Machine learning is the process of building analytical models to automatically discover previously unknown patterns from data that indicate associations, sequences, anomalies (outliers), classifications, and clusters and segments. These patterns reveal hidden rules as to why an event happened--for example, rules that predict likely customer churn. The widely used Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is used to develop predictive analytical models. CRISP-DM includes six phases: business understanding, data understanding, data preparation, model development using supervised and unsupervised learning, model evaluation and model deployment. The business understanding phase involves defining the business problem or use case, the business objectives and the business questions that need to be answered.

When investors think of artificial intelligence stocks, Microsoft Corporation (NASDAQ:MSFT) isn't usually the first name that comes to mind. Inc. (NASDAQ:AMZN) as the leader in at-home AI, due to the success of the company's Echo device, while "Watson" from International Business Machines Corp. (NYSE:IBM) is arguably the top turn-key artificial intelligence solution for enterprise-level entities. Those investors who believe AI is the future, however, may want to put MSFT stock back on their radar as a way to play the movement. The software giant's recent acquisition of Maluuba speaks volumes about its artificial intelligence ambitions and what it actually wants to "do" with it. Maluuba isn't a household name, but within artificial intelligence circles (and these are VP of AI Research Harry Shum's words), "Maluuba's vision is to advance toward a more general artificial intelligence by creating literate machines that can think, reason and communicate like humans – a vision exactly in line with ours."

Banks are already experimenting with robotic process automation in areas like their compliance functions. But robotics technology may soon find its way to nearly all aspects of running the bank. As banks become more comfortable with the relying on software robots to replicate the actions of a human interacting with machines to handle rote tasks, experts say they will be quick to deploy the technology companywide as a way to trim expenses and redirect employees to more crucial tasks. "I think we're going to see it move from a few narrow functions to across the enterprise," said Alan McIntyre, the industry managing director for banking at Accenture. "It's going to become an indispensable technology for banks, rather than an interesting experiment."

Oren Boiman, CEO and co-founder of Magisto talks about how as marketers, we need innovation in digital video. Mass consumer adoption of video is forcing us to overcome the challenges of a fragmented audience and learn to manage risk. The field of video marketing is a particularly hot topic right now. Marketing innovation is being driven by mass consumer adoption of digital video in a myriad of shapes and sizes. In the broadest terms, the marketing trade is behind the curve and eager to fill the gap and find audiences beyond our reach. One of the challenges of finding and speaking to a fragmented audience is creating marketing video content with agility, scale and with a voice.

Deals to AI startups reached a record high last year, from 160 deals in 2012 to 658 in 2016. Although non-US deal share has been increasing over the time period, well over a majority of deals, around 70%, went to startups in the US in the last 5 years. The top 3 states for deals were California (51%), New York (11%), and Massachusetts (9%). Using the CB Insights database, we mapped the most well-funded AI startups in each of the 35 states where there have been equity deals to an AI company in the last five years. The map only includes companies that have not exited and only includes equity financing.

Mark Carney, the Bank of England Governor's, recent "Robots to steal 15 million jobs" warning is closely followed by a Japanese life insurer announcing that they are replacing 34 staff with robots to improve productivity by 30% and save just under £1m a year in salaries. In this instance the robots are an artificial intelligence (AI) system described as'cognitive technology that can think like a human'. It is capable of reading medical certificates and gathering data to calculate claim payments and when you also hear that an American insurer is already using AI and boasting of paying a claim for a stolen mobile phone in 3 seconds using their system known as'AI Jim', the attraction to insurers is obvious. To some, a'robot revolution' will just be another technological advancement, albeit one of significance to compare with the industrial revolution or the internet. To others it may be a very worrying radical change with the potential for global transformation, both socially and economically.

Shivaram Kalyanakrishnan is an assistant professor in the department of computer science and engineering at the Indian Institute of Technology-Bombay. He specialises in artificial intelligence (AI) and is the only author from India who is part of an 18-member study panel of the Stanford University-hosted report titled Artificial Intelligence and Life. Kalyanakrishnan's expertise broadly fits in the area of machine learning. Called reinforcement learning, it defines what actions software agents should take to maximize a certain type of reward after learning from reward and punishment. In an interview, he urges people to be more optimistic about the things AI can do rather than be obsessed with the fear around AI machines.

In a year of uncertainty and unpredictability, change strangely remained our only constant in 2016. Against a backdrop of unexpected political events – the outcome of the Brexit referendum, the election of Donald Trump and the Italy constitutional reform vote, for example – and an unsettled global economy, technological innovation has been developing at a dizzying pace. Nowhere has this been more notable than in the retail sector. Customer demand for convenience is driving change. Our Unfaithful Consumer research found that 55 percent of consumers see it as the most important factor when it comes to deciding where, and how, to shop. With the help of truly disruptive new technology, the focus in 2016 was on making the entire shopping experience more convenient for the consumer.

Economists worry that artificial intelligence (AI) could make many workers obsolete. Now, AI researchers could be putting their own jobs at risk. Researchers at Google and elsewhere are writing AI software that's better than humans at writing AI software, reports Light Reading (Banking Technology's sister publication). Researchers at the Google Brain artificial intelligence research group tasked software with designing a machine-learning system to take a test that benchmarks language-processing software. The software-written software beat previously published results for software designed by humans, according to a report this week on the MIT Technology Review.

The notion of a technological singularity brought about by advances in Artificial Intelligence (AI) has entertained academics, inventors, futurists, and journalists since the concept was first coined around the middle of the last century. The singularity posits that, at some point in the near or distant future, we humans will create AI that outsmarts us, leading to all sorts of unhappy results for our kind. Depending on whether you prefer utopian or dystopian science fiction, the singularity will either be absolutely fabulous or downright horrifying. Mathemetician and science-fiction writer Vernor Vinge is thought to have coined the term "the singularity." Vinge's view in this 1993 essay is decidedly dystopian: "Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended."