The resounding win by a Google artificial intelligence programme over a champion in the complex board game Go this month was a statement - not so much to professional game players as to Google's competitors. Many of the tech industry's biggest companies, like Amazon, Google, IBM and Microsoft, are jockeying to become the go-to company for AI In the industry's lingo, the companies are engaged in a "platform war". A platform, in technology, is essentially a piece of software that other companies build on and that consumers cannot do without. Become the platform and huge profits will follow. Microsoft dominated personal computers because its Windows software became the centre of the consumer software world.

Games such as chess and Go display perfect information, and AI clearly has an upper hand. What happens, however, when information is imperfect and requires strategy? It has often been said that traditional business intelligence is like driving while looking in the rearview mirror. The implication, of course, is that real-time analytics is more like sensible driving behavior, where you keep your eyes mainly on the road ahead. That includes setting your direction to reacting in a second to get to where you want to go.

Artificial intelligence is rapidly changing the business and consumer landscape, but has it reached its full potential? And in 2016, we will continue this momentum and see artificial intelligence redefine the future of work, deliver on the promise of big data, and even transform consumers' lives. The pace at which large-scale organizations more widely adopt artificial intelligence to replace manual, repetitive tasks will rapidly increase. We're already seeing enormous investments from companies like Toyota to use artificial intelligence for more precise decision making. This is just one example of the many companies taking this approach to foster higher productivity and business profits, and also streamline responsibilities for high-skill jobs.

Author's Note: This article is a part of a series about "China & Israel's Interaction in Business". The past decade has seen both China and Israel doing exceptionally well in the business sector. Israel, the dubbed "Startup Nation", has had its startup ecosystem bloom and flourish in recent years with an incredible 69% growth from 2014 to 2015 alone. Meanwhile, China has been busy living out the business world's version of the "Cinderella" story, transitioning in under 30 years from an oppressed and bullied nation with high poverty rates to becoming one of the leading economic capitals of the world. Naturally, the shared success and prowess of both countries in their respective fields has caught the other's eye, and has birthed a love story of sorts between Israeli entrepreneurs and Chinese investors who share a mutual interest for the other's trade.

Tay isn't the first chatbot in history but it became the most prominent because of its ties with Microsoft. Then it became one of the most notorious chatbot in less than 24 hours after it switched from well-meaning teen to offensive, pro-Nazi, anti-feminist rebel. Naturally, Microsoft shut it down, "putting it to sleep", so to speak. Now the company has come out with a statement clarifying that Tay's words do not reflect the company's principles and values at all. They do own up to the "slight" oversight in protecting Tay from attacks.

A group of logistics entrepreneurs is launching a Silicon Valley-style accelerator for supply-chain technology startups, aiming to draw new investment and talent to the freight business. The founders say they will run the Dynamo program alongside a 12 million logistics venture fund in Chattanooga, Tenn. The accelerator will have a 3 million budget raised from the fund and other partners to put toward startups focused on logistics-oriented technologies such as autonomous-truck operations, drones and software. The startups will participate in a three-month program that will include testing their ideas with businesses in the Chattanooga area. The city has a growing manufacturing base, and is close to distribution hubs.

An Iranian charged with hacking the computer system that controlled a New York dam used a readily available Google search process to identify the vulnerable system, according to people familiar with the federal investigation. The process, known as "Google dorking," isn't as simple as an ordinary online search. Yet anyone with a computer and Internet access can perform it with a few special techniques. Federal authorities say it is...

Rather than dexterity or flying skills, what you really need to be a professional civilian drone pilot may simply be patience. Australian startup Ninox, which began trials in 2015, is one of a number of local companies that has a business plan relying on the services of professional drone pilots. Ninox, in particular, plans to hire out its unmanned aerial systems (UAS) to assist with invasive pest detection and agricultural mapping, among other tasks. But first, they need people to fly their machines. Colin Smith, a former army major in the Australian Defence Force, is the company's newest chief UAS controller.

No longer the exclusive domain of data-reliant businesses like Google, Microsoft, and Amazon, Machine learning has been making its way to the masses as an essential approach to data. Today, machine learning is understood and accepted by a more mainstream audience, and has become a measurable driver for big business both on and offline. There are three key reasons why machine learning has become one ofthe top 10 strategic technology trendsthat will shape digital business opportunities through 2020. First, the volume of data companies now collect is so massive that many struggle to make sense of it. Machine learning allows companies to take advantage of the information they already have.

Last week we previewed this in "How Machine Learning APIs are Being Used to Predict Startup Success." Can there be a quantifiable way to hedge investors' risk and ensure they are betting on the right horse? According to the startup "jury" algorithm PreSeries, it's mathematically probable to predict which startup is most likely to succeed and that startup is Novelti. This startup which uses online machine-learning algorithms to convert Internet of Things sensor data into real-time intelligence, machine learning and pattern recognition was predicted to be successful with an 87 percent likelihood. Novelti beat out four other predictive analytics and artificial intelligence competitors--Intranetum, Emotion Research Lab, Datatrics and restb--at the PAPIs Connect conference for machine learning and predictive APIs.