Robots can paint, but when it comes to writing, they shouldn't quit their day jobs. That's the combined conclusion from results of two contests announced this week. On the upside, artificial intelligence created some pretty impressive works for RobotArt.org's The contest challenged artists and engineers to create a robot that painted like a real artist. Essentially, the aim was to get "as many teams as possible to set up a robot that can do any sort of painting," the contest site explains.

Grace Peters recently wrote in HPCwire, "Thanks to machine learning, the page you see when you log-on to Amazon.com is likely very different from the one I see. Advertising, product recommendations, and special deals are all tailored to our unique customer profiles based on historical browsing trends and buying behavior. Online retailers like Amazon were among the first users of customer data collection and analysis for improving services and personalizing the shopping experience, and they've become so skilled some sites might even be able to predict what we will purchase before we even know what we're looking for." Peters goes on, "Advancements in digital technologies have driven a paradigm shift in the way businesses interact with their customers, with touchpoints increasingly moving to digital mediums. Because of the limited opportunities to satisfy customers on a person-to-person level, machine learning is now in widespread use by a variety of modern enterprises as a way to enrich customer experiences, create more personalized and customer-centric interactions, and offer seamless omnichannel communications."

Alphabet Inc.'s (NASDAQ:GOOG) Google is reputed as having one of the most intelligent artificial intelligence infrastructure globally. Its wide reach via its Chrome browser and Android mobile operating system means its influence runs deep. The main issue is whether the company can really find the right mix to convert these enviable advantages into the next in-demand product. This is the question most attendees at the company's annual I/O developer conference. This question was partly answered by Google CEO Sundar Pichai.

If yesterday's Google I/O keynote was anything to go by, it's abundantly clear that Artificial Intelligence is here to stay. Many of the mobile apps and services we use each day already have some level of AI powering their internals, but these days it's become so seamless that we hardly ever notice. I frankly don't talk to my phone too often, but when I do--from asking Google Now to ask for information about the new city I've landed in, to querying Google Photos to show me all photos of my daughter laughing, it's fascinating (and sometimes scary) to see these tools in surprisingly accurate action. Many of these advancements are thanks to rapid developments in the fields of machine learning and artificial intelligence, developments that now enable computing devices to understand our voice, or recognize features in photos. Coupled with cloud-based services and cellular connectivity, all of this'intelligence' is suddenly available to billions of smartphones, from mega-metropolises to humble villages.

You might ask what the difference is between most artificial intelligence (AI) companies and SparkCognition. Here it is: while at other firms, humans build models; SparkCognition puts them together with algorithms. Rather than roughing out one model and then doing a bunch of testing, SparkCognition continually tests and fits models to data accumulating in real time, an architecture that allows it to deal with big data. Without foregone conclusions about what might be happening, SparkCognition algorithms keep probing for relationships and possible explanations without any a priori idea of what's going on. This fantastic flexibility, along with the speed of computer technology, allows SparkCognition to come to conclusions fast enough for real-time intervention.

Artificial intelligence has been around since 1956 and has made some giant leaps in that time: beating the best human at chess, the best human at US gameshow Jeopardy and recently beating the best human at complex strategy game Go. Brands have only recently started adopting artificial intelligence for core consumer services. Google's voice recognition technology now claims 98% accuracy and Facebook's DeepFace is said to recognise faces with a 97% success rate. IBM's Watson, which uses artificial intelligence to perform its question-answering function, is 2,400% "smarter" today than when it achieved the Jeopardy victory five years ago. There is no doubt that the relationship between men and machines is changing, and brands are on the cusp of making artificial intelligence an everyday element of their customer offerings.

If you control the code, you control the world,

DeepMind acquired startup by Google for 500M established a new collaboration with University of Oxford. The news is announced by Demis Hassabis, co-founder of DeepMind and VP of engineering at Google from a blog-post [1]. Deep learning researchers Prof Nando de Freitas, Prof Phil Blunsom, Dr Edward Grefenstette and Dr Karl Moritz Hermann, from University of Oxford, who teamed up earlier this year to co-found Dark Blue Labs, are hired by DeepMind. Also Dr Karen Simonyan, Max Jaderberg and Prof Andrew Zisserman, one of the world's foremost experts on computer vision systems, and they recently have a start-up called Vision Factory will join DeepMind from University of Oxford[1,2]. The three professors hired by DeepMind are holding joint appointments at Oxford University where they will continue to spend part of their time.

Thanks to a new deep learning system from Yahoo! Research, GIFs are just one more art form--in addition to poetry and calligraphy, to name a few--that computers are quickly mastering. A computer made that all on its own. In fact, not only did a computer make the above GIF, it actually scanned the original video and decided which bits had the highest GIF potential; a video went in, and a slew of appealing GIFs came out. We're on our way to what you could call a fully automated, bean-to-bar, GIF-making solution. Research in New York do, you could call it Video2GIF.

College of Computing Professor Ashok Goel teaches Knowledge Based Artificial Intelligence (KBAI) every semester. And every time he offers it, Goel estimates, his 300 or so students post roughly 10,000 messages in the online forums -- far too many inquiries for him and his eight teaching assistants (TA) to handle. That's why Goel added a ninth TA this semester. Her name is Jill Watson, and she's unlike any other TA in the world. Jill is a computer -- a virtual TA -- implemented, in part, using technologies from IBM's Watson platform.