In my 25 years of working with large datasets, from developing early machine learning algorithms for multimedia systems in the 1990s to optimizing the email marketing infrastructure at GSI Commerce in the 2000s and now applying machine learning to big data to find actionable insights in real time, I've seen the convergence of machine learning and marketing firsthand. This year, I'm excited to see how machine learning (ML), an artificial intelligence (AI) discipline geared toward the technological development of human knowledge, has impacted the marketing big data ecosystem. I'm also intrigued by how much room I see for growth in the future. Machine learning techniques are being used to solve many diverse problems, and we stand to benefit as we move towards a world of hyper-converged data, channels, content, and context -- having the right conversation at the right time with the right person in the right way. For us marketers, ML is about finding nuggets of "predictive" knowledge in the waves of structured and unstructured data.

Nice and steady does it. A video analysis system uses motion tracking and machine learning to assess how good surgeons are at suturing a wound. "Different surgeons all have different styles of suturing," says Aneeq Zia at the Georgia Institute of Technology in Atlanta, whose team developed the system. The team first captured footage of 41 surgeons and nurses practising their suturing and knot-tying skills on foam boards. Participants also wore an accelerometer on each hand to capture motion data, and a clinician then watched the videos and rated each person's skills.

The Premier League has obtained a new court order to block illegal streams fed to Internet Protocol TV (IPTV) boxes running Kodi. It means that internet service providers (ISPs) including Sky, BT, Virgin Media and TalkTalk will have to block customers' access to streams provided by third-party add-ons on Kodi at the request of the Premier League. This can also be done mid-game, according to a report in Bloomberg. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar. Japan's On-Art Corp's CEO Kazuya Kanemaru poses with his company's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' and other robots during a demonstration in Tokyo, Japan Japan's On-Art Corp's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' performs during its unveiling in Tokyo, Japan Singulato Motors co-founder and CEO Shen Haiyin poses in his company's concept car Tigercar P0 at a workshop in Beijing, China A picture shows Singulato Motors' concept car Tigercar P0 at a workshop in Beijing, China Connected company president Shigeki Tomoyama addresses a press briefing as he elaborates on Toyota's "connected strategy" in Tokyo.

I can highly recommend Deep Learning: A Practioner's Approach. From a preview of this, it's extremely well-written and easy to follow -- and includes lots of code examples. It is by the brilliant minds of the Deep Learning 4J people. Tutorials of Keras: This could be the Rosetta Stone, or at least the Apache Beam, of DL. Autopilot: TensorFlow: This is some great code to try and learn from.

Earlier this year, I predicted 2015 will be the year artificial intelligence enters the conversation for customer service. Two months into the year, we already see this becoming a reality for businesses today. For instance, Deloitte Consulting has recently shared best practices on how to evaluate what artificial intelligence can do for your business, including how cognitive technologies can help generate insights that can reduce costs, improve efficiency or enhance customer service. At the same time, brand experts are writing about how robots are improving customer service and creating new branding channels for organizations. Finally, just last week, my colleague wrote about how artificial intelligence can actually bring the humanity back to customer service – creating a more engaging and personal customer experience that customers will actually love.

Artificial Intelligence offers a lot of advantages for organisations by creating better and more efficient organisations, improving customer services with conversational AI and reducing a wide variety of risks in different industries. Although we are only at the beginning of the AI revolution that is upon us, we can already see that artificial intelligence will have a profound effect on our lives. As a result, AI governance and Explainable AI are becoming increasingly important, if we want to reap the benefits of artificial intelligence. Data governance and ethics have always been important and a few years ago, I developed ethical guidelines for organisations to follow, if they want to get started with big data. Such ethical guidelines are becoming more important, especially now since algorithms are taking over more and more decisions.

Planning to Netflix and chill this weekend? The movie you choose to watch may be heavily influenced by Netflix's sophisticated algorithms. Similarly, decisions like where you choose to dine and what you choose to wear are increasingly facilitated by predictive technologies powered by deep learning. Here are five ways that popular consumer tech companies Netflix, Yelp, Yahoo, StitchFix, and Google improve your online experience with artificial intelligence. Historically, watching television is a unidirectional communication channel.

There is a gaping hole in the digital defences that companies use to keep out cyber thieves. The hole is the global shortage of skilled staff that keeps security hardware running, analyses threats and kicks out intruders. Currently, the global security industry is lacking about one million trained workers, suggests research by ISC2 - the industry body for security professionals. The deficit looks set to grow to 1.8 million within five years, it believes. The shortfall is widely recognised and gives rise to other problems, says Ian Glover, head of Crest - the UK body that certifies the skills of ethical hackers.

To some Artificial Intelligence (AI) may seem like a solely sci-fi concept, but in truth it is already becoming reality in ways we may not realise, with its application within the facilities management function already in use. Aside from virtual assistants like Apple's Siri and Microsoft's Cortana, which have already pervaded our day-to-day lives, other forms of AI are steadily making inroads into all sectors, and FM is no exception. Whether it is the use of smart floor sweepers or robot receptionists, AI is one fast-evolving concept that a growing number believe has the potential to not only overhaul the FM industry but the entire professional environment. According to our recent Twitter poll on the subject, just over half of respondents believe that AI is an opportunity to increase their organisation's profit margins. Does this indicate that some in the FM sector already see the potential to save money on staffing costs as robots and machines take over more manual FM services as some of the more sensationalist headlines suggest?

Last year, Swedbank in Sweden "hired" Nina, a dynamo of a company rep. Nina is adept at interacting with customers on the bank's website, answering their questions and routing them to the right human representative. She typically engages in some 45,000 conversations a month and successfully answers eight out of 10 inquiries. Not only can Nina understand and mimic human speech, she can also use data to make connections and recommendations. "Nina's brain for Swedbank is educated on all things Swedbank," says Robert Weideman, EVP and GM of the enterprise division at Nuance Communications, which created Nina.