It's one thing to keep robots from crashing into fixed obstacles like walls or furniture, but preventing collisions with other moving things is a much tougher challenge. Targeting teams of robots working together, MIT on Thursday announced a new algorithm that helps robots avoid moving objects. Planning algorithms for robot teams can be centralized, in which a single computer makes decisions for the whole team, or decentralized, in which each robot makes its own decisions. The latter approach is much better in terms of incorporating local observations, but it's also much trickier, since each robot must essentially guess what the others are going to do. MIT's new algorithm takes a decentralized approach and factors in not just stationary obstacles but also moving ones.

Will Knight reports in the MIT Technology Review, "A few years ago, a breakthrough in machine learning suddenly enabled computers to recognize objects shown in photographs with unprecedented--almost spooky--accuracy. The question now is whether machines can make another leap, by learning to make sense of what's actually going on in such images. A new image database, called Visual Genome, could push computers toward this goal, and help gauge the progress of computers attempting to better understand the real world. Teaching computers to parse visual scenes is fundamentally important for artificial intelligence. It might not only spawn more useful vision algorithms, but also help train computers how to communicate more effectively, because language is so intimately tied to representation of the physical world."

Predicting cyber attacks before they happen have two conventional approaches. One uses a set of indicators specified by an expert, and the other uses machines to detect abnormal activity. The problem with these approaches is that rules are often broken by criminals, and there is just too much abnormal activity flagged, even when these are not attacks. AI² is a collaboration between MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and PatternX, a machine learning startup with a focus on information security and threat prediction. The hybrid platform combines Artificial Intelligence, with Analyst Intuition, to give AI².

Google is beginning to look beyond search to tap into some of the most lucrative and promising businesses in the tech industry: artificial intelligence and cloud computing. The company, the largest and most significant part of Alphabet Inc., has grown to mammoth proportions off the back of its search-based advertising division. But those revenues are starting to slow. The cloud allows companies to manage and sell server space and software that lives inside its data centers, like AI, to other large companies. That type of service-based business is fast becoming the new way to reap profits in the tech industry.

With all the buzz about artificial intelligence and the launch of the Facebook bot marketplace, I thought it might be helpful to look at the potential implications for marketers over the next 12 months and provide a relatively jargon-free look at some of the near-term opportunities and tips on how to start to prepare for them. At a high level, it's about using AI to power more direct interactions between brands and people, focusing on faster, smarter responses to their questions and needs. Yes, Facebook has released the bot store and messenger maps will become the primary channel for digital customer service and inquires. Facebook is not the only one -- Microsoft has a bot API in Skype and other popular messaging apps such as Kik have also released functionality. Brands like KLM have already rolled our messenger bots for accessing your flight data, and airlines are some of the biggest users of customer service via Twitter.

A century ago, more than 60,000 tigers roamed the wild. Today, the worldwide estimate has dwindled to around 3,200. Poaching is one of the main drivers of this precipitous drop. Whether killed for skins, medicine or trophy hunting, humans have pushed tigers to near-extinction. The same applies to other large animal species like elephants and rhinoceros that play unique and crucial roles in the ecosystems where they live.

Google's parent company Alphabet saw its revenue grow 17% during the first three months of this year, the company said on Thursday, but spent more money on its experimental moonshot projects, engineers, data centers and YouTube shows, causing it to miss investors' profit expectations. Alphabet shares dropped more than 4% in the US during after-hours trading to about 724 a share. The dilemma illustrates Alphabet's key challenge as it seeks to become the technology firm most omnipresent in consumers lives, including search, email, smartphones, maps, self-driving cars, virtual reality and even cancer research. Alphabet's growth has also attracted attention from regulators. On 20 April, the European Union's antitrust regulators charged the company with using its mobile operating system, Android, to block out competitors.

Behavioral economics is an exciting skeleton on which to build human systems such as technology and communities. One of the leading minds in behavioral economics is Dan Ariely, New York Times best-selling author of Predictably Irrational, The Upside Of Irrationality, and frequent TED speaker. I recently interviewed Dan for my Forbes column to explore how behavioral economics is playing a role in technology, data, artificial intelligence, and preventing online abuse. Predictably, his insight was irrationally interesting. OK, that was a stretch.

Rodney Brooks wasn't willing in 2002 to hazard a guess about when the challenges of robotics would be overcome. "Not in two years or three years," Brooks asserted during an IndustryWeek interview that year. "But is it going to be here in 30 years or 40 years? I'm not quite prepared [to make a prediction]." Still in a book published then and the interview, he gave us a peek at what it would look like when it arrived: "robots that take instruction easily rather than ones that require hours of programming time; robots that can help in small-batch operations rather than ones that only make financial sense in continuous or nearly continuous fixed operation settings with long runs; robots with social interaction skills;" and robots that reduce costs on the factory floor.

Google CEO Sundar Pichai thinks we're hurtling towards a future where you'll rely on artificial intelligence more than your smartphone. "In the long run, we're evolving in computing from a'mobile-first' to an'AI-first' world," he said on Alphabet's Q1 earnings call. Google has long used a ton of AI and machine learning in its core products. Investment and research in those areas allows it to serve you the best search results depending on your context (like giving you live sports scores if you search the name of a team during a game), warn you about traffic or the weather, and even write emails for you. And, for now, finding ways to become more like a smart assistant on your smartphone is a big focus.