For NVIDIA (NASDAQ:NVDA) shareholders, the past year has been fantastic. The stock has soared 190%, with all of the company's segments firing on all cylinders. The core graphics card business is booming, with PC gaming proving to be a bright spot in an otherwise dismal PC market. Enterprise use of NVIDIA's products is growing fast, with cloud computing companies turning to NVIDIA's Tesla GPUs to enable deep learning and artificial intelligence applications. Sales to the automotive industry are rising as well, with NVIDIA's automotive platforms gaining momentum.

Microsoft Corp.'s acquisition of the smart scheduling app Genee reflects a drive to add artificial intelligence to all of its digital experiences. The deal, announced Monday, could let Microsoft enhance its virtual assistant Cortana, to better compete with Alphabet Inc.'s Google Now and Apple Inc.'s Siri, as CIO Journal's Angus Loten reports. With Genee, Cortana could automatically set up business meetings by interpreting keywords in email. Though AI gets much attention these days, many CIOs don't have a clear idea about how to use the technology or maximize its value. Microsoft is expanding its AI expertise partly through acquisition, recently buying Wand Labs, a smart messaging app, and SwiftKey, a tool that predicts what users want to type next.

A fascinating new simulation finds that self-driving cars will terraform cities: 90% of cars will be eliminated, acres of land will open up, and commute times will drop 10%. A team of transportation scientists at the Organization for Cooperation and Development took data on actual trips in Lisbon, Portugal and looked at how a fleet of self-driving, shared "taxibots" would change city landscape [PDF]. These "taxibots", the researchers imagine, are a marriage of mass carpooling and UPS delivery intelligence: they constantly roam throughout cities and match carpool routes with mathematical elegance. Ultimately, they estimate, 9 out of 10 cars would be completely unnecessary -- as would public transit. "Nearly the same mobility can be delivered with 10% of the cars TaxiBots combined with high-capacity public transport could remove 9 out of every 10 cars in a mid-sized European city," the paper concludes.

You might think of drones as friendly things, like the DJI Phantom you fly yourself or those Amazon drones that could soon be delivering your groceries. Think again when it comes to military drones. An MQ-9 Reaper unmanned aerial vehicle with a 66-foot wingspan can loiter 50,000 feet above the Earth for a day at a time, poised to hit a target with a devastating 3,800 pounds of Hellfire missile payload. But as with all weapons, the awesome firepower of a drone needs to be aimed accurately. "It's less about technology than about strategy, about the way it's deployed," said Gavin Hood, director of drone drama "Eye in the Sky," out now on DVD and Blu-ray.

A U.N. working party will adopt guidelines as soon as November for preventing cyberattacks on network systems used in self-driving vehicles, a source involved in the negotiations said. The guidelines will call on automakers to introduce specific measures for alerting drivers when attacks are detected and preventing the loss of control over the vehicles, according to the source. Discussions on the topic at the World Forum for Harmonization of Vehicle Regulations in Geneva has been led by Japan and Germany, while the United States is planning to establish its own safety regulations separate from the U.N. measures. Autonomous driving, which frees drivers from controlling a vehicle, involves artificial intelligence technology and requires use of a network of electronic devices that collect and exchange data known as the internet of things. But such networks have proven vulnerable to hackers trying to take over self-driving vehicles.

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"They tirelessly patrol outside your property around the clock, and actively deter crime by establishing physical presence at the site," the San Francisco startup Aptonomy said on its website. "[Smart] drones live on your property, and get to know it well. In a live monitoring scenario, you can adjust the drone's viewpoint and move it around safety in real-time – even from hundreds of miles away." Special features of the security drone are a flight controller, day and night vision cameras, strobe lighting and loudspeakers built on top of the DJI S-1000, a camera-carrying octocopter, the type most often used by movie-makers. The security drone's artificial intelligence hardware and navigational systems allow it to fly low and fast, avoiding obstacles in structure-dense environments to detect human activity or faces.

When Google unveiled its Tensor Processing Unit (TPU) during this year's Google I/O conference in Mountain View, California, it finally ticked for this editor in particular that machine learning is the future of computing hardware. Of course, the TPU is only a part of the firm's mission to push machine learning – the practice that powers chat bots, Siri and the like – forward. Google also has TensorFlow, its open source library of machine intelligence software. And sure, the chips that we find in our laptops and smartphones will continue to get faster and more versatile. But, it seems as if we've already seen the extent of the computing experiences that these processors can provide, if only limited by the devices they power.

This short tutorial will not only guide you through some basic data analysis methods but it will also show you how to implement some of the more sophisticated techniques available today. We will look into traffic accident data from the National Highway Traffic Safety Administration and try to predict fatal accidents using state-of-the-art statistical learning techniques. If you are interested, download the code at the bottom and follow along as we work through a real world data set. This post is in R while a companion post covers the same techniques in Python. The swirl package is designed to teach people R.

A drone was confiscated earlier this month after it crashed at a north London jail with drugs and cell phones, according to police. The drone was not alone: Another was seen later that day and caught mid-flight. The drone seizures followed a man acting suspiciously near the prison just one day before the drones were caught. That man ran from police when confronted, dropping two bags of drugs and phones, according to the BBC. No arrests have been made so far in connection to the drugs, phones and drones.