Since 2013, MetisMetisVisit their siteView company profile Create Job Alert has been offering a full-time data science bootcamp in New York. Tailored specifically for people with some experience coding and an aptitude for math, the program expanded to San Francisco last year, where it's about to commence its second class. Now, the company has its eyes set on Chicago. This week, Metis announced it will be offering a part-time course in machine learning, taught by machine learning consultant Jeremy Watt, who holds a PhD from Northwestern and has authored an upcoming textbook on the subject. The 36 hour course will start in July and take place over six weeks.

Microsoft is clearly in the midst of a renaissance, and nothing more clearly indicates this than its aggressive use of open source. Initially a "cancer," and then an afterthought, open source has become Microsoft's single greatest weapon in recovering its industry stature. For evidence, look no further than its opening up of CNTK, Microsoft's artificial intelligence framework that powers everything from its digital assistant Cortana to the Skype Translator. Microsoft has always been a technology pioneer. The problem is that the company too often bottled up such innovations, as Bloomberg captures.

In the run up to next week's Hadoop confab in Silicon Valley, vendors are releasing a flock of automation and other tools aimed at beefing up the mainstream data processing framework. Among them is an attempt to incorporate data science with a leading Hadoop distribution via a machine-learning approach. Boston-based data science automation specialist DataRobot said this week its machine-learning platform designed to fill the data science skills gap has been certified on Cloudera Enterprise 5. The Cloudera platform is used for data management and analytics. DataRobot said the certification means Cloudera users could incorporate machine learning into their analytics operations without additional interfaces or protocols.

Cloud Machine Learning relies on the open source TensorFlow machine learning library, according to Google. The tool will take machine learning mainstream, offering data scientists and developers a way to build a new class of intelligent applications, the company said. It provides access to the same technologies that power Google Now, Google Photos and voice recognition in Google Search as application program interfaces. In a blog post about Cloud Machine Learning, Google said the tool makes it easy for developers to build large-scale machine learning models in less time. Cloud Machine Learning is portable, fully managed and scalable, and works with data in several formats.

New lip-reading technology could help solve crimes by deciphering what people caught on CCTV are saying, researchers have claimed. The visual speech recognition technology developed by the University of East Anglia in Norwich can be used to determine what people are saying in situations where audio is not good enough to hear - such as on security camera footage. Helen Bear, from the university's school of computing science, said the technology could be applied to a wide range of situations from criminal investigations to entertainment. She added: "Lip-reading has been used to pinpoint words footballers have shouted in heated moments on the pitch, but is likely to be of most practical use in situations where there are high levels of noise, such as in cars or aircraft cockpits. "Crucially, whilst there are still improvements to be made, such a system could be adapted for use for a range of purposes - for example, for people with hearing or speech impairments."

If you have ever tried your hand at lip-reading in a noisy environment, you'll know it isn't easy. Now, researchers have invented a machine that can tell the difference between sounds that look the same on the lips to give anyone the ability to decipher what's being said. It is hoped the new technology could help people with hearing and speech impairments communicate more easily and even help solve crimes. Researchers have invented a machine that can tell the difference between sounds that look the same on the lips to give anyone the ability to decipher what's being said. The visual speech recognition technology, can be applied'any place where the audio isn't good enough to determine what people are saying,' according to Helen Bear, who created the machine alongside Richard Harvey at the University of East Anglia (UEA).

UPDATE: March 24, 2016, 3:32 p.m. EDT: Microsoft has "taken Tay offline" and is "making adjustments" to her. The company gave TechCrunch the following statement on Tay's status: "The AI chatbot Tay is a machine learning project, designed for human engagement. It is as much a social and cultural experiment, as it is technical. Unfortunately, within the first 24 hours of coming online, we became aware of a coordinated effort by some users to abuse Tay's commenting skills to have Tay respond in inappropriate ways. As a result, we have taken Tay offline and are making adjustments."

To paraphrase William Gibson, "The future is already here and, thanks to intelligent assistants (IA), it is more evenly distributed than ever before." Based on our spoken input, mobile personal assistants (like Siri and Google Now) answer questions, navigate routes, and organize meetings. Close cousin Alexa, running on the Echo, understands our utterances when we order pizza, hail an Uber, or complete an order from Amazon. Meanwhile, a large set of distant cousins – call them text'bots – understand "plain English" requests and can recommend restaurants, movies, or even bridal fashions. We humans are learning to take over our digital lives using our own words and our choice of digital device.

For interaction designers, it's becoming common to encounter privacy concerns as part of the design process. Rich online experiences often require the personalization of services, involving the use of people's information. Because gathering information to personalize a customer experience can interfere with the overall experience -- with negative consequences for the business -- how do we navigate this increasingly difficult territory? What are the guidelines to follow when using data to personalize digital experiences, and how can organizations help people feel comfortable with personalization services that research clearly shows people want? Exchanging personal information for things we want, whether physical or virtual, is nothing new. Long before the Internet, we freely published our home phone numbers and addresses in public directories.

Is your government ready for the Internet of Things (IoT)? The news media has been full of stories of self-driving cars being tested around the world and drones being used in diverse places. But a quiet global technology revolution is now occurring that is transforming the way we live and work in almost every area of life. And while robots at Amazon and smart home devices seem to be getting regular media attention, much more is happening in cyberspace. We live in exciting times with vast technological possibilities merging our online and offline lives.