Preacher's Seth Rogen and Evan Goldberg are teaming up with Silicon Valley's Sonny Lee to write and develop a sitcom about artificial intelligence in the not too distant future for FX. The show, Singularity, will focus on a world where artificial intelligence's capabilities greatly surpass those of the human race and how that affects every aspect of culture. While the premise of the series sounds entirely sci-fi, Lee told The Hollywood Reporter that like Silicon Valley there will be a level of satire that the show brings to the concept. Lee specifically reached out to Goldberg and Rogen because of how similar the tone of his show is to their apocalyptic comedy, This Is The End, which was released two years ago. The magazine reported that Lee, Goldberg and Rogen landed the deal with FX, but the show received multiple bids from a variety of networks.

Is it possible that the secret to building machine intelligence lies in spending endless hours reading Reddit? That's one question a team of researchers at OpenAI, a nonprofit backed by several Silicon Valley luminaries, hopes to answer with a new kind of supercomputer developed by chipmaker Nvidia. The researchers are also training robots do the dishes through experimentation, and they are building algorithms capable of learning to play a wide variety of different computer games. The new machine, called a DGX-1, is optimized for the form of machine learning known as deep learning, which involves feeding data to a large network of crudely simulated neurons and has resulted in great strides in artificial intelligence in recent years. The DGX-1 will let AI researchers train deep-learning systems more quickly using more data.

Netflix spent 1 million for a machine learning and data mining competition called Netflix Prize to improve movie recommendations by crowdsourced solutions, but couldn't use the winning solution for their production system in the end. This white paper takes a closer look at the real-life issues Netflix faced and highlights key considerations when developing production machine learning systems.

The musician: Since Mohr was discovered by Canadian producer Hawksley Workman, the singer/guitarist and her hard-rocking Toronto outfit the Mohrs have performed alongside Soundgarden, Jane's Addiction and Walk Off the Earth. Her style: Mohr gave the humble little hummable its most complete treatment, with hard-strummed acoustic guitar, smoky vocals and actual lyrics (!) combining to create a single that could actually slide quite comfortably into alt-rock radio. "I just tried to open it up with some bigger chords and make it a little more rockish," she explained. The verdict: "It was catchy in moments, but it was a little convoluted for my liking. . . . It's like asking a computer to write poetry just because it knows all the words in the world. It's lacking the things that make music so beautiful, which is vulnerability, emotion."

Machine learning is at the core of many recent advances in science and technology. With computers beating professionals in games like Go, many people have started asking if machines would also make for better drivers or even better doctors. In many applications of machine learning, users are asked to trust a model to help them make decisions. A doctor will certainly not operate on a patient simply because "the model said so." Even in lower-stakes situations, such as when choosing a movie to watch from Netflix, a certain measure of trust is required before we surrender hours of our time based on a model.

Two of today's major business and intellectual trends offer complementary insights about the challenge of making forecasts in a complex and rapidly changing world. Forty years of behavioral science research into the psychology of probabilistic reasoning have revealed the surprising extent to which people routinely base judgments and forecasts on systematically biased mental heuristics rather than careful assessments of evidence. These findings have fundamental implications for decision making, ranging from the quotidian (scouting baseball players and underwriting insurance contracts) to the strategic (estimating the time, expense, and likely success of a project or business initiative) to the existential (estimating security and terrorism risks). The bottom line: Unaided judgment is an unreliable guide to action. Consider psychologist Philip Tetlock's celebrated multiyear study concluding that even top journalists, historians, and political experts do little better than random chance at forecasting such political events as revolutions and regime changes.1 The second trend is the increasing ubiquity of data-driven decision making and artificial intelligence applications. Once again, an important lesson comes from behavioral science: A body of research dating back to the 1950s has established that even simple predictive models outperform human experts' ability to make predictions and forecasts. This implies that judiciously constructed predictive models can augment human intelligence by helping humans avoid common cognitive traps.

It ain't rocket packs, not quite yet, but it does feel like the future. The smartest brands in history: Google anticipating your search bar entries, Facebook putting together a personalized news feed, Amazon knowing every embarrassing detail of your interest in cookbooks and novelty toilet paper, and Netflix inventing a whole new genre based on your viewing preferences ("Nostalgic Hawaiian Sci-Fi Family Cop Documentaries"). All of these technologies are powered by artificial intelligence: systems based on invisible, complex systems that process more data than has ever been produced -- learning from it, responding, and predicting. As a New York Times story reports, interest in AI in the 1980s created a minor boom. Without any viable business uses, though, it led to an "AI winter."

Over recent years, we've seen artificial intelligence systems designed to write software, compose music, paint works of art, and even pen news articles, but the machines have been notably quiet in the medium of fiction storytelling. Designing an A.I. system that can write the screenplay for a movie, or compose a great novel, has posed a big challenge for researchers. So just how close are we to having machines pen our blockbuster films? In June, a bizarre short film entitled Sunspring premiered. Filled with incoherent non-sequiturs and inexplicably surreal tangents, the film could be considered either a compelling dream-like fugue or an amateurish mess.

Tomorrow, August 11th, Google's Brain Team will be answering questions submitted in this Reddit thread on the topic of machine learning. It is an AMA, ask me anything, session and it was introduced as "AMA: We are the Google Brain team. We'd love to answer your questions about machine learning." Now, this is not simply about RankBrain but all of Google's machine learning efforts across all their products and services. This includes, Google said, RankBrain for Google Search, SmartReply for GMail, Google Photos, Google Speech Recognition and more.

An employee video released in June described how Tronc would use artificial intelligence and machine learning to "allow journalists to do their jobs … Mojtaba Arvin is a computer programmer who's fascinated by artificial intelligence . Right now, he spends his time as an information technology student .