It's your nighttime routine: You drop your phone onto the nightstand charging pad, and it asks about your day. You tell it, talking to the virtual personal assistant just like you'd talk to a friend. Your phone's artificial intelligence knows you almost as well as you know yourself (maybe even better). So when it suggests ways to get through tomorrow's calendar, you trust its advice. AI is practically everywhere, and getting smarter all the time.

Industrial robots used to be dumb, somewhat inflexible, and mostly blind - but also fast, precise and very efficient. As the cost of components, sensors and vision systems has been dropping, vision-enabled robots are becoming more prevalent and capable, and the industry is dramatically changing. Those changes can be seen in recent trends in China, investments in and acquisitions of robotic companies, by an analysis of recent startup companies, new and widening application areas for robot use, and technological developments. For the past 50 years industrial robots have picked the low-hanging fruit of manufacturing by handling the dull, dirty and dangerous tasks. But today, as consumers want more personalized products, and want them faster, and as costs have dropped and executives have pushed for greater productivity through automation, mobile and vision-enabled robots are emerging and being deployed in many new application areas, particularly for SMEs and in logistics, but also in government, agriculture, surveying, construction and healthcare.

Intent on driving automation throughout the business, DLA Piper has partnered with Canadian tech firm Kira Systems to launch an artificial intelligence tool for document review during M&A transactions. The move comes just three months after Kira Systems secured a similar deal with Big Four accountant Deloitte and follows a 200-person UK redundancy round by DLA Piper as part of an attempt to shift towards automation. 'We believe that this innovative technology will do for corporate transactional work what e-discovery has done for litigation,' said Jonathan Klein, chair of DLA Piper's US M&A practice. 'It will not only make due diligence faster and more efficient, but will mitigate risk throughout the process, all of which are important benefits for our clients and the firm.' Kira Systems has developed machine-learning software, which will be available for DLA Piper lawyers across the global firm, to search and analyse text in contracts.

Recent advances in artificial intelligence have made it clear that our computers need to have a moral code. Consider this: A car is driving down the road when a child on a bicycle suddenly swerves in front of it. Does the car swerve into an oncoming lane, hitting another car that is already there? Does the car swerve off the road and hit a tree? Does it continue forward and hit the child?

After escalating one of the most lethal covert operations in U.S. history, President Obama finally made a public estimate of the civilian cost of the nation's secret drone program, which has targeted Islamic militants in remote corners of the globe. Human rights groups immediately challenged the estimate and the amount of transparency from the administration, saying both were too limited. The White House said that 64 to 116 civilians had been wrongly killed in 473 strikes launched by the U.S. government from the time Obama was inaugurated and the end of last year. The vast majority of the attacks were launched by drones, officials said, but the estimate also covers some strikes using manned aircraft. Monitoring organizations estimate the number of civilians killed in U.S. strikes ranges from 200 to more than 1,000.

BMW, a company that prides itself on building "the ultimate driving machine," plans to start producing fully autonomous vehicles by 2021 for ridesharing programs. Think of it as Uber for people who don't like people. This is a surprising move, given that the company has said essentially nothing about technology that everyone from Google to General Motors to Tesla is racing to develop. And it marks a radical departure from the slow-and-steady approach of the mainstream automakers, who see the technology rolling out slowly over the next two decades. Still, ze Germans see themselves surging ahead by relying upon help from Intel and Mobileye, an Israeli firm that dominates the market for the cameras that are key to active safety features like collision warning and lane-keeping.

On 7 May, a Tesla Model S was involved in a fatal accident in Florida. At the time of the accident, the vehicle was driving itself, using its Autopilot system. The system didn't stop for a tractor-trailer attempting to turn across a divided highway, and the Tesla collided with the trailer. In a statement, Tesla Motors said this is the "first known fatality in just over 130 million miles [210 million km] where Autopilot was activated" and suggested that this ratio makes the Autopilot safer than an average vehicle. Early this year, Tesla CEO Elon Musk told reporters that the Autopilot system in the Model S was "probably better than a person right now."

Louis Columbus recently wrote in Forbes, "Machine learning's core technologies align well with the complex problems manufacturers face daily. From striving to keep supply chains operating efficiently to producing customized, built- to-order products on time, machine learning algorithms have the potential to bring greater predictive accuracy to every phase of production. Many of the algorithms being developed are iterative, designed to learn continually and seek optimized outcomes. These algorithms iterate in milliseconds, enabling manufacturers to seek optimized outcomes in minutes versus months. The ten ways machine learning is revolutionizing manufacturing include the following."

VR Infinite Gesture is a plugin for developing VR games in the Unity Game Engine. Watch the Getting Started tutorial video here: https://youtu.be/NfHi7ZnA8EE Use the included VR user interface to Record, Edit, and Train your gestures into the Neural Network. After you've trained it, it can detect your gestures. We've included Playmaker extensions so you can create a VR gesture tracking game without code!

PyData Seattle 2015 Machine learning models often result in actions: search results are reordered, fraudulent transactions are blocked, etc. But how do you evaluate model performance when you are altering the distribution of outcomes? I'll describe how injecting randomness in production allows you to evaluate current models correctly and generate unbiased training data for new models. Stripe processes billions of dollars in payments a year and uses machine learning to detect and stop fraudulent transactions. Like models used for ad and search ranking, Stripe's models don't just score---they dictate actions that directly change outcomes.