From computer vision to game playing, artificial intelligence (AI) has made a lot of progress in the past few years. Companies such as Google and Facebook have already placed huge bets on this technology, and over the next decade, AI features will steadily creep into one product after another. In this O'Reilly report, you'll examine the state of AI today and where we might be headed in coming years. To explain today's AI capabilities, authors Ben Lorica and Mike Loukides look at prominent examples such as Google's AlphaGo, self-driving cars, and face recognition--AIs that consist of narrow solutions to specific problems. Can researchers develop general intelligence flexible enough for an AI to learn without supervision, or choose what it wants to learn?

Natural Language Processing seems to have become somewhat of a commodity in recent years. More than a few companies have sprung up that offer basic NLP capabilities through a cloud API. If you'd like to know whether a text carries a positive or negative message, or what people or companies it mentions, you can just send it to one of these black boxes, and receive the answer in less than a second. Superficially, all these NLP APIs look more or less the same. Textrazor, AlchemyAPI, Aylien, MeaningCloud and Lexalytics all offer similar services (named entity recognition, sentiment analysis, keyword extraction, topic identification, etc.), and do so through similar interfaces.

In a TEDx talk entitled "How Computers are Learning to Be Creative", Blaise Agüera y Arcas, Google principal scientist, demonstrated how neural networks recognizing images can run them in reverse-- thus generating them. Of this, he noted that perception and creativity are highly linked together. With Google's neural network models, machine perception and machine creativity are no longer that far-fetched. Arcas identified perception as the process by which simple objects are transformed by the mind into overwhelmingly different concepts. With today's technology, even computers are capable of perception. Creativity, on the other hand, is actually-- as far as Arcas is concerned in his speech-- the "flip side" of the former.

The full article about the 12 Algorithms Every Data Scientist Should Know was posted by Mark van Rijmenam. Mark is an entrepreneur and a Big Data strategist. Algorithms have become part of our daily lives and they can be found in almost any aspect of business. Gartner calls this the algorithmic business and it is changing the way we (should) run and manage our organizations. There are all kinds of algorithms and for each aspect of your business, there are different algorithms, which nowadays you can even buy at an algorithm marketplace.

Glen Hiemstra has spent two decades studying the future. He tries to understand and articulate the kind of future we want as individuals, organizations, and societies. In other words, he helps companies better anticipate tomorrow's threats, opportunities, and competition as a seasoned futurist. One important area where the future will be written: the corporate office or collaborative workspaces where many of us get most of our work done. How will those change over the next decade?

Lisp (historically, LISP) is a family of computer programming languages with a long history and a distinctive, fully parenthesized prefix notation.[1] Originally specified in 1958, Lisp is the second-oldest high-level programming language in widespread use today. Only Fortran is older, by one year.[2][3] Lisp has changed since its early days, and many dialects have existed over its history. Today, the best known general-purpose Lisp dialects are Common Lisp and Scheme.

Pathologists have been largely diagnosing disease the same way for the past 100 years, by manually reviewing images under a microscope. But new work suggests that computers can help doctors improve accuracy and significantly change the way cancer and other diseases are diagnosed. A research team from Harvard Medical School and Beth Israel Deaconess Medical Center and recently developed artificial intelligence (AI) methods aimed at training computers to interpret pathology images, with the long-term goal of building AI-powered systems to make pathologic diagnoses more accurate. "Our AI method is based on deep learning, a machine-learning algorithm used for a range of applications including speech recognition and image recognition," explained pathologist Andrew Beck, HMS associate professor of pathology and director of bioinformatics at the Cancer Research Institute at Beth Israel Deaconess. "This approach teaches machines to interpret the complex patterns and structure observed in real-life data by building multi-layer artificial neural networks, in a process which is thought to show similarities with the learning process that occurs in layers of neurons in the brain's neocortex, the region where thinking occurs."

Each year at Cannes Lions, the Saatchi & Saatchi New Directors' Showcase features a live show conceived around a theme that mirrors the most exciting happenings in the ad industry. This year it was less a live show, more an experiment. In a nod to the rising prominence of artificial intelligence, Saatchi & Saatchi and its LA agency Team One set about potential capabilities of the technology. The result is a music video that was creatively conceived, cast, directed, shot and edited wholly by machines. Saatchi & Saatchi hid it within the NDS reel and tasked the audience to try and pick it out among a crop of films by some of the world's most talented new directors.

An artificial intelligence (AI) lawyer chatbot – yes, that's genuinely a thing – has successfully helped to void 160,000 parking tickets across London and New York in just under two years – all for free. According to The Guardian, it was created by a 19-year-old Stanford University student and self-taught coder who claims that it is "the world's first robot lawyer." Joshua Browder, who was born in London, says that his DoNotPay chatbot assists its users in an easy, friendly way, and it certainly appears to be working. It's already taken on a quarter of a million parking ticket legal cases, and it's won 64 percent of them. That totals 4 million in fines that are no longer having to be paid.

The Air Force recently tested an artificial intelligence flight combat system named ALPHA against it's own tactical experts. John Iadarola, host of ThinkTank gives his final judgment on the use of artificial intelligence in combat. Tell us what you think in the comments below. Retired USAF Colonel Gene Lee -- an experienced combat instructor with "considerable fighter aircraft expertise" -- was repeatedly shot down during engagements with ALPHA in a high-fidelity air combat simulation. Lee called his computerized opponent "the most aggressive, responsive, dynamic and credible AI I've seen to date."