UNU allows groups to chat online in a new way by forming a Swarm Intelligence that can answer questions, make predictions, and each decisions. Artificial intelligence (unanimous) UNU has not only conquered the Oscars and Super Bowl, but also the famous Kentucky derby. Its Swarm Intelligence software has reportedly made betting gamblers richer, with correct predictions owing to its successful forecasting methodologies. According to News Discovery, UNU is a software program that harnesses the collective power of horse racing professionals to correctly predict the first four horses that cross the finish line and in which order. At last weekend's Kentucky Derby, one experimental player witnessed the power of this software at first hand.

Are deep neural networks creative? It seems like a reasonable question. Google's "Inceptionism" technique transforms images, iteratively modifying them to enhance the activation of specific neurons in a deep net. The images appear trippy, transforming rocks into buildings or leaves into insects. Another neural generative model, introduced by Leon Gatys of the University of Tubingen in Germany, can extract the style from one image (say a painting by Van Gogh), and apply it to the content of another image (say a photograph). Generative adversarial networks (GANs), introduced by Ian Goodfellow, are capable of synthesizing novel images by modeling the distribution of seen images.

Deep neural networks have progressed immensely in recent years. Far from being moonshots, they are now at a point where they are better than humans at several tasks. They are capable of understanding text without previously encountering the words, of translating different languages, they can even cut transcription errors by half. And now, it seems they can recognize and replicate art (and a number of art styles). A team from the University of Freiburg in Germany have used deep neural networks to copy the artistic style of famous painters and paste them into video clips from movies and TV shows.

But artificial intelligence isn't some far-off fantasy imagined by a science fiction film-maker or writers. It's here, and only going to get better. From Stanley Kubrick's HAL 9000 in his 1968 sci-fi classic 2001: A Space Odyssey, to Samantha, the AI assistant that Joaquin Phoenix fell in love with in Spike Jonze's film Her, humanity has long dreamt of the day it can just talk to its computers. And some very bright people indeed are betting this will be the way we'll all interact with our computers very soon. We've all heard of Siri, of course – Apple's AI assistant, built right into the iPhone and iPad.

Computers will have developed "common sense" within a decade and we could be counting them among our friends not long afterwards, one of the world's leading AI scientists has predicted. Professor Geoff Hinton, who was hired by Google two years ago to help develop intelligent operating systems, said that the company is on the brink of developing algorithms with the capacity for logic, natural conversation and even flirtation. The researcher told the Guardian said that Google is working on a new type of algorithm designed to encode thoughts as sequences of numbers – something he described as "thought vectors". Although the work is at an early stage, he said there is a plausible path from the current software to a more sophisticated version that would have something approaching human-like capacity for reasoning and logic. "Basically, they'll have common sense."

"[Clippy was] utterly clueless and oblivious to the appropriate ways to treat people … No matter how long users worked with Clippy, he never learned their names or preferences. Indeed, Clippy made it clear that he was not at all interested in getting to know them. If you think of Clippy as a person, of course he would evoke hatred and scorn." Microsoft retired Clippy in 2007. As a going away present, users were invited to fire staples at him.

There are some human attributes robots could never replace - or at least that's what you might hope. But one university has brought that into question by replacing one of their teaching assistants with a machine. Student Tyson Bailey began to wonder if Jill was a computer and posted his suspicions on Piazza. 'We were taking an AI course, so I had to imagine that it was possible there might be an AI lurking around,' said Bailey, who lives in Albuquerque, New Mexico. 'Then again, I asked Dr. Goel if he was a computer in one of my first email interactions with him.

MLconf in Seattle is a week away and we are getting a glimpse. Ethics in machine learning is the hottest conversation right now. Hear how a quantum molecular dynamic model made Uber service more reliable, get practical advice on next revolution in text search, and learn about multi-classification evaluation and ensemble learning. Franziska Bell, Data Science Manager at Uber, will talk about how a quantum molecular dynamic model for enzymes made Uber more reliable as a service. And of course, you don't need to be a quantum mechanics to be a data scientist.

SUNNYVALE, CA--(Marketwired - May 13, 2016) - Niara, a provider of security analytics for attack detection and incident response, today announced that it has been named a Cool Vendor in the 2016 Cool Vendors in UEBA, Fraud Detection and User Authentication1 report by Gartner, Inc. Key findings of the report show "technologies that respond to user behavior are increasingly prevalent in security markets, although clients must consider how to integrate products with existing technologies to identity threats and suspicious behaviors both within and outside the organization." Additionally, Chief Information Security Officers (CISOs) and other security leaders should investigate UEBA technology to accelerate risk identification and escalation. "We believe being recognized as a Gartner Cool Vendor further validates that Niara's advanced user and entity behavioral analytics approach is becoming a priority for organizations looking to accelerate attack detection and response," said Sriram Ramachandran, CEO and co-founder of Niara. "Niara's analytics modules detect attacks and risky behaviors inside organizations, and empower security teams with advanced incident investigation and threat hunting capabilities." Niara's security analytics platform leverages data from any data source within the network and security infrastructure, applying unsupervised and supervised machine learning algorithms, statistical modeling and other analytics techniques to unearth security events that get past traditional solutions.

For the image manipulation I used the Python Imaging Library (PIL).