Bengaluru-based Microsoft Accelerator has selected 14 startups for its startup accelerator programme. It is the tenth batch for Microsoft's Accelerator Programme. Selected startups belong to the realm of AI and machine learning and will undergo an intensive programme to increase their'enterprise readiness quotient.' The cohort has been selected from VC portfolios – including Inventus Capital Partners, Ideaspring Capital, Accel Partners, IDG Ventures and Pi Ventures, based on their nominations. They were selected based upon founder experience and industry expertise, products, and traction, as per an official statement.

AI is no longer the future--it's now here in our living rooms and cars and, often, our pockets. As the technology has continued to expand its role in our lives, an important question has emerged: What level of trust can--and should--we place in these AI systems? To explore this question, we spoke to 30 AI scientists and leading thinkers. They told us that building trust in AI will require a significant effort to instill in it a sense of morality, operate in full transparency and provide education about the opportunities it will create for business and consumers. And, they say, this effort must be collaborative across scientific disciplines, industries and government.

Artificial intelligence has become as meaningless a description of technology as "all natural" is when it refers to fresh eggs. At least, that's the conclusion reached by Devin Coldewey, a Tech Crunch contributor. AI has become a popular buzzword, he said, precisely because it's so poorly defined. Marketers use it to create an impression of competence and to more easily promote "intelligent" capabilities as trends change. The popularity of the AI buzzword, however, "has to do at least partly with the conflation of neural networks with artificial intelligence," he said.

At the heart of AI systems are statistical models that have no concept of social inequality, fairness, or hardships. In Cathy O'Neil's book, Weapons of Math Destruction (WMD), she points out that big data is discriminating nearly at every juncture of our society and pummeling the poor at each opportunity. Her book points to many avenues of misuse of data, but most offensive is through the use of proxies. Data statistics that are designed for one purpose but are repurposed to be used for economic or convenience sake. There are a number of examples of this.

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As the tug of war between humans and machines escalates, we've become witnesses on nearly a daily basis to events that suggest there won't be an ultimate winner or loser in this existential battle for survival and supremacy. Just take two little human mistakes that recently received worldwide attention because of the power of today's technology to magnify their impacts on a global scale. The first was the mistake made by a senior partner at PricewaterhouseCoopers, who was assigned to hand an envelope to an actor tasked to announce the best picture of the year. This is a task that has been performed flawlessly for decades. It is a job that has been practiced so often that a structured protocol has been established to ensure that it is handled seamlessly.

California released a proposal this week amending some of its strict regulations for autonomous vehicles. If all goes as planned, the state will allow self-driving vehicles to operate without a human driver behind the wheel starting next year. The proposal eliminates some of the hoops automakers have to jump through to test self-driving cars on public roads, reports the Los Angeles Times. Testers no longer need to obtain permission from each locality their cars drive through, and instead only need to inform each location of their plans. And rather than creating an emergency plan with each group of law enforcement officials, companies would only need to file a communications plan going forward.

The field of AI has seen a significant increase in interest in the past couple of years, including an upswing in the number of large enterprises running their own experiments with AI systems. The vast majority of AI projects in enterprises is still at the experimentation stage where about half of large enterprises are experimenting with "smart computing" projects. These organizations are examining problems and deciding whether AI can be applied to find solutions. These efforts are still in the early stages. But one area that appears to be taking off is how enterprises are now seriously looking at "accelerated analytics" and "AI driven analytics" as a solution to the data deluge many companies are seeing.

Digital transformation is clearly essential to companies' future success, as businesses that manage the digital transformation process well are already seeing higher growth, profit, and employee engagement rates than their peers, according to the Leaders 2020 Research Brief. Digital transformation, however, is not merely about the implementation of new technology but, just as important, about the usage of this technology. As we go about our private lives, we are increasingly relying on the Internet of Things (IoT) to connect us to myriad applications, services, service providers, and vendors. We are connected to the IoT through everything from our smartphones, wearable fitness devices, and personal virtual assistants, to connected cars, connected homes, GPS locators, and a wide variety of sensors. All of this happens in an increasingly seamless fashion, and our usage of these technologies is affecting virtually every aspect of our daily routines and tasks. From a corporate perspective, the massive amounts of data generated – through these devices and the billions of enterprise devices and sensors that are already connected (15 billion devices in 2015 based on an Intel infographic) – is creating the potential for an entirely new level of integration and usage of data into our business decisions.

Some of the world's biggest leaders in science and technology including Stephen Hawking, Elon Musk, Steve Wozniak, and Bill Gates, have expressed their concerns about the rapid progression and evolution of Artificial Intelligence (AI). Elon Musk in a CNBC interview stated, "I think that the biggest risk is not that the AI will develop a will of its own… but rather that it will follow the will of people that establish its utility function." Movies like The Terminator, The Matrix, Ex Machina, 2001: A Space Odyssey amongst others, all point to the notion that artificial intelligence will evolve past human intelligence to the point that we will no longer be able to control our own creations. There is an ingrained narrative that AI will somehow reach a level of self-awareness and inevitably then attempt to destroy or replace the human race. And while some of these ideas may seem excessive, or merely the product of media and film exaggeration of AI leading to Terminator-like robots hunting humans like deer, there is enough concern amongst thought leaders such as those mentioned above, to make these concerns highly credible even if there is no certainty about them ever playing out.