take advantage of the automatic differentiation (backpropagation) facilities of libraries like PyTorch / Tensorflow?

"We are already at the point where you can't tell the difference between deepfakes and the real thing," Professor Hao Li of the University of Southern California tells the BBC. We are at the computer scientist's deepfake installation at the World Economic Forum in Davos which gives a hint of what he means. Like other deepfake tools, his software creates computer-manipulated videos of people - often politicians or celebrities - that are designed to look real. Most often this involves "face swapping", whereby the face of a celebrity is overlaid onto the likeness of someone else. As I sit, a camera films my face and projects it onto a screen in front of me; my features are then digitally mapped.

If Sunspring is anything to go by, artificial intelligence in film-making has some way to go. This short film, made as an entry to Sci-Fi London's 48-hour film-making competition in 2016, was written entirely by an AI. The director, Oscar Sharp, fed a few hundred sci-fi screenplays into a long short-term memory recurrent neural network (the type of software behind predictive text in a smartphone), then told it to write its own. The result was almost, but not quite, incoherent nonsense, riddled with cryptic nonsequiturs, bizarre turns of phrase and unfathomable stage directions such as "he is standing in the stars and sitting on the floor". All of which Sharp and his actors filmed with sincere commitment.

This is my brand-new film on the future of work, jobs and education. Are you excited, or are you worried? The next 20 years will bring more change than the previous 300 years. Technology is rebooting the very idea of work, how we work, when we work, where we work, and sooner or later why we work. Computers are no longer stupid.

Acumen Research and Consulting, Recently Published Report titled "Artificial Intelligence (AI) Market Size, Opportunities and Forecast, 2019 to 2026". The worldwide artificial intelligence market and is anticipated to grow at a CAGR of around 49% in terms of revenue during the forecasting period 2019 to 2026. The AI technology's ability to effectively interpret the data collected and predict decisions by critical algorithms helps to improve productivity; for example, Netflix recommends movies based on previous viewing habits by consumers. AI has revolutionized the business management approach in the current business environment through the application of process management tools, company purchasing ads, pattern forecasts and other resources. These are the main factors of growing innovation in AI technology and in the demand for machine learning.

GitHub is a clearinghouse for all sorts of open source projects, including those for machine learning, automated and otherwise. More specifically, automated machine learning is the use of automated techniques, be they learned methods or simple heuristics, used for algorithm selection, hyperparameter tuning, architecture design, or any other conceivable portion of a machine learning implementation. Switching gears, Indiana Jones is one of the greatest characters to ever grace the silver screen. Raiders of the Lost Ark, the first movie in which the character was featured, is a personal favorite, film adored by millions. The rest of the (current) quadrilogy movies run alternately hot and cold, but even the poorest quality Indiana Jones is better than 95% of available cinema.

One of my 2019 new year resolutions was to read more books. I signed up for GoodReads and stated a reading challenge with a modest goal of finishing twelve books. I finished twenty-four, and many of these books are great reads for entrepreneurs, CIOs, and other digital transformation leaders. What makes a good book? My favorites have a strong focus, come from a unique perspective, are easy to read/listen, deliver a clear message, back their hypotheses with data or testimonials, tell personal stories, and are concise.

By Raju Vegesna The past decade has been a true testament to the success of many inventive technologies. The biggest wave we witnessed was the advent of artificial intelligence and machine learning. NLP & Conversational AI In the early 2010s, consumer natural language processing (NLP) allowed us to talk to our phones and control smart-home appliances reliably. Many people expected NLP to explode in other domains, but it never really materialized, because of either poor implementations or a focus on other types of development. Over the next decade, NLP will be put to use in complex software to lower the barrier to entry.

How to assess the potential of liking a city or a neighborhood before ever having been there. The concept of urban quality has until now pertained to global city ranking, where cities are evaluated under a grid of given parameters, or either to empirical and sociological approaches, often constrained by the amount of available information. Using state of the art machine learning techniques and thousands of geotagged satellite and perspective images from diverse urban cultures, this research characterizes personal preference in urban spaces and predicts a spectrum of unknown likeable places for a specific observer. Unlike most urban perception studies, our intention is not by any means to provide an objective measure of urban quality, but rather to portray personal views of the city or Cities of Indexes.

In June, 1972, Ángel Parra, Chile's leading folksinger, wrote a song titled "Litany for a Computer and a Baby About to Be Born." Computers are like children, he sang, and Chilean bureaucrats must not abandon them. The song was prompted by a visit to Santiago from a British consultant who, with his ample beard and burly physique, reminded Parra of Santa Claus--a Santa bearing a "hidden gift, cybernetics." The consultant, Stafford Beer, had been brought in by Chile's top planners to help guide the country down what Salvador Allende, its democratically elected Marxist leader, was calling "the Chilean road to socialism." Beer was a leading theorist of cybernetics--a discipline born of midcentury efforts to understand the role of communication in controlling social, biological, and technical systems.