Mitch and Freada Kapor have long been champions of equality. They talk about their hope for a more diverse tech workforce in Silicon Valley. Mitch was the man behind Lotus Notes and has gone on to be a big promoter of social issues. During those three intensive days spent brainstorming new technologies, she realized she was not the only one. Huaranca was one of just two Latinos in a room of 100 people.

Google's ad tracking data has been extended – potentially to watch over much of your life. Until recently, the site had important restrictions on the way that it could use your data. And perhaps one of the most important ones was the fact that Google worked hard to keep a massive database of web-browsing records separate from the personal information that it stores about people. Because of its huge range of products, Google knows a lot about specific people: for most internet users, it likely has their name, their addresses and a range of other personal information. And through its DoubleClick advertising network it has a huge set of information about people's web browsing history.

Spring XD addresses the new demands of big data and real-time data pipelining, but it sets a foundation for much more. Data Science, Machine Learning and Predictive Analytics are becoming more common across industries. The most successful and innovative companies are currently exploring live data streaming scenarios instead of the traditional batch collection, storage, ETL-like transformations and offline analytical solutions. Two main reasons are demanding this change. First, some data is really only valuable in the moment it's connected--as the half-life of its business value degrades quickly.

At a dinner I attended some years ago, the distinguished differential geometer Eugenio Calabi volunteered to me his tongue-in-cheek distinction between pure and applied mathematicians. A pure mathematician, when stuck on the problem under study, often decides to narrow the problem further and so avoid the obstruction. An applied mathematician interprets being stuck as an indication that it is time to learn more mathematics and find better tools. I have always loved this point of view; it explains how applied mathematicians will always need to make use of the new concepts and structures that are constantly being developed in more foundational mathematics. This is particularly evident today in the ongoing effort to understand "big data"--data sets that are too large or complex to be understood using traditional data-processing techniques.

Las Vegas - 25 Oct 2016: IBM (NYSE: IBM) today announced IBM Watson Data Platform to help companies gain more valuable insights from data. The platform delivers the world's fastest data ingestion engine and cognitive-powered decision-making to data professionals, allowing them to collaborate in the IBM Cloud, with the services they prefer. IBM is also making IBM Watson Machine Learning Service available – making machine learning simple with an intuitive, self-service interface. "Machine learning is incredibly powerful, but many of today's data professionals lack the skills to fully exploit it for business and the ability to effectively collaborate on datasets," said Bob Picciano, Senior Vice President, IBM Analytics. "Watson Data Platform applies cognitive assistance for creating machine learning models, making it far faster to get from data to insight. It also, provides one place to access machine learning services and languages, so that anyone, from an app developer to the Chief Data Officer, can collaborate seamlessly to make sense of data, ask better questions, and more effectively operationalize insight."

Bank of America debuted a virtual assistant bot today at Money2020, a fintech conference being held this week in Las Vegas. Named Erica, the bot uses artificial intelligence and predictive analytics to learn your personal spending habits and offer helpful advice. The bot will be available by voice command or plain text in Bank of America smartphone apps next year, according to CNBC. Erica is designed to be not just a virtual assistant but each customer's "personal advocate," said Bank of America head of digital banking Michelle Moore. It can tell you about your spending habits, notice if you spend more than usual on a certain product or category of products, present opportunities to reduce debt or save money, and alert you if your credit score dips.

Figuring out how much a business trip will cost can be a hassle. Employees are often put in the position of figuring out how to get somewhere, and once they get there, they don't have an incentive to keep their spending to a minimum. A new startup called TravelBank aims to help by providing a predictive budget for a trip, based on when an employee is traveling and the destination. After that, it helps the employee to document spending and file an expense report that shows how much money was spent against budget. More than just helping employees capture expenses, TravelBank is focused on helping to change their behavior so they spend less money.

Darknet is one of the most interesting and thought provoking sci fi books that I have read in awhile. As someone who is deeply immersed in the fields of machine learning and artificial intelligence, I have come across or thought about many of the ideas that have been presented in this book, especially the central theme – autonomous agents that aided by our increasingly digital online worlds, become capable enough to run their own corporate entities. Technology is not quite there yet for a creation of such an agent, but it's probably much closer than most people realize. That's why it was really interesting to go through the intellectual exercise of imagining what kind of things would such an entity engage in if it comes to be. For that reason alone Darknet is very worthwhile read for all AI geeks out there.

Applied Materials' (NASDAQ:AMAT) business strategy that enables major technological inflections for customers has earned it the top spot in many of its markets served, resulting in increased sales and EPS since 2013. With that, management has set lofty targets to reach by 2018, including EPS of 2.00, though we think that may be stretching it a bit. Applied is currently working through what it sees as the second phase of WFE drivers in mobile and social media. While it expects such macro trends to provide solid growth, even more robust proliferation of its chips is expected to come with the next wave of visual computing and artificial intelligence. Applications include virtual/augmented reality, the Internet of Things, big data, artificial intelligence, smart vehicles, and additive manufacturing.

When it comes to machine learning frameworks, Google's Tensorflow is clearly the most popular option right now, but with CNTK, Microsoft also released its own internal framework at the beginning of the year. The company is launching the first beta of the next version (2.0) of CNTK today and with it, it hopes to challenge Tensorflow's leadership position. CNTK used to stand for'Computational Network Toolkit' but the software has now been renamed to Microsoft Cognitive Toolkit instead. Xuedong Huang, Microsoft's Chief Speech Scientist, told me that he believes CNTK/Cognitive Toolkit has always had plenty of advantages over Tensorflow and similar frameworks -- especially with regards to performance. According to Microsoft's benchmarks, Cognitive Toolkit continues to outperform its competitors in most tests and unsurprisingly, this new version is faster than the previous releases, especially when working on big data sets.