Peggy Smedley: For you, what are the most interesting trends that you see? You and I have talked in the past about the IoT (Internet of Things) and I know that you have a lot of vision, a lot of examples that you look at when you think about cloud and edge and we talk about manufacturing and all these things in vertical markets, but for listeners right now, based on investments you guys [Microsoft] are making, what do you see are the most interesting trends? Sam George: Well, I think if you zoom the telescope way back out and look at the very big picture, what we're seeing across all of these vertical markets, whether it's manufacturing or agriculture, smart cites, smart energy. If you take a look at what's happening with all of these, there's a set of disruptive technologies that are fundamentally transforming how those industries function. Cloud was a big catalyst for that and I'd say, very well established at this point. And then IoT, a couple of years ago, really started hitting the scene, building on top of cloud and giving these businesses unprecedented visibility if they were able to take advantage of it back in the early days. Virtually all aspects of their business are able to sense things in the physical world, in realtime, that they weren't able to before. And then while the IoT was happening, edge computing started happening too, which was a normal and natural optimization, where as I connect and start collecting data from these billions of devices that are sensing across all of these different industries that are sensing things that are happening, it's natural to start taking some of the computing that you were doing in the cloud and some of the services that you were taking advantage of and pushing those right out and distributing those right out to the devices themselves for a variety of reasons, whether that's latency concerns or security concerns or anything else. We see this wonderful trend of AI that is powering really new breakthrough capabilities across all of these industries. AI is a great example, where as it takes advantage of those proceeding waves, edge computing and the IoT and cloud. AI can now run in a distributed fashion as well.

William Karnes, MD, is director of the high-risk program and colonoscopy quality at the UCI Health H.H. Chao Comprehensive Digestive Disease Center in Orange, Calif., and chief medical officer of Docbot, a technology that uses artificial intelligence to detect abnormalities from colonoscopy capsule video. Here, Dr. Karnes shares his thoughts with Becker's ASC Review on the future of AI in the gastroenterology specialty, and how the technology could help patients and physicians. Question: Can you tell me a little more about the Docbot technology and how you got involved? Dr. William Karnes: The story goes back to 2012 when I came to UCI and Dr. Chan brought me on to wipe out colon cancer in Orange County. It was a three-pronged approach but one of the most important ones.

The Whole time Director, Amnaika Roy Rashtrawar, of IFFCO Tokio General Insurance said that technology would play a major role in the extension of the reach of insurance products to several remotest parts of the country. She shared her views during an interview regarding the recent developments in the space of general insurance and the future plans of the company that would have a significant impact on their customer's experience. Interviewer: In your opinion, will technology be able to play a bigger role for insurance penetration in India, keeping in mind the cheap data plans and the increasing number of users of smartphone? Technology has always been a major promoter of insurance products. As more and more customers shall be getting access to the internet via high-speed networks, technology shall be helping to extend the reach of products of insurance.

Someday, artificial intelligence could become so advanced that it gains the ability to think creatively -- and, perhaps, so vastly surpasses humanity's artistic abilities that it would have to explain its creations to our squishy, primitive brains. At least, that's one of the predictions that physicist, philosopher, and creativity scholar Arthur Miller makes in his new book, "The Artist in the Machine." The book, released last month, details how machines are starting to demonstrate creativity, from learning to improvise music to pulling together insights from seemingly unrelated fields of research -- and suggests how the trend might continue. Futurism caught up with Miller to chat about his book and his thoughts on art and the future of creativity. While some of the technology Miller describes, like artificial general intelligence, is probably hiding in the distant future, he argues that today's technology may be more creative than most assume.

As I had always been in love with technology, I have a habit of exploring new technologies. I like to read about what's happening in the tech world and how these new technologies can disrupt the current industries. In the recent past, as I was exploring and reading extensively on what impact can recent technologies have over our lives, I quickly noticed that there were a few terms that were thrown around almost all over the place: AI, Data Science, Machine Learning, Deep Learning. Although, technically wrong, let's refer to these technologies as AI (Artificial Intelligence) in general. I was kinda hooked and I started to casually read about them as these technologies naturally appeared to have the potential to disrupt any industry imaginable.

Shelf, the leading AI-enabled knowledge management platform on the market, received the Business Intelligence Group "Best New Product of the Year" BIG Award in the startup category when the 2019 award winners were announced on November 6th 2019. The BIG Awards recognize the innovative products, people, and technologies leading their respective industries. Shelf was selected from a pool of 1000's of applicants, thanks to its unique ability to transform how employees access critical company knowledge. According to Maria Jimenez, chief nominations officer of the Business Intelligence Group, "We assessed numerous enterprise technology products in our search for the Best New Product and found Shelf capabilities to be truly unique. The product itself is intuitive and easy to use, and the ROI Shelf produces for its customers is undeniable. As a result, we felt as though Shelf was in a class of its own and deserving of this recognition."

The China Cables, obtained by the International Consortium of Investigative Journalists, reveal about the camps in which more than a million Uighurs and other ethnic minorities are understood to be detained. This is for the first time a document outlining the camps has been leaked. In an exclusive Skype interview with Fergus Shiel, Project manager of China Cables, Saurabh Bose of WION asks about the classified intelligence briefings that reveal about the scope and ambition of Chines govt's AI-based policing platform. Two things differentiate China Cables from previously investigations, that an operation manual has revealed the camps in which more than a million Uighurs and other ethnic minorities are understood to be detained. The NYT had policy settings of these camps, anecdotal reports, satellite images, but this is the very first time that a document outlining the camps have been leaked we understand that it is the first document of it's kind to come out of China for the last thirty years because of it's classification level.

People are working to create a machine that behaves like a human. The thinking machine can be also termed as artificial intelligence, which tends to be the biggest gift to humankind. Undoubtedly, it's evident that the Machine learning course is the current trend as the market scale keeps increasing due to its high demand factor. Machine learning course gives us a clear idea of how the future leads us to innovate unlimited and incredible technologies that happening around us each day. Organizations & businesses are been influenced by the smart machine works due to its high accuracy ratio of output delivery when compared to the output ratio delivered by humans.

I will also appreciate more future posts. While building sophisticated machine learning models is getting easier, understanding how models develop knowledge and arrive to conclusions remains a very difficult challenge. Typically, the more accurate the models the harder they are to interpret. KDNuggets posted an article highlighting the value and resources surrounding AI Explainability - what do you think? Are these tutorials useful for you?

There is a problem with artificial intelligence. It can be amazing at churning through gigantic amounts of data to solve challenges that humans struggle with. But understanding how it makes its decisions is often very difficult to do, if not impossible. That means when an AI model works it is not as easy as it should be to make further refinements, and when it exhibits odd behaviour it can be hard to fix. But at an event in London this week, Google's cloud computing division pitched a new facility that it hopes will give it the edge on Microsoft and Amazon, which dominate the sector.