Compared to the introduction of software as a service (Saas), which is more like a cosmetic change, this radical turnaround will be triggered and driven by Artificial Intelligence, or more specifically, by Machine Learning . Machine Learning allows computer programs to process data automatically in real-time to develop predictive models from data. With programs that are capable of performing this process, companies could ascend to new levels of data analysis to draw patterns and predictions from existing data. The opportunities arising from this are endless. Software solutions that rely on Machine Learning hardly require human input.

IRIS.TV, a video personalization company that enables publishers and marketers to maximize the value of their video inventory by streaming custom programming to individual users across all devices, announced a partnership with Vemba, a premium video distribution and content discovery platform. Vemba is a uniquely publisher-focused platform, enabling content publishers to directly control all components of video distribution, ingestion and monetization. Content from Vemba's discoverable marketplace works with any video player technology, and offers real time video analytics across all player environments. "Our proprietary prescriptive analytics enables publishers using the Vemba platform to make actionable decisions based on data-driven insight and provides real-time performance data to understand asset value and to maximize return on video syndication," says Field Garthwaite, CEO of IRIS.TV (pictured top left). The Vemba partnership with IRIS.TV enables publishers to maximize revenue from their video content libraries by providing users with personalized content using both owned and external video content sources.

Dmitry Malioutov can't say much about what he built. As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM's corporate clients. One such program was meant for a large insurance corporation. It was a challenging assignment, requiring a sophisticated algorithm. When it came time to describe the results to his client, though, there was a wrinkle. "We couldn't explain the model to them because they didn't have the training in machine learning." In fact, it may not have helped even if they were machine learning experts. That's because the model was an artificial neural network, a program that takes in a given type of data--in this case, the insurance company's customer records--and finds patterns in them. These networks have been in practical use for over half a century, but lately they've seen a resurgence, powering breakthroughs in everything from speech recognition and language translation to Go-playing robots and self-driving cars.

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When the news broke last month that Microsoft was to acquire LinkedIn for a little over 26 billion, it sent shockwaves through the tech world as one of the most expensive deals of its kind in history. The question is: Why did it happen, what was the potential gain for each side of the table and where do we go from here? The truth is, we've seen a number of acquisitions like these, even if the particular deals we've witnessed haven't reached 26 billion. In this case, it appears that both Microsoft and LinkedIn needed each other in a way that would defend their position and possibly grow much faster. Microsoft wants to integrate LinkedIn's database into a variety of Microsoft products for greater intelligence so that Skype, Word or Exchange will be LinkedIn enabled.

By the year 2030, artificial intelligence (A.I.) will have changed the way we travel to work and to parties, how we take care of our health and how our kids are educated. Focused on trying to foresee the advances coming to A.I., as well as the ethical challenges they'll bring, the panel yesterday released its first study. The 28,000-word report, "Artificial Intelligence and Life in 2030," looks at eight categories -- from employment to healthcare, security, entertainment, education, service robots, transportation and poor communities -- and tries to predict how smart technologies will affect urban life. "We believe specialized A.I. applications will become both increasingly common and more useful by 2030, improving our economy and quality of life," Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts, said in a written statement. "But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of A.I. are broadly shared."

We recently spoke to FastCo Design about how design jobs would evolve. The article included excerpts from Rob Girling's exploration on how Artificial Intelligence will impact design. Would it replace or augment human capabilities? In the last few months, I have been thinking a lot about how AI will impact our future as individuals, as designers and society. A very simple way to examine if AI algorithms will displace designers (or any profession) is to understand the degree to which that occupation can be easily codified or reduced to a set of reliable patterns, steps or models.

Welcome to today's channel rundown, containing vital news and analysis on the channel's comings and goings. Distributor Tech Data said it will offer Windows 10 Enterprise E3 as a subscription for cloud service providers (CSPs) to sell to SMBs. The distributor said it will offer the automated service, which provides enterprise-grade security and management capabilities, to its solution providers in the Americas and Europe through the Tech Data Cloud Solutions Store. Windows 10 Enterprise E3 features the complete stack of Microsoft's CSP cloud solutions, including Windows 10 Enterprise, Office 365, Enterprise Mobility Suite, Azure and Dynamics Customer Relationship Management Online as a pay-as-you-go, partner-delivered managed service. Kaspersky has rolled out Kaspersky Endpoint Security Cloud, a new SaaS-based solution that aims to provide SMBs with multi-layered IT security.

A major topic of discussion in the tech world is Artificial Intelligence, or AI as some call it. Self-learning systems have been adopted in various fields, ranging from self-driving cars to robotics. Google, the world's most popular search engine has now integrated its own machine learning system as a part of its search algorithm. Google feels that a self-learning system holds the key to handling search queries of the future with greater accuracy. Google's AI system is called RankBrain and it was launched back in October 2015.

The UC Berkeley-led center, directed by artificial intelligence researcher Stuart Russell, will seek to understand how human values can be built into AI's design, and create a mathematical framework that will help people build AI systems that are beneficial to humanity. Scientists might get around this communication problem by designing artificial intelligence that can watch humans and learn what their values are through their actions (though even that comes with some uncertainty, as humans don't always act in ways aligned with their values, Russell added). The USC center, co-directed by artificial intelligence researcher Milind Tambe and social work scientist Eric Rice, seems to operate in a mindset perpendicular to the one at UC Berkeley: It seeks to harness AI's existing capabilities to solve problems in messy, complicated human contexts. AI also includes a wide range of tools, including machine learning, computer vision, natural language processing and game theory (though some may consider game theory part of another discipline, Tambe said).