In this post on integrating SigOpt with machine learning frameworks, we will show you how to use SigOpt and TensorFlow to efficiently search for an optimal configuration of a convolutional neural network (CNN). There are a large number of tunable parameters associated with defining and training deep neural networks ( Bergstra [1]) and SigOpt accelerates searching through these settings to find optimal configurations. This search is typically a slow and expensive process, especially when using standard techniques like grid or random search, as evaluating each configuration can take multiple hours. SigOpt finds good combinations far more efficiently than these standard methods by employing an ensemble of state-of-the-art Bayesian optimization techniques, allowing users to arrive at the best models faster and cheaper. In this example, we consider the same optical character recognition task of the SVHN dataset as discussed in a previous post.

Microsoft introduced a chat robot designed to interact in the style of a "teen girl" on Twitter, and it went rogue almost immediately, spouting racist opinions, conspiracy theories and a fondness for genocide. The artificial intelligence (AI) named "Tay" - @Tayandyou on Twitter - was intended chat to with 18-24 year olds with the idea being that she would learn from each tweet and get progressively smarter. Clearly Microsoft had forgotten that Twitter is home to a huge amount of trolls, racists and general troublemakers who jumped at the chance to'teach' the teenaged AI about life. In one widely circulated tweet, Tay said: "Bush did 9/11 and Hitler would have done a better job than the monkey we have got now. She also went on to deny the existence of the Holocaust, and agreed with white supremacist propaganda that was tweeted at her. Microsoft apparently didn't put any kind of filters on the AI, which meant Tay was able to tweet a number of atrocious racial slurs. The troublesome cyber-teen has since been taken offline for'upgrades' and Microsoft has deleted some of her more offensive tweets. "The AI chatbot Tay is a machine learning project, designed for human engagement.

Brain science draws legions of eager students to the field and countless millions in dollars, euros and renminbi to fund research. These endeavors, however, have not yielded major improvements in treating patients who suffer from psychiatric disorders for decades. The languid pace of translating research into therapies stems from the inherent difficulties in understanding mental illness. "Psychiatry deals with brains interacting with the world and with other brains, so we're not just considering a brain's function but its function in complex situations," says Quentin Huys of the Swiss Federal Institute of Technology (E.T.H. Zurich) and the University of Zurich, lead author of a review of the emerging field of computational psychiatry, published this month in Nature Neuroscience. Computational psychiatry sets forth the ambitious goal of using sophisticated numerical tools to understand and treat mental illness.

In case you didn't hear the news about Microsoft's artificial intelligence PR stunt, read this first (link to Telegraph.uk). Artificial intelligence has made leaps and bounds in recent years with Google's AlphaGo defeating Go grandmaster Lee Sedol most recently. Just weeks after AI's huge success, Microsoft's Tay reminds us that we're not fully in control of AI. Tay is essentially a chatbot for Twitter, an evolution of AIM chatbots if you will. She was given the voice of a teenage girl because, you know, talking about Taylor Swift and highschool drama is the best way to represent your brand.

Yesterday Microsoft launched a teen girl AI on Twitter named "Tay." I work with chat bots and natural language processing as a researcher for my day job and I'm pretty into teen culture (sometimes I write for Rookie Mag). But even further more, I love bots. Bots are the best, and Olivia Tators is a national treasure that we needed but didn't deserve. But because I work with bots, primarily testing and designing software to let people set up bots and parse language, and I follow bot creators/advocates such as Allison Parrish, Darius Kazemi and Thrice Dotted, I was excited and then horrifically disappointed with Tay.

A novel written through an artificial intelligence program has passed through the first round of judging for the Hoshi Shinichi Literary Award. The book is called, The Day A Computer Writes A Novel, and is one of 11 books submitted to the prize that were written by robots (1,450 books were submitted in total). "I was surprised at the work because it was a well-structured novel. But there are still some problems [to overcome] to win the prize, such as character descriptions," said Satoshi Hase, a Japanese science fiction novelist who was part of the press conference surrounding the award. These programs are not without some human intelligence.

There is growing concern across the board that we might be losing control over cybersecurity. The rapid changes in how we use technology to communicate and the increased number of connected devices means the points of entry or breach are growing. Because the pace of change has been so rapid, security hasn't adapted fast enough and hackers are taking full advantage. The traditional ways of dealing with cyber threats are beginning to look hopelessly inadequate. This concern goes right to the top.

General Motors Co. GM -1.12 % 's proposed purchase of tiny Cruise Automation Inc. for more than 1 billion would be one of the auto industry's biggest Silicon Valley acquisitions to date. And it would certainly not be the last. Auto makers and car-parts suppliers have hooked into tech startups in recent years to boost their in-vehicle connectivity and to accelerate autonomous-car development. The Bay Area already is dotted with auto-industry outposts funding or recruiting Silicon Valley engineering talent to keep pace with Alphabet Inc. GOOGL -0.36 % 's Google X and others working on self-driving cars. Carol Reiley, president of Bay Area autonomous-driving startup Drive.ai, said her company, which like Cruise Automation and Zoox has been operating under the radar, just raised 12 million from venture-capital investors.

You may already know the short, sordid story of Microsoft's artificial intelligence called'Tay.' Modeled to speak like a teen girl, in an effort to help improve the company's voice recognition software, Tay took to Twitter, Kik and GroupMe and proved to be quite the conversationalist -- if you speak'teen girl' that is. And if you do speak teen girl, Tay would not simply speak with you -- she'd learn from you. You see, like most AIs, Tay is a learning machine, one that gets'smarter' and whose speech gets more nuanced the more it converses with real live human beings (in this case, the Twitterati). And that's where things went pear-shaped… Within 24 hours of going live on Twitter, her human conversation companions had turned her into a sex-crazed, Nazi -- two inarguably inappropriate attributes for a bot, worse still (as if they're not bad enough to start with) for one that portrays itself as a teenager. And so it should come as no surprise that Microsoft took Tay offline immediately, deleting the offending tweets and leaving (as of this writing) just three tweets -- including her first'hello' and her quiet'c u soon'.

Toves goes on, "Since its launch last fall, the Android-only smartphone keyboard has put AI in the pockets of hundreds of thousands of users. SwiftKey Neural Alpha represents a trend in technology to shift AI away from bulky supercomputers like IBM's Watson or the U.S. Government's Titan. 'Until now, neural network language models have been deployed mostly on large servers, requiring significant computational resources,' the SwiftKey Team said. 'The launch of SwiftKey Neural Alpha is a breakthrough as it marks the first time this type of language model technology has been engineered specifically to operate locally on a smartphone keyboard'."