Hard on the heels of the White House's new report about artificial intelligence's potential to address major societal challenges, NVIDIA will be holding Washington's largest ever AI conference. GTC DC will feature some of the most prominent leaders in government and industry when it takes place Oct. 26-27, at the Ronald Reagan Building and International Trade Center in Washington. The event is the latest in a series of GPU Technology Conferences, which have attracted 16,000 people so far this year across Silicon Valley, Europe and Asia. The timing is right for policymakers and AI experts to meet, following yesterday's White House report concluding that "AI has the potential to help address some of the biggest challenges that society faces" and recommending increased funding in AI research to fuel economic growth. The report, Preparing for the Future of Artificial Intelligence, published by the National Science and Technology Council, notes that "the effectiveness of government itself is being increased as agencies build their capacity to use AI to carry out their missions more quickly, responsively and efficiently."

Artificial intelligence (AI), deep learning, and neural networks represent incredibly exciting and powerful machine learning-based techniques used to solve many real-world problems. In addition, each neuron applies a function or transformation to the weighted inputs, which means that the combined weighted input signal is transformed mathematically prior to evaluating if the activation threshold has been exceeded. Architecturally, an artificial neural network is modeled using layers of artificial neurons, or computational units able to receive input and apply an activation function along with a threshold to determine if messages are passed along. Models can become increasingly complex, and with increased abstraction and problem solving capabilities by increasing the number of hidden layers, the number of neurons in any given layer, and/or the number of paths between neurons.

Udacity President Sebastian Thrun spoke Thursday at Vanity Fair's New Establishment Summit. Prepare for your car to become an intellectual giant -- and for you to like it. In a highly optimistic forecast at the Vanity Fair New Establishment Summit in San Francisco, computer scientist Sebastian Thrun said artificial intelligence will radically reshape our lives for the better. "In the last 200 or 300 years, we have made ourselves into superhumans," able to plow a field a thousand times faster than our ancestors, fly across the Atlantic Ocean and talk to a person in Australia from thousands of miles away, he said. Artificial intelligence will take us to the next step: "Rather than replacing our muscles, we're going to be making our brains stronger."

Researchers working for Google have produced a new kind of computer intelligence which can learn in ways less immediately dependent on its programmers than any previous model. It can, for instance, navigate its way through a map of the London underground without being explicitly instructed how to do so. For the moment, this approach is less efficient than the old-fashioned, more specialised forms of artificial intelligence, but it holds out promise for the future and, like all such conceptual advances in computer programming, it raises more urgently the question of how society should harness these powers. An algorithm is simply a sequence of instructions. Law codes can be seen as algorithms.

Where can you find an unbiased, personal finance app that serves purely in your interests? An app that analyzes your bank accounts, your recurring subscriptions and your spending habits to figure out how to save you money? Clarity Money is cofounded by Adam Dell, Michael Dell's brother, and backed by some heavy hitters including the Soros Fund, Maveron Partners and Bessemer Venture Capital. Once you download the app and link your bank accounts, Clarity Money promises to analyze your accounts and make suggestions to save you money. It uses data science and machine learning to negotiate bills, create a savings account, find lower interest rate credit cards and/or personal loans, transfer money between accounts, and deliver actionable insights based on your spending patterns, credit score and credit cards.

Parag Mital is director of machine learning at Kadenze, as well as an artist and interdisciplinary researcher obsessed with the nature of information, representation and attention. Artificial intelligence allows machines to reason and interact with the world, and it's evolving at a breakneck pace. Many advances in AI can be attributed to machine learning, which works by tapping massive computing power to crunch through enormous amounts of digitized data. Now consider that most of our data, the best minds in the business and more computing power than you could ever imagine sit with just a handful of companies. For these reasons, only a few companies in the world are best situated to understand the true potential -- and the current limits -- of AI.

A tutorial given at NAACL HLT 2013. Machine learning is everywhere in today's NLP, but by and large machine learning amounts to numerical optimization of weights for human designed representations and features. The goal of deep learning is to explore how computers can take advantage of data to develop features and representations appropriate for complex interpretation tasks. This tutorial aims to cover the basic motivation, ideas, models and learning algorithms in deep learning for natural language processing. Recently, these methods have been shown to perform very well on various NLP tasks such as language modeling, POS tagging, named entity recognition, sentiment analysis and paraphrase detection, among others.

How do you explain machine learning to a child? Answer by Daniel Tunkelang, data scientist, search/discovery expert, led teams at LinkedIn and Google, on Quora. We want to teach a computer to recognize which foods are yummy and which foods are yucky. But the computer doesn't have a mouth or any way of tasting the food. Instead, we need to teach it by showing it examples of foods ("labeled training data"), some of which are yummy foods ("positive examples") and some of which are yucky foods ("negative examples").

During the 2016 Collision Conference held in New Orleans, our Content Strategist Cecilia Haynes interviewed conference speaker Dr. Tyrone Grandison. At the time of the interview, he was the Deputy Chief Data Officer at the U.S. Department of Commerce. Tyrone is currently the Chief Information Officer for the Institute for Health Metrics and Evaluation. Coming fresh off his talk on "Data science, apps and civic responsibility", Cecilia was thrilled to chat with Tyrone all about the democratization of data and how open data can help anyone build innovative products and services. I saw your talk and I thought you would be the the perfect person to reach out to.

In the aftermath of the Brexit vote to leave, one of the tweets that caught my eye was from founder and CEO of analyst firm HfS Research, Phil Fersht (@pfersht), which simply said, "at least the British can stop worrying about robots taking their jobs. Just get rid of the jobs altogether..." While that may not be amusing as it plays out against our globalised economy, it demonstrates how this topic has taken hold of so many of us. About a year ago, I was asked to sit on a panel at the annual Constellation Research Connected Enterprise 2015 called'The robots are here! The future of HR tech', to debate whether we're entering a dystopian existence where humans are the bottleneck to productivity and innovation or becoming a world of augmented humanity and digital humanisation. It's a fact that major economic shifts have led to both marginalisation, the downside, as well as great opportunity, clearly the upside.