The findings suggest that about a quarter of all police departments in the US have access to face recognition technology. That police are using face recognition technology is not a problem in itself. In a world with a camera in every pocket, they would be daft not to. But face recognition can be used far more broadly than fingerprint recognition, which means it carries a higher risk of tagging innocent people. Fingerprints are difficult to work with.

Investigators eager to uncover the genetic basis of autism could now have hundreds of promising new leads thanks to a study by Princeton University and Simons Foundation researchers. In the first effort of its kind, the research team developed a machine-learning program that scoured the whole human genome to predict which genes may contribute to autism spectrum disorder (ASD). The results of the program's analyses -- a rogue's gallery of 2,500 candidate genes -- vastly expand on the 65 autism-risk genes currently known. Researchers have recently estimated that 400 to 1,000 genes underpin the complex neurodevelopmental disorder. This newest research provides a manageable, "highly enriched" pool from which to pin down the full suite of ASD-related genes, the researchers said.

Editor's note: At the ISC conference next week in Frankfurt, Andrew Ng, chief scientist at Baidu, will present the keynote address and Bryan Catanzaro, research scientist at Baidu's Silicon Valley AI Lab, will participate in the Analyst Crossfire Panel. Speech recognition has expanded accessibility, natural language processing helps answer user questions, and image recognition offers more intuitive search results. It's not surprising that AI is transforming internet companies. We believe the AI revolution will transform many other industries as well, from transportation to healthcare. AI research has been going on for decades, so you may ask "what has changed to make AI so useful today?"

From alarm's snooze in the morning to watching television at night, and all the activities in between – human life is increasingly influenced by machines. Today, machine learning has transformed devices with static pre-programmed software into smart machines driven by Artificial Intelligence (AI), giving them the ability to learn by themselves based on gathered data. Machine learning focuses on developing computer programs that can teach themselves to grow and update the program embedded in a device by analyzing incoming data. Defined as the science of getting computers to act without being explicitly programmed, Machine learning is aiding human life by paving the path towards smart technologies such as self-driving cars, practical speech recognition, and effective web search. It has also improved the concept of understanding human genome in the field of biotechnology.

Big data is a big deal, but problems within the data can skew results and lead to problematic choices. To help keep data -- and the decisions based on it -- clean, researchers at Columbia University and the University of California at Berkeley have developed new software. ActiveClean analyzes prediction models to determine which mistakes (e.g., typos, outliers and missing values) to edit first, updating the models in the process, according to Columbia. "Big data sets are still mostly combined and edited manually, aided by data-cleaning software like Google Refine and Trifacta or custom scripts developed for specific data-cleaning tasks," university officials said. "The process consumes up to 80 percent of analysts' time as they hunt for dirty data, clean it, retrain their model and repeat the process. Cleaning is largely done by guesswork."

Erik Mueller is Director of Intelligent Assistants at Capital One. He won the AAAI Feigenbaum Prize with the Watson Team. He has ten patents on artificial intelligence and is the author of four books in the field. He holds a Ph.D. and M.S. in computer science from UCLA and an S.B. in computer science from MIT.

Memory fills the gaps in information that even todays best AI algorithms can't Google's DeepMind artificial intelligence lab does more than just develop computer programs capable of beating the world's best human players in the ancient game of Go. The DeepMind unit has also been working on the next generation of deep learning software that combines the ability to recognize data patterns with the memory required to decipher more complex relationships within the data. Now, it's at this point where when we say "memory" you might think that we're referring to the type of RAM or some other form of hardware computer memory you stick into servers, but no. After all, say for example we asked you to predict an outcome then it's likely that not only will you draw on the information you have on hand at the time but you'll also – consciously or sub-consciously – draw on past memories that, when accessed and interpreted correctly, will help you create a better, more informed answer – or opinion. It's this "human" type memory – this "external" memory as researchers call it – that we're increasingly seeing being used to augment today's most advanced deep learning AI's – such as DeepMind. Deep learning is the latest buzz word for artificial intelligence algorithms called neural networks that can learn over time by filtering huge amounts of relevant data through many "deep" layers.

As CTO, he has the weighty task of making sense of tomorrow's disruptive technologies – today – then enabling Wipro to compete and win in these areas. We met him to hear how his team thinks about the future, and where RPA and AI fit into their roadmap. Wipro is well known for providing technology and outsourcing services. From distant origins in Mumbai in the 1940s, Wipro has grown into a worldwide technology and outsourcing company with over 40 billion in revenue. But it might come as a surprise to many that Wipro filed over 500 patents last year. This is because, like many global service businesses, Wipro is being pushed to help clients innovate: do new things, with new tools and technologies.

On Wednesday, Stephen Hawking spoke at the opening of Cambridge University's new artificial intelligence center, which, in part, will investigate potential problems the technology may pose, reports the Telegraph. In his address, Hawking, a long-time critic of unchecked and poorly considered advances in the area, warned, "The rise of powerful AI will be either the best, or the worst thing, ever to happen to humanity." SEE ALSO: Stephen Hawking: 'Human race has no future' without space travel He indicated that while it may, "finally eradicate disease and poverty," it could, "also bring dangers, like powerful autonomous weapons, or new ways for the few to oppress the many." Further, said Hawking, "...in the future, AI could develop a will of its own -– a will that is in conflict with ours." The astrophysicist applauded the establishment of the Cambridge AI center, noting, "We spend a great deal of time studying history, which, let's face it, is mostly the history of stupidity ... so it is a welcome change that people are studying instead the future of intelligence."

Getting started using the SDK is quite easy: you can either use Node.js or .NET (this is Microsoft after all), or work exclusively through a REST-based API. Forced to say goodbye to my beloved Python, I went for the Node.js Disregarding the formatting, the code contains four lines in total: the first imports the BotBuilder package, the second allows you to use the console to interact with the bot, the third instantiates the bot itself and the last line contains the dialog info. I'll be using a slightly more advanced version allowing me to use the Bot Framework Emulator to interact with the Chatbot. Let's give it a try.