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 .

Do machine-learning algorithms processing search engine queries bring on prejudice, discrimination and stereotyping in query results? The paper submitted to the International Conference on Social Informatics scheduled for publication analyzes how Google and Bing represent female beauty in their image search results, particularly when it comes to different age and racial groups. For nearly every country analyzed, white women appear more in the "beautiful" results, and black and Asian women appear in the "ugly" ones, per The Washington Post, which initially pointed to the study. Searches for "ugly" women return images of those about 60% white and 20% black between the ages of 30 to 50.

The way in which people engage with brands has changed. Gone are the days when it was a one-way interaction; younger demographics especially love a value-add exchange with brands they can identify with. Chatbots have been heralded as one way of opening up the channels, but as with every new marketing tech innovation, you need to get it right. Brands need access to tech that can do the job well and not make the experience clunky and robotic. One company that recognises this issue is Israel/US based imperson.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

The first UK Robotics Week took place from 27 June to 1 July, with events and activities around the country showcasing leading UK technology and engineering research in robotics and autonomous design. Co-ordinated by the Engineering and Physical Sciences Research Council's UK Robotics and Autonomous Systems (UK-RAS) Network, and supported by the Royal Academy of Engineering, the Institution of Engineering and Technology and the Institution of Mechanical Engineers, the week sees robotic research groups from around the world visiting the UK to demonstrate their latest technologies in surgical robotics, field robotics, autonomous driving and unmanned aerial vehicles, while other challenges are set to engage and inspire school, college and university students. On 29 June, the Academy hosted a panel discussion on robotic ethics. The event also featured a Pepper and a NAO robot, from London Design and Engineering UTC, which will be some of the first in the UK to be used in an educational setting. The panel discussion can be found on Twitter at @RAEngNews.

Apple and Intel acquired machine learning startups. Palantir purchased a data visualization startup. And AWS rolled out an analytics service for streaming real time data. We've got all this and more in our Big Data Roundup for the week ending August 14, 2016. The company acquired Turi, an artificial intelligence (AI) and machine learning startup, in a deal reportedly worth 200 million.