There has been a dramatic increase in work in the last five or six years, coming from the exponential data explosion and an increase in audit regulation bureaucracy,

This article originally appeared on the International Business Times. Machines are capable of understanding speech, recognizing faces and driving cars safely, making recent technological advancements seem impressively powerful. But if the field of artificial intelligence is going to make the transformative leap into building human-like machines, it'll first have to master the way babies learn. "Relatively recently in AI there's been a shift from thinking about designing systems that can do the sort of things that adults can do, to realizing if you want to have systems that are as flexible and powerful and do the kinds of things that adults do, you need to have systems that can learn the way babies and children do," developmental psychologist Alison Gopnik, a researcher at the University of California at Berkeley, told International Business Times. "If you compare what computers can do now to what they could do 10 years ago, they've certainly made a lot of progress, but if you compare them to what a 4-year-old can do, there's still a pretty enormous gap."

The hottest ticket in tech is an invitation to a banal South Florida business park, indistinguishable on the outside from countless other office buildings that dot America's suburban landscape. Humanoid robots walk down the halls, and green reptilian monsters hang out in the lounge. Cartoon fairies turn the lights on and off. Even the office equipment does the impossible. The high-definition television hanging on the wall seems perfectly normal. Incredibly, it is now levitating in midair. Get as close as you'd like, check it out from different angles.

In an industry known for its love of buzzwords and hype, artificial intelligence (AI) has become marketing's new'big data'. But where big data ultimately led to new layers of complexity, AI promises the opposite. Big data forced marketers to become data scientists (or hire them, if they could be found), but AI holds out the hope that marketers may get to go back to doing what they signed up for the in the first place. Recent months have seen technology providers such as Salesforce, Oracle and Microsoft bring new AI-based technologies to market, promising to derive insights and improve conversions by mimicking the processes of the human brain in software. Salesforce, for example, is rolling out its Einstein AI technology to provide functions such as product recommendations within the Commerce Cloud, email content recommendations within its Marketing Cloud, and predictive forecasting tools for sales managers with its Sales Cloud.

Facial recognition software is most commonly known as a tool to help police identify a suspected criminal by using machine learning algorithms to analyze his or her face against a database of thousands or millions of other faces. The larger the database, with a greater variety of facial features, the smarter and more successful the software becomes – effectively learning from its mistakes to improve its accuracy. Now, this type of artificial intelligence is starting to be used in fighting a specific but pervasive type of crime – illegal fishing. Rather than picking out faces, the software tracks the movement of fishing boats to root out illegal behavior. And soon, using a twist on facial recognition, it may be able to recognize when a boat's haul includes endangered and protected fish.

ORLANDO, Fla., October 18, 2016 View All Press Releases Gartner Reveals Top Predictions for IT Organizations and Users in 2017 and Beyond Analysts Explore the Digital Future at Gartner Symposium/ITxpo 2016, October 16-20 in Orlando Gartner, Inc. today revealed its top predictions for 2017 and beyond. Gartner's top predictions for 2017 examine three fundamental effects of continued digital innovation: experience and engagement, business innovation, and the secondary effects that result from increased digital capabilities. "Gartner's top strategic predictions continue to offer a provocative look at what might happen in some of the most critical areas of technology evolution. At the core of future outcomes is the notion of digital disruption, which has moved from an infrequent inconvenience to a consistent stream of change that is redefining markets and entire industries," said Daryl Plummer, managing vice president, chief of research and Gartner Fellow. "Last year, we said digital changes were coming fast. This year the acceleration continues and may cause secondary effects that have wide-ranging impact on people and technology."

Neil Prakash, an Australian recruiter for the Islamic State group (also called ISIS), was arrested somewhere in the Middle East after surviving drone attacks by the FBI, the New York Times reported Thursday. The 25-year-old, who was linked to militant plots in Australia and had appeared in several ISIS propaganda videos, was believed killed in a U.S. airstrike in Iraq in April. According to the Times, which cited an unnamed senior American military official, Prakash was wounded in an airstrike earlier this year but survived. Another senior U.S. military official reportedly said the former Melbourne resident was arrested some time in the last few weeks by an unidentified Middle Eastern government. Prakash, who converted to Islam from Buddhism and took the name Abu Khaled al-Cambodi, left Australia in 2013 and has been recruiting fighters for ISIS since then.

Deep Learning is a new area of Machine Learning research that has been gaining significant media interest owing to the role it is playing in artificial intelligence applications like image recognition, self-driving cars and most recently the AlphaGo vs. Lee Sedol matches. Recently, Deep Learning techniques have become popular in solving traditional Natural Language Processing problems like Sentiment Analysis. For those of you that are new to the topic of Deep Learning, we have put together a list of ten common terms and concepts explained in simple English, which will hopefully make them a bit easier to understand. We've done the same in the past for Machine Learning and NLP terms, which you might also find interesting. In the human brain, a neuron is a cell that processes and transmits information.

In an industry known for its love of buzzwords and hype, artificial intelligence (AI) has become marketing's new'big data'. But where big data ultimately led to new layers of complexity, AI promises the opposite. Big data forced marketers to become data scientists (or hire them, if they could be found), but AI holds out the hope that marketers may get to go back to doing what they signed up for the in the first place. Recent months have seen technology providers such as Salesforce, Oracle and Microsoft bring new AI-based technologies to market, promising to derive insights and improve conversions by mimicking the processes of the human brain in software. Salesforce, for example, is rolling out its Einstein AI technology to provide functions such as product recommendations within the Commerce Cloud, email content recommendations within its Marketing Cloud, and predictive forecasting tools for sales managers with its Sales Cloud.

Dugong expert Dr Amanda Hodgson estimates she has stared at more than 30,000 photographs of blue water. "It's really taxing on your eyes and it's hard to maintain concentration." The researcher from WA's Murdoch University has been scanning pictures captured by aerial drones in a search for dugongs, to work out their population, size and location. Globally dugongs are classed as "vulnerable to extinction" and are found in waters off the northern half of Australia. "There are areas where they're quite vulnerable because their habitat overlaps with coastal development."