Google is unveiling more and more about their revolutionary software, including the innovations behind the search Search and Street View functions. However, they haven't been as forthcoming in terms of their hardware. Google just unveiled one of its hardware brainchilds: the Tensor Processing Unit (TPU). The TPU is a custom ASIC created specifically for Google's open source software library for machine learning, TensorFlow. We've been running TPUs inside our data centers for more than a year, and have found them to deliver an order of magnitude better-optimized performance per watt for machine learning.

What was once just a figment of the imagination of some our most famous science fiction writers, artificial intelligence (AI) is taking root in our everyday lives. We're still a few years away from having robots at our beck and call, but AI has already had a profound impact in more subtle ways. Weather forecasts, email spam filtering, Google's search predictions, and voice recognition, such Apple's Siri, are all examples. What these technologies have in common are machine-learning algorithms that enable them to react and respond in real time. There will be growing pains as AI technology evolves, but the positive effect it will have on society in terms of efficiency is immeasurable.

Discovery on Pinterest is all about finding things you love, even if you don't know at first what you're looking for. The Visual Discovery engineering team at Pinterest is tasked with building technology that will help people to continue to do just that, by building technology that understands the objects in a Pin's image to get an idea of what a Pinner is looking for. Over the last year we've been building a large-scale, cost-effective machine vision pipeline and stack with widely available tools with just a few engineers. Today we're sharing some new technologies we're experimenting with, as well as a white paper, accepted for publication at KDD 2015, that details our system architecture and insights from these experiments and makes the following contributions: It used to be that if a Pin had never before been saved on Pinterest, we weren't able to provide Related Pins recommendations. This is because Related Pins were primarily generated from traversing the local "curation graph," the tripartite user-board-image graph evolved organically through human curation.

As if the communication and messaging apps ecosystem wasn't already bursting at its seams, Google has added three more--Spaces, Allo and Duo. Spaces can be downloaded on Android and iOS devices now, while Allo and Duo will be "available this summer". But wait, what's so different with Allo, in a world that has Whatsapp, Facebook's Messenger, Apple's iMessage and not to forget, Google's own Hangouts app? Allo is essentially designed to be a smarter instant messaging app and offer features which no rival does, yet. And most of those are based on the integration of machine learning, also known as artificial intelligence. What Allo does is it pre-empts what your response to a particular message might be, with some suggestions that show up as you are about to respond.

Washington: The world's first artificial intelligence lawyer has been employed by a law firm in the US, which will use the robot to assist its various teams in legal research. The robot called'ROSS' is built upon Watson, IBM's cognitive computer. With the support of Watson's cognitive computing and natural language processing capabilities, lawyers can ask ROSS their research question and the robot reads through the law, gathers evidence, draws inferences and returns highly relevant, evidence-based answers. ROSS also monitors the law around the clock to notify users of new court decisions that can affect a case. The programme continually learns from the lawyers who use it to bring back better results each time.

The University of Washington will be hosting the first of four White House Office of Science and Technology Policy workshops on artificial intelligence. The session in Seattle on Tuesday, involving the UW School of Law and the UW Tech Policy Lab, will focus on legal and policy issues around artificial intelligence. Speakers include UW professors, White House staff and the chief executive officer of the Allen Institute for Artificial Intelligence. Oren Etzioni, who is also a UW computer science and engineering professor, will provide an overview on the current state of artificial intelligence, followed by two panel discussions. The first will examine issues around making decisions in the private or public sector using artificial intelligence.

I have spent a lot of time working with spreadsheets, databases, and data more generally. This work has led to me having a very particular set of skills, skills I have acquired over a very long career. Skills that make me a nightmare for people like you. If you let my daughter go now, that'll be the end of it. I will not look for you, I will not pursue you.

"An Introduction to Statistical Learning (ISL)" by James, Witten, Hastie and Tibshirani is the "how to'' manual for statistical learning. Inspired by "The Elements of Statistical Learning'' (Hastie, Tibshirani and Friedman), this book provides clear and intuitive guidance on how to implement cutting edge statistical and machine learning methods. ISL makes modern methods accessible to a wide audience without requiring a background in Statistics or Computer Science. The authors give precise, practical explanations of what methods are available, and when to use them, including explicit R code. Anyone who wants to intelligently analyze complex data should own this book.

Thousands of articles and tutorials have been written about data science and machine learning. Hundreds of books, courses and conferences are available. You could spend months just figuring out what to do to get started, even to understand what data science is about. In this short contribution, I share what I believe to be the most valuable resources - a small list of top resources and starting points. This will be most valuable to any data practitioner who has very little free time.

Something strange happened in the world of artificial intelligence (AI) on Wednesday. Facebook CEO Mark Zuckerberg posted on his Facebook profile that his company has created an AI system that is "getting close" to beating the best humans at Chinese board game Go. Hours later, DeepMind -- a startup based in London that was bought by Google for 400 million in 2014 -- said it had already developed an AI named AlphaGo that had just beaten the best Go player in Europe. DeepMind's breakthrough was splashed across the front cover of science journal Nature yesterday evening and covered by over 200 media titles. "This is the first time that a computer Go program has defeated a human professional player, without handicap, in the full game of Go - a feat that was previously believed to be at least a decade away," explained the DeepMind research paper -- Mastering the game of Go with deep neural networks and tree search.