THE RISE OF ARTIFICIAL intelligence has inspired both fascination and fear of the world to come. Some tech prophets envision a "singularity," in which advances in AI trigger drastic technological growth, while others imagine that autonomous machines will someday turn on their creators and destroy us. But when you're engaged in the science of machine intelligence, you understand that this is a false set of choices shaped by a misleading phrase. The term "artificial intelligence" was coined in 1955 to convey the concept of general intelligence: the notion that all human cognition stems from one or more underlying algorithms, and that by programming computers to think in the same way, we could create autonomous systems modeled on the human brain. At the same time, other researchers were taking a different approach.

MasterCard (MA) is taking payments, the last -- and sometimes, the most painful -- part of shopping into the future, replacing card swipes with robots, artificial intelligence and the ubiquitous selfie. The steps, including this week's introduction of a chatbot for banks called "MasterCard KAI" that uses artificial intelligence to respond to customer queries via texts or through apps like Facebook Messenger, are vital parts of CEO Ajay Banga's strategy of leverage technological development to expand the $113 billion company beyond traditional card-based transactions. To create the chatbot, MasterCard partnered with startup Kasisto, developing a "conversational artificial intelligence platform" that banks and merchants can use to let customers make transactions, monitor their spending habits, check account balances and ask questions, the company said at the Money 20/20 conference in Las Vegas. It will be released in the U.S. early next year. "This bot enables entirely new experiences, bringing Mastercard benefits and offers to consumers with human-like conversations that are personal and contextual," Zor Gorelov, Kasisto CEO and co-founder, said in a statement.

We have discussed some AI topics in the previous posts, and it should seem now obvious the extraordinary disruptive impact AI had over the past few years. However, what everyone is now thinking of is where AI will be in five years time. I find it useful then to describe a few emerging trends we start seeing today, as well as make few predictions around machine learning future developments. The following proposed list does not want to be either exhaustive or truth-in-stone, but it comes from a series of personal considerations that might be useful when thinking about the impact of AI on our world. Companies like Vicarious or Geometric Intelligence are working toward reducing the data burden needed to train neural networks.

A team of computer scientists and legal professionals has created artificial intelligence with the ability to accurately predict the outcome of 79 percent of cases decided upon by the European Court of Human Rights. The performance of the artificial intelligence was published Monday by PeerJ Computer Science. Text from European Court of Human Rights cases was used to train a machine learning algorithm to find patterns in case text. The predictive model is made possible by advancements in natural language processing and machine learning, the analysis said. "We don't see AI replacing judges or lawyers, but we think they'd find it useful for rapidly identifying patterns in cases that lead to certain outcomes. It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights," said lead scientist Nikolaos Aletras in a statement by University College London.

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Ben Dickson is a software engineer and the founder of TechTalks. While machine learning is introducing innovation and change to many sectors, it also is bringing trouble and worries to others. One of the most worrying aspects of emerging machine learning technologies is their invasiveness on user privacy. From rooting out your intimate and embarrassing secrets to imitating you, machine learning is making it hard to not only hide your identity but also keep ownership of it and prevent from being attributed to you words you haven't uttered and actions you haven't taken. Here are some of the technologies that might have been created with good-natured intent, but can also be used for evil deeds when put into the wrong hands.

She heads HR for one of the largest banks and now has a difficult mandate to execute. She has had to shut down a branch in a small city because that branch is no longer profitable. Many of the jobs in the bank that were once being done by humans have been handed over to robots or "bots" as they are called. "Is Artificial Intelligence a job killer", I ask her. "The bots have been programmed in-house in our innovation lab. The innovation lab has added jobs."

The company's scientists think its new AI-based factotum will be the biggest thing since search. It is the day after Google's big hardware event in San Francisco, when the company formally unveiled a new phone (a jab to the iPhone) and a voice-activated speaker (a gut punch to Amazon's Echo). Word of mouth is already tracking positive; a countdown to ecstasy, in the form of upcoming rhapsodic reviews of the Pixel phone, has already begin. But in a conference room on the company's sprawling Mountain View campus, Fernando Pereira, who leads Google's projects in natural language understanding, is less excited about his company's shiny new devices than he is about what will happen when people use them. "Let me tell you a little bit about The Transition," he says.

A CNN Money report found that Americans paid more than $6 billion in overdraft fees in 2013 to the top three banks alone. A CNN Money report found that Americans paid more than $6 billion in overdraft fees in 2013 to the top three banks alone. Ahead of their official presentation at the Money 20/20 FinTech conference in Las Vegas, Change Labs has announced the launch of their platform and savings product, along with their latest pilot service that they are calling Predictive Overdraft Protection . Co-founded in 2015 by CEO Yaniv Levi, Head of Product Assaf Priel, and CTO Dmitri Chebotarev, Change Labs is on a mission to reshape the way that people behave with their money. So far the company has succeeded in raising $1.3 million in seed capital to reach their alpha testing round from various unidentified backers.

When Apple released its software application, Siri, in 2011, iPhone users had high expectations for their intelligent personal assistants. Yet despite its impressive and growing capabilities, Siri often makes mistakes. The software's imperfections highlight the clear limitations of current AI: today's machine intelligence can't understand the varied and changing needs and preferences of human life. However, as artificial intelligence advances, experts believe that intelligent machines will eventually – and probably soon – understand the world better than humans. While it might be easy to understand how or why Siri makes a mistake, figuring out why a superintelligent AI made the decision it did will be much more challenging.