For the latest information, please visit: http://www.wolfram.com Speaker: Anton Antonov Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, and more.

Massimiliano "Max" Versace traces the birth date of his startup to when NASA came knocking in 2010. The U.S. space agency had caught wind of his military-funded Boston University research on making software for a brain-inspired microprocessor through an IEEE Spectrum article, and wanted to see if Versace and his colleagues could help develop a software controller for robotic rovers that could autonomously explore Mars. NASA's vision proved no easy challenge. Mars rovers have limited computing, communications, and power resources. NASA engineers wanted artificial intelligence that could rely solely on images from a low-end camera to navigate different environments.

The combination of machine learning, deep learning, natural language processing, and cognitive computing will change the ways that humans and machines interact with our environments. AI-driven smart services will sense one's surroundings, know one's preferences are from past behavior, and subtly guide people and machines through their daily lives in ways that will truly feel seamless. This quest to deliver AI driven smart services across all industries and business processes will usher the most significant shift in computing and business this decade and beyond. Organizations can expect AI driven smart services to impact future of work flows, IOT services, customer experience journeys, and block chain distributed ledgers. Success requires the establishment of AI outcomes (see Figure 1).

Try typing "the machines" into Google and chances are that one of the top results the artificial intelligence-powered search engine will return is the phrase: "The Machines are Coming". After a 2016 filled with high-profile advances in artificial intelligence (AI), leading technologists say this could be a breakout year in the development of intelligent machines that emulate humans. Asia, until now lagging Silicon Valley in AI, will play a bigger role as the field cements itself at the pinnacle of the technology world in 2017, the experts say. AI – technically, a computing field that involves the analysis of large troves of data to predict outcomes and patterns – is as old as modern computers but its esoteric nature means it has long endured caricatures of its actual potential – think for example, the 1960s space age cartoon The Jetsons, which featured a sentient robot maid and automated flying cars (both of which we are still waiting for, even 50 years on). Now, a confluence of factors has given rise to hopes that computers with human-like cognitive ability may soon be a reality.

Computers can already hold a massive amount of instantly retrievable data in a manner that puts most humans to shame, but getting them to actually display intelligence is an entirely different challenge. A team of researchers from Northwestern University just made a huge stride toward that goal with a computational model that actually outperforms the average American adult in a standard intelligence test. Don't miss: Apple new 2017 iPad models reportedly have been delayed As PhysOrg reports, the witty computer system utilizes an AI platform called CogSketch that gives it the power to solve visual problems just by looking at them, which is something that has traditionally held back many examples of artificial intelligence. Being able to visually understand, interpret, and then use that data to come to a solution brings the computer system closer to the functioning of the human brain than many before it, and so the team pitted its creation against a popular standardized test called Raven's Progressive Matrices. The Raven's test (or RPM for short) is composed of 60 multiple-choice questions that measure the taker's ability to reason, using visual puzzles.

When Facebook (NASDAQ:FB) suggests you "tag" a friend in a photo, it generally suggests that friend's name. That small interaction provides a glimpse into the world of an emerging and powerful aspect of artificial intelligence (AI) in action -- image recognition. With its treasure trove of words and pictures from 1.79 billion monthly active users, it is using that data, combined with recent advancements in AI, to propel this and other technological advances. Facebook may well have the lead in facial recognition, even extending a step further into the realm of facial verification. It released a research paper in 2014 in which it reported 97.35% accuracy, which approaches human levels of recognition.

Google Brain researchers are looking for ways to soon put forth a software that will be creating machine learning software as well. There's a relevant reason why researchers are getting their heads on this. A lot of money is still needed to hire experts who can work with it. What's more is that building an AI still requires a significant amount of time and effort to develop AIs using machine-learning. Relieving some of that stressful work to other machine learning systems could greatly cut the human input that needs to be dedicated to the entire process.

Machine learning (ML) methods have been around for ages, but the big-data revolution and the plummeting cost of computing power are now making them truly excellent and practical analytical tools in banking across a variety of use cases, including credit risk. ML algorithms may sound complex and futuristic, but the way they work is quite simple. Essentially they combine a massive set of decision trees (i.e., a decision-making model that breaks out individual decisions and possible consequences, also known as "learners") to create an accurate model. By churning through these learners at high speeds, ML models are able to find "hidden" patterns, particularly in unstructured data that common statistical tools miss. Overfitting (the analytical description of random errors rather than underlying relationships) of the model is a typical concern about ML.

TechEmergence is an artificial intelligence market research firm. We help companies and institutions gain insight on the applications and implications of AI and machine learning technologies. Our insights have been featured and referenced in some of the world's most respected publications, including:

Arccos Golf announced Thursday that Microsoft will be its official cloud partner in an initiative that will see the two companies develop technologies that use advanced analytics to deliver insights to help golfers of all skill levels. The Arccos Course Analyzer will debut Jan. 24 at the PGA Show in Orlando as a platform that layers an Arccos user's data on top of millions of data points for more than 40,000 golf courses mapped in the Arccos system. It uses Microsoft Azure's cloud-computing services and machine learning capabilities to provide personalized recommendations for strategies on nearly every golf hole in the world. "Our goal is to create the most advanced Artificial Intelligence platform for golf," Arccos CEO and co-founder Sal Syed said in a statement. "It will leverage a user's personal performance history, all the shots ever taken by the Arccos community, weather, elevation, course features, equipment selections and much more. The resulting strategic advice will be smarter than anything that's humanly possible. With its broad suite of capabilities, Microsoft's Azure cloud platform is the ideal solution to unlock this vision."