Artificial intelligence and machine learning are being adopted into the enterprise at a rapid clip and adoption is likely to surge in 2019. What comes next is the real business challenge: How will we manage technology that we likely don't understand? The issue is likely to bubble up in the year ahead. For now, most of us are lulled into thinking more algorithms are better and even assuming we can outsource critical thought to models. Why hurt our brains when we can trust Einstein, Watson, Alexa, Google Assistant, and other software tools to think for us?

As the power of artificial intelligence grows, the likelihood of a future war filled with killer robots grows as well. Proponents suggest that lethal autonomous weapon systems (LAWs) might cause less "collateral damage," while critics warn that giving machines the power of life and death would be a terrible mistake. Last month's UN meeting on'killer robots' in Geneva ended with victory for the machines, as a small number of countries blocked progress towards an international ban. Some opponents of such a ban, like Russia and Israel, were to be expected since both nations already have advanced military AI programs. But surprisingly, the U.S. also agreed with them.

Many years ago when I had a hairstyle that needed a comb, my parents ran a manufacturing plant and a wholesale front end was integrated into the building. It followed the usual arc of 3 or so years of hit and miss ( i.e. losses to break-even) income, which was subsidised by my father still holding his job down at an engineering plant; he'd finish his work at 5pm, and go into the business until late at night. The older generation had a work ethic that defies what my definition of hard work is, because they must have worked about 70 hours a week as a norm, with 90 hours seeming more likely. This isn't an exaggeration, as I can remember as a boy that they'd be out there 7 days a week to get the business going. They left home from 7am and came home as late as 11pm sometimes, so the maths aren't unrealistic. I don't know how they did it in those years, either physically, mentally or emotionally.

Old school, new school: The Tampa Bay Rays have two pitchers who have started 20 games this year. One is their ace, Blake Snell, whose 2.03 earned-run average ranks second in the American League. The other is Ryne Stanek, a reliever turned “opener” — in his case, a right-hander who works the first inning or so, followed by a left-hander. In a year in which the Rays lost starters Anthony Banda, Jose DeLeon and Brent Honeywell to Tommy John surgery and traded starters Chris Archer and Nathan Eovaldi, the team leads the AL in ERA since May 19, when Sergio Romo debuted as Tampa Bay’s first “opener.” There is no pitching statistic more derided in sabermetrics than wins for a pitcher.

In this blogpost, you will learn how Azure SQL Database intelligent performance feature Intelligent Insights has successfully helped a customer troubleshoot a hard to find 6-month intermittent database performance issue in a single day only. You will find out how Intelligent Insights helps an ISV operate 60,000 databases by identifying related performance issues across their database fleet. You will also learn how Intelligent Insights helped an enterprise seamlessly identify a hard to troubleshoot performance degradation issue on a large-scale 35TB database fleet. Azure SQL Database, the most intelligent cloud database, is empowering small and medium size business, and large enterprises to focus on writing awesome applications while entrusting Azure to autonomously take care of running, scaling, and maintain a peak performance with a minimum of human interaction, or advanced technical skill set required. Intelligent Insights is a new disruptive intelligent performance technology leveraging the power of artificial intelligence (AI) to continuously monitor and troubleshoot Azure SQL Database performance issues with a pinpoint accuracy and at a large scale simply not possible before.

Billions of text posts, photos, and videos are uploaded to social media every day, a firehose of information that's impossible for human moderators to sift through comprehensively. And so companies like Facebook and YouTube have long relied on artificial intelligence to help surface things like spam and pornography. Something like a white supremacist meme, though, can be more challenging for machines to flag, since the task requires processing several different visual elements at once. Automated systems need to detect and "read" the words that are overlaid on top of the photo, as well as analyze the image itself. Memes are also complicated cultural artifacts, which can be difficult to understand out of context. Despite the challenges they bring, some social platforms are already using AI to analyze memes, including Facebook, which this week shared details about how it uses a tool called Rosetta to analyze photos and videos that contain text.

Since March, when an autonomous vehicle killed a pedestrian in Arizona, forecasts for AVs have been decidedly less optimistic. But autonomous vehicle promoters are undeterred. AI entrepreneur Andrew Ng contends that self-driving cars will be safe for pedestrians when walkers and cyclists conform to their limitations. "What we tell people is, 'Please be lawful and please be considerate,'" he told Bloomberg. Peter Norton is an associate professor in the Department of Engineering and Society at the University of Virginia. He is the author of Fighting Traffic: The Dawn of the Motor Age in the American City.

LAST December, Ed Bridges was mingling with the crowds of Christmas shoppers on the streets of Cardiff, UK, when the police snapped a picture of him. He has been trying to get them to delete it ever since. Bridges hasn't been convicted of a crime, nor is he suspected of committing one. He is simply one of a vast number of people who have been quietly added to face-recognition databases without their consent, and most often, without their knowledge.

A new flying robot called DelFly has flapping wings and can dodge a swatting hand with as much agility as a fruit fly. DelFly has two thin plastic wings on each side of its body, inspired by a fruit fly. Though it's 55 times bigger than an actual fruit fly, DelFly can do all the same aerial acrobatics. It can even perform 360-degree flips – a move flies never seem to do. Flies perform agile evasive motion when trying to escape a threat, such as a predator or an incoming flyswatter. One particularly nimble move they perform is called a banked turn, and involves tilting their bodies to perform a sharp change in direction.

Mattel's AI nanny, called Aristotle, recently gained the notorious distinction of being subject to a bipartisan protest in the US Congress. Plus, there was a petition against it with over 15,000 signatures. The Campaign for a Commercial-Free Childhood, which organized the petition, argued that Aristotle is a consumerist ploy. It "attempts to replace the care, judgment and companionship of loving family members with faux nurturing and conversation from a robot designed to sell products and build brand loyalty." Aristotle, designed to interact with kids, was based on the same technologies as virtual assistants such as Amazon's Alexa.