The combination of software-defined networking and machine learning/artificial intelligence is becoming a powerful tool for making networks more reliable and secure. And while not everyone is willing to talk about their activities yet -- CenturyLink Inc. (NYSE: CTL) and Verizon Communications Inc. (NYSE: VZ) declined interview requests on this topic -- a peek inside what is happening at AT&T Inc. (NYSE: T) and Level 3 Communications Inc. (NYSE: LVLT) offers a clear view of what's possible. In this first of two stories, executives at those companies share how machine learning and AI are being built into their networks today. As Mazin Gilbert, AVP of Intelligent Services at AT&T Labs, explains, artificial intelligence and machine learning are hardly new concepts, nor is the idea of using these tools to improve network performance and security. There was talk about that as far back as the 1980s, he says.

Mark Zuckerberg say he's created an AI that controls his smart house Zuckerberg may debut'Jarvis' AI assistant next month

Kawasaki announced it is working on an artificial intelligence system that would allow a motorcycle to communicate with, and adapt to its rider. The AI would be able to converse with a rider and, using cloud computing and a motorcycle's electronics, adapt the bike's settings to the rider's needs and skills. The AI wouldn't just allow a motorcycle to talk to a rider; Kawasaki says the AI will use a technology called an "Emotion Engine" to interpret a rider's emotions and perhaps even develop its own personality. Kawasaki says the AI will allow a motorcycle to converse (??) with its rider while processing data from the internet (???????) and vehicle information (????). While this may sound like science fiction, the Emotion Engine is already being used in the real world.

UC Berkeley artificial intelligence (AI) expert Stuart Russell will lead a new Center for Human-Compatible Artificial Intelligence, launched this week. BRETT, the Berkeley Robot for the Elimination of Tedious Tasks, ties a knot after watching others demonstrate it. Russell, a UC Berkeley professor of electrical engineering and computer sciences and the Smith-Zadeh Professor in Engineering, is co-author of Artificial Intelligence: A Modern Approach, which is considered the standard text in the field of artificial intelligence, and has been an advocate for incorporating human values into the design of AI. The primary focus of the new center is to ensure that AI systems are beneficial to humans, he said. The co-principal investigators for the new center include computer scientists Pieter Abbeel and Anca Dragan and cognitive scientist Tom Griffiths, all from UC Berkeley; computer scientists Bart Selman and Joseph Halpern, from Cornell University; and AI experts Michael Wellman and Satinder Singh Baveja, from the University of Michigan.

Mark Zuckerberg say he's created an AI that controls his smart house Zuckerberg may debut'Jarvis' AI assistant next month

The author is a Silicon Valley based IIoT industry analyst & co-founder of ArcInsight Research Partners, a research & advisory group. He has also trained with business strategy consulting firms, with additional qualifications in decision analytics, Bayesian-learning approaches & risk-assessment. I wrote about GE's Predix Platform last year in the context of its immensely successful Minds Machines Conferences where the company showcased a very compelling story about its quiet but steady transformation into a digital industrial company. This is a far cry from creating avatars in a consumer or mobile context. Industrial stakes are very high.

We are a group of researchers who study, analyze, and build different aspects of social systems (e.g. By understanding and measuring complex networks, we try and build solutions for social good. Our work primarily derives from Data Science, Computational Social Science, Social Computing, Machine Learning, and Natural Language Processing.

Have you ever wondered whether you should be applying Machine Learning in Insurance Pricing? According to Gartner, Machine Learning is one of the hottest technology trends of 2016 and is revolutionising the way many companies do business. In this blog post I take a look at machine learning from an insurance pricing stand point, highlighting the advantages and challenges of applying machine learning in insurance pricing. In order to help you get started I also provide free R code, so you can try these exciting algorithms on your own insurance data. Machine Learning has gained in popularity in recent years - but wait... isn't Machine Learning just Statistical Modelling!? Lets start with some definitions: Clearly then there are similarities between supervised learning and statistical modelling.

As more cyber- threats arise every day, extensive research into prevention and detection schemes is being conducted globally. One of the issues faced is keeping up with the sheer mass of new emerging threats online. Traditional detection schemes are rule or signature based. The creation of a rule or signature relies on prior knowledge of the threats structure, source and operation, making it impossible to stop new threats without prior knowledge. Manually identifying all new and disguised threats is too time-consuming to be humanly possible.

Two London trusts have become the first in UK to establish data sharing between their Cerner Health Information Exchanges, covering a population of 1.3 million people. Homerton University Hospital NHS Foundation Trust and Barts Health NHS Trust went live on with the connection 12 July, with clinicians in both acute hospitals able to view a summarised care record from the other site. The visible information for each trust includes discharge summaries, diagnosis, medications, investigations and results. Niall Canavan, Homerton Hospital's director of information technology, said the next step was "to open this data to any contributing partner organisation in east London". Charles Gutteridge, Barts' chief clinical information officer, said the move had been "relatively simple to do, as Homerton also used the Cerner Millennium system, but a really big step forward".