If you want to talk about something important or sensitive, odds are that conversation will happen over the phone rather than email or text. The sound of someone's voice is an important part of trusting them--but the ability to trust the voice on the other end of that call is human might change. Google DeepMind announced a new speech generation method it calls WaveNet, which could bring artificial intelligence closer than ever to indiscernibly mimicking human speech. The algorithm can easily learn different voices and even generates artificial breaths, according to a DeepMind blog post. DeepMind, the London-based AI firm acquired by Google in 2014, broadly works to "solve intelligence," a goal that spans health, data center energy efficiency, and ancient Chinese board games.

Verifying your identity with brainwave scans sounds pretty awesome on the surface, but new research from from Texas Tech University shows that EEG identification could be the start of a whole new world of privacy concerns. It's not so much that brainwaves are susceptible to forgery, like fingerprints -- it's that EEG scanning applications can glean a lot more from your grey matter than you might want. Security researchers Abdul Serwadda and Richard Matovu recently tested a pair of EEG authentication systems to see if it was possible to identify personal information from anonymous brainwave scans. The pair created a machine learning system that compared the new brainwaves scans to EEG scans from a group of known alcoholics -- and the machine successfully identified 25-percent of persons who identified themselves as alcoholics in the new sample. "We weren't surprised," Serwadda said of the experiment.

An implementation of support vector machines (SVM) is available in the JMSL Numerical Library as of release 7.3. The data mining functionality in JMSL continues to expand with the latest release, including areas such as decision trees and bootstrap aggregation. The documentation of the IMSL Libraries is detailed and robust, but the algorithm discussion and examples can only cover a finite set of use cases. This series of blog posts walks through some additional examples with a focus on classification, starting with the textbook examples part of most SVM resources. Notes and key points are highlighted throughout to provide a complementary resource for users new to SVM or new to using the JMSL Library.

A.I is out to get us. It will replace us all.. or maybe, it's just another tool that we will get used to like calculators or iPhones. If you are reading this post, chances are you are familiar with Artificial Intelligence, Deep Learning, Neural nets. I am not going to be pedantic and use them interchangeably. If you don't care for any of that, feel free to read this article as "Human in Machine Learning loop". Let's start with a practical example of something I built at Rent The Runway.

"There is a stigma against market timing. This stigma existed for good reasons, but the explosion of vast data sets and new analytical techniques has now made timing the market possible. Just as it was considered irresponsible to time the market over the last 30 years, it will be considered irresponsible NOT to time the market in the next 30 years." Light food and drinks provided. The speakers will be Blair Hull, most recently founder of Ketchum Trading, and Matthew Dixon of the Illinois Institute of Technology's Stuart School of Business and founder of Quiota, LLC.

In this Q&A Ari explains why the use of machine learning for automation is unlikely to overtake most organizational roles in the near future, why data is so incredibly important, the continucontinuous need for data scientists and his priorities for 2016.

Google DeepMind claims to have significantly improved computer-generated speech with its AI technology, paving the way forward for sophisticated talking machines like those seen in sci-fi films like "Her" and "Ex-Machina." The London-based research lab, acquired by Google in 2014 for a reported 400 million, announced on Thursday that it has developed a talking computer programme called "WaveNet" that halves the quality gap that currently exists between human speech and computer speech. Although WaveNet sounds more like a human voice than existing artificial voice generators -- known as "text-to-speech" (TTS) systems -- it requires too much computing power to make it practical, meaning Google won't be integrating it into its products any time soon, according to The Financial Times. Aäron van den Oord, a research scientist, at DeepMind said: "Mimicking realistic speech has always been a major challenge, with state-of-the-art systems, composed of a complicated and long pipeline of modules, still lagging behind real human speech. Our research shows that not only can neural networks learn how to generate speech, but they can already close the gap with human performance by over 50%.

I'm also the CEO of a company that is utilizing A.I. technologies to improve K-12 education through synchronized planning calendars. During my journey with EduSync, I've learned a few things about what artificial intelligence is, what it isn't, and how it can have a positive impact in K-12. Artificial intelligence is young--newborn young. In simple terms, it is the attempt to build a computer that operates like a human brain. This involves programming software that learns from experience (machine learning or ML), understands human language including common usage and context (natural language processing or NLP), and has the ability to figure out what to do in the future based on the past (predictive analytics).

As the health care industry shifts from fee-for-service to value-based care, the ability to deploy effective population health initiatives has emerged as a critical factor for the success of organizations. With more risk shifting to providers, organizations need to go beyond merely analyzing data to stratify patients into condition-specific cohorts; they need to develop sophisticated approaches for weighing a wide range of variables to selectively deliver interventions and guidance to caregivers that help improve outcomes while lowering costs. Population health has the promise to deliver big results, but many providers are facing roadblocks along the way. In order to successfully engage in population health, providers should focus on five critical areas. Successful population health initiatives need access to relevant, accurate data.

Over the past century, we have made massive strides in the rights revolution. These include rights for women, children, the LGBT community, animals, and so much more. Exploring the future, we must ask ourselves: what next? Will we ever fight for the rights of artificial intelligence? If so, when will this AI rights revolution occur, and what will it look like?