Just as ATMs changed banking and computers took over the home and workplace, robots and artificial intelligence are going to transform a bunch of industries over the next decade. By 2025, a machine may be putting together your driverless car in a factory with no human oversight. A robot maid could be cleaning up after you at home, and your financial advisor might be a computer investing for you automatically. And with at least 90 countries operating unmanned aerial vehicles, the wars of the future may increasingly be fought with "drone" aircraft. These are just some of the interesting -- and sometimes scary -- predictions to come from a 300-page report released by Merrill Lynch in November, which estimates the global market for robots and AI will grow from 28 billion to more than 150 billion just five years from now.

Artificial intelligence is a common topic explored within the science-fiction genre. Sunspring, a new sci-fi short, instead of using the theme of artificial intelligence in its narrative, used AI to actually produce the narrative in the first place. The film, which had its online debut on Ars, had its screenplay written by an AI which goes by the name of'Benjamin'. The film was submitted as part of the 48-Hour Film Challenge at the Sci-Fi London film festival by Oscar Sharp, a BAFTA-nominated filmmaker and Ross Goodwin, a creative technologist and former Obama administration ghostwriter. Sunspring comes to life through the acting and production. The screenplay is sufficiently vague and nonsensical to leave a lot of room for interpretation.

SugarCRM held its annual user conference, SugarCon, earlier this week in San Francisco. Over 1,200 people were on hand to see what direction the company was taking its platform in. And while many of its competitors are expanding their offerings to include ecommerce, configure-price-quoting (CPQ), marketing automation and other related areas, SugarCRM CEO Larry Augustin emphatically stated that Sugar is staying true to its CRM roots and explore the many ways CRM can be even more important to business success in the near future. I had a chance to speak with Augustin and hear how the company is looking to bring the latest and greatest technology developments to the platform to make CRM a system more relevant, and attractive, for sales professionals to turn to in order to build successful relationships with modern consumers. Below is an edited transcript of that conversation, as well as the video of our full conversation.

At lunch last week, I learned that a couple colleagues were engaged in a little duel--trying to out-walk each other, as tracked by their new Fitbits. Self-improvement was definitely the goal, but seeing peer performance and benchmarks provided the required motivation to achieve that goal. If you're a data science or analytics leader, your job is to manage analysts who produce insights. So, if you want to drive your business through these insights, you have two options. You can either hire more analysts or you can increase the productivity of your existing analysts.

Various land-use configurations are known to have wide-ranging effects on the dynamics of and within other city components including the transportation system. In this work, we particularly focus on the complex relationship between land-use and transport offering an innovative approach to the problem by using land-use features at two differing levels of granularity (the more general land-use sector types and the more granular amenity structures) to evaluate their impact on public transit ridership in both time and space. To quantify the interdependencies, we explored three machine learning models and demonstrate that the decision tree model performs best in terms of overall performance--good predictive accuracy, generality, computational efficiency, and "interpretability". Results also reveal that amenity-related features are better predictors than the more general ones, which suggests that high-resolution geo-information can provide more insights into the dependence of transit ridership on land-use. We then demonstrate how the developed framework can be applied to urban planning for transit-oriented development by exploring practicable scenarios based on Singapore's urban plan toward 2030, which includes the development of "regional centers" (RCs) across the city-state.

Respondents were asked what they saw as the biggest area of opportunity for Big Data in comparison to traditional systems, with 62% agreeing that they consider real time analysis as the biggest area of opportunity today. "It's not long ago we were visiting enterprises and having to explain why they should look at big data. Today in 2016, Big Data Analytics is already considered a necessity to remain competitive by 63% of organizations," explains Serge Haziyev, VP Technology Services, SoftServe. "It's very encouraging that machine learning has featured so prominently in this survey. I find that businesses that take the plunge and implement machine learning techniques realize the benefits early on – it's a big step forward because it delivers prescriptive insights enabling businesses to not only understand what customers are doing, but why."

The new team has a distinct goal: to invent the future of Search, a voice-activated, human-like entity that can answer any query intelligently. "We are building the ultimate assistant. In two years, you can expect Google to become a personal life assistant across multiple surfaces, including your phone, Google Home, even cars," Mogenet said. Some of Google's best-known products are already shaped by machine learning, the ability of computers to spot patterns in large datasets and learn by example. For instance, Google Photos uses it to understand the content of an image.

We have been hearing predictions for decades of a takeover of the world by artificial intelligence. In 1957, Herbert A. Simon predicted that within 10 years a digital computer would be the world's chess champion. That didn't happen until 1996. And despite Marvin Minsky's 1970 prediction that "in from three to eight years we will have a machine with the general intelligence of an average human being," we still consider that a feat of science fiction. The pioneers of artificial intelligence were surely off on the timing, but they weren't wrong; AI is coming.

In his quest to transform the way the Pentagon wages war, Defense Secretary Ashton B. Carter has turned to Silicon Valley, hoping its experimental culture, innovation and sense of urgency would rub off on the rigid bureaucracy he runs. Carter has made several trips to the Valley and appointed Eric Schmidt, the chairman of Google's parent company to an advisory board. And recently he sat down at the Pentagon with Elon Musk to see what suggestions the billionaire founder of Tesla and SpaceX might have to make the nation's military more efficient and daring. "Having an incentive structure that rewards innovation is extremely important," he said in an interview after the meeting. Whatever you reward will happen." The Pentagon finds itself in a new arms race, struggling to keep pace with forms of combat that are fought with bytes as well as bullets. The technological advancements disrupting established business sectors are now shaking up the world of war -- where robots, swarming drones ...

When most people think of artificial intelligence (AI) they think of HAL 9000 from "2001: A Space Odyssey," Data from "Star Trek," or more recently, the android Ava from "Ex Machina." But to a computer scientist that isn't what AI necessarily is, and the question "what is AI?" can be a complicated one. One of the standard textbooks in the field, by University of California computer scientists Stuart Russell and Google's director of research, Peter Norvig, puts artificial intelligence in to four broad categories: The differences between them can be subtle, notes Ernest Davis, a professor of computer science at New York University. AlphaGo, the computer program that beat a world champion at Go, acts rationally when it plays the game (it plays to win). But it doesn't necessarily think the way a human being does, though it engages in some of the same pattern-recognition tasks.