General Motors Co. GM -1.12 % 's proposed purchase of tiny Cruise Automation Inc. for more than 1 billion would be one of the auto industry's biggest Silicon Valley acquisitions to date. And it would certainly not be the last. Auto makers and car-parts suppliers have hooked into tech startups in recent years to boost their in-vehicle connectivity and to accelerate autonomous-car development. The Bay Area already is dotted with auto-industry outposts funding or recruiting Silicon Valley engineering talent to keep pace with Alphabet Inc. GOOGL -0.36 % 's Google X and others working on self-driving cars. Carol Reiley, president of Bay Area autonomous-driving startup Drive.ai, said her company, which like Cruise Automation and Zoox has been operating under the radar, just raised 12 million from venture-capital investors.

When Ray Kurzweil met with Google CEO Larry Page last July, he wasn't looking for a job. A respected inventor who's become a machine-intelligence futurist, Kurzweil wanted to discuss his upcoming book How to Create a Mind. He told Page, who had read an early draft, that he wanted to start a company to develop his ideas about how to build a truly intelligent computer: one that could understand language and then make inferences and decisions on its own. It quickly became obvious that such an effort would require nothing less than Google-scale data and computing power. "I could try to give you some access to it," Page told Kurzweil.

Jia Jia (innovation consultant; New York): Reading about Google's AlphaGo crushing world champion Lee Se-dol made me unexpectedly afraid. I'd not given much thought to AI and had assumed that warnings from the likes of Elon Musk, Stephen Hawking and Bill Gates was cautionary but no cause for alarm. But knowing how the computer plays is unnerving. After his defeat in the first game, Lee commented of AlphaGo that "It did not play like a human at all." In fact, AlphaGo had made an early mistake but didn't lose its cool as a human would.

In the final game of their historic match, Google's artificially intelligent Go-playing computer system has defeated Korean grandmaster Lee Sedol, finishing the best-of-five series with four wins and one loss. The win puts an exclamation point on a significant moment for artificial intelligence. Over the last twenty-five years, machines have beaten the best humans at checkers, chess, Othello, even Jeopardy! But this is the first time a machine has topped the very best at Go--a 2,500-year-old game that's exponentially more complex than chess and requires, at least among humans, an added degree of intuition. Game Five grew into the most exciting of the series, a game balanced on a knife edge. The victory is notable in its own right. But this week's events are even more significant when you consider that the machine learning technologies underpinning Google's machine, known as AlphaGo, are already pushing their way into real-world applications.

In winter, snowfall can rapidly disrupt daily life and impact on Japan's economy. Snowplowing is a considerable annual expense, and methods for co-ordinating plowing activity are needed to ensure an efficient, cost-effective service. Clever computer models are needed to manage such complex activities, which involve many agents and interactions. Now, Satoshi Takahashi at the University of Electro-Communications, and Tokuro Matsuo at the Advanced Institute for Industrial Technology in Tokyo have devised a computational method that combines task allocation and scheduling of individual snow-plows to maximize efficiency. The researchers aimed to identify the best routes for multiple snow-plows to take without replicating route paths, meaning their computer model had to allocate and schedule tasks simultaneously.

Russian Defence Minister Sergei Shoigu announced Friday that Moscow will deploy a range of missile systems on the Kuril islands, claimed by Japan, as part of its military build-up in the far-eastern region, Agence France-Presse (AFP) reported. The islands have been a reason of tense relations between Moscow and Tokyo. "The planned rearmament of contingents and military bases on Kuril islands is under way. Already this year they will get Bal and Bastion coastal missile systems as well as new-generation Eleron-3 unmanned aerial vehicles," Shoigu said during a ministry meeting, AFP reported. Russia has been investing in military infrastructure on the Kuril islands, which Japan considers its territory, leading to strained relations between the two nations.

A company that helps users to create their own websites now knows what kind of sites their 80 million users are building without pestering them with repeated questions. Wix, a Tel Aviv-based web development company, is using machine learning on Google's cloud platform to learn more about its users so it can help them find the images they need to build interesting and useful websites. That's just the beginning of how machine learning will be used in the cloud, according to industry analysts who say machine learning will be the biggest thing that's ever hit the cloud. David Zuckerman, head of developer experience for Wix, said machine learning in the cloud will be a boon to companies that don't have a major research division. "The cloud has brought this technology to everyone," he said.

In an unassuming, two-story Victorian town house in Bristol, people are being filmed, monitored, and tracked 24/7. Invisible sensors constantly keep a watchful eye as they go about their business. But what these folks lose in privacy could be our collective gain in life expectancy--that is, if the long-term data bears out. Pivotal to the 15-million ( 21M) Sensor Platform for Healthcare in a Residential Environment (SPHERE) project, this house has been invisibly fitted with dozens of cameras and sensors while its occupants are asked to don wearable devices. The aim is to research how health is related to everyday lifestyle and living conditions over time.

Dr. Quoc Viet Le is a research scientist at Google Brain known for his path-breaking work on deep neural networks (DNN). He is especially famous for his Ph.D work in image processing under Andrew Ng, one of the pioneers of the DNN revolution. Le's and Ng's work demonstrated how computers could be used to learn complicated features and patterns in a way similar to how the mammalian brain learns, with better performance than earlier neural network technology. One of their first breakthroughs was demonstrating the training of a large neural network to detect cats from YouTube videos. This revolutionized the interest in DNNs, and got the current giants of the computer industry such as Google, Facebook and Microsoft in a race to incorporate AI techniques into their software.

It was the unspooling of an unfortunate series of events involving artificial intelligence, human nature, and a very public experiment. Amid this dangerous combination of forces, determining exactly what went wrong is near-impossible. But the bottom line is simple: Microsoft has awful lot of egg on its face after unleashing an online chat bot that Twitter users coaxed into regurgitating some seriously offensive language, including pointedly racist and sexist remarks. On Wednesday morning, the company unveiled Tay, a chat bot meant to mimic the verbal tics of a 19-year-old American girl, provided to the world at large via the messaging platforms Twitter, Kik and GroupMe. According to Microsoft, the aim was to "conduct research on conversational understanding."