AI is an intelligent technology that makes computer work smartly like an intelligent human, and Pichai says machine learning and AI will "allow you to use your voice to search for information, to translate the web from one language to another, to filter the spam from your inbox, to search for "hugs" in your photos and actually pull up pictures of people hugging ... to solve many of the problems we encounter in daily life. It's what has allowed us to build products that get better over time, making them increasingly useful and helpful."

The following interview is one of many included in the report. As part of our ongoing series of interviews surveying the frontiers of machine intelligence, I recently interviewed Brendan Frey. Frey is a co-founder of Deep Genomics, a professor at the University of Toronto and a co-founder of its Machine Learning Group, a senior fellow of the Neural Computation program at the Canadian Institute for Advanced Research, and a fellow of the Royal Society of Canada. His work focuses on using machine learning to understand the genome and to realize new possibilities in genomic medicine. Brendan Frey: I completed my Ph.D. with Geoff Hinton in 1997.

AI is an intelligent technology that makes computer work smartly like an intelligent human, and Pichai says machine learning and AI will "allow you to use your voice to search for information, to translate the web from one language to another, to filter the spam from your inbox, to search for "hugs" in your photos and actually pull up pictures of people hugging ... to solve many of the problems we encounter in daily life. It's what has allowed us to build products that get better over time, making them increasingly useful and helpful."

In a blog post Sundar Pichai shares his vision of Google's future that will focus on machine learning, artificial intelligence, mobile computing and the cloud.

Last December, Tesla CEO Elon Musk teamed up with Y Combinator president Sam Altman and former Google Brain Team scientist Ilya Sutskever to launch OpenAI, a 1 billion non-profit organization dedicated to furthering our understanding of artificial intelligence with a promise to share its research openly with the world. Today, it's taken its first step in that direction by launching a free toolkit for developers to build and train their own AI bots with games and algorithmic challenges. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. The OpenAI Gym, currently in beta, includes environments to simulate situations for your AI to learn from, as well as a site to compare and reproduce results. The tools are designed for use with Reinforcement Learning (RL), one of the technologies used to develop Google's AlphaGo AI that defeated Go world champion Lee Se-Dol recently. RL works on the principle that a bot will receive a reward every time it completes an action successfully – similar to how you might train a dog.

Fresh off its promotion at Facebook's F8 developer conference, Poncho announced today that it has raised 2 million for its personalized weather forecasting service. The round was led by Lerer Hippeau Ventures and will be earmarked for improvements to Poncho's natural language processing, in addition to building artificial intelligence and data science technology into its bots and apps. Participating investors include Greycroft Partners, Comcast Ventures LP, Venture51 Capital Partners, RRE Ventures, Betaworks, Broadway Video Ventures, Ore Ventures, and several angel investors. Started two years ago out of Betaworks, Poncho offers a weather forecast alternative to Yahoo Weather, AccuWeather, and The Weather Channel. The company seeks to dominate what CEO Sam Mandel calls "thin content," which is activity that "takes place within the notification layer and also on a messaging platform that's contextually relevant, customized, and comes at the right time, but with enough polish to be engaging and cause a happy emotion."

Here's the tech news you need to know this Friday. The employees were part of the account-management and sales teams within the company's "publisher ad-tech group." It was a huge win across the board, and the stock increased 12% in after-hours trading. The company claims it is "curing" cancer. The stock soared more than 15% after-hours, but settled at about 8%.

Scientific determinism as first published by Laplace in 1814 is an important and essential principle in the macro-world around us. We know that if we push something, it will move -- unless our impulse was not sufficient to overcome inertia… and so forth. Laplace postulated that if there were an omniscient daemon who knew the precise positions and impulses of each and every particle in a system, this daemon would be able to deterministically calculate each and every future state of this system. Our beloved spreadsheet calculations resemble this daemon (possibly in more than one connotation). Typing in some basic data to start calculations from, the wonderous spreadsheet software will automagically calulate everything depending on them, eventually deriving the results we wanted to obtain.

If you're looking to add artificial intelligence to a hardware project for doing things like sensing objects in an enviroment or understand voice commands, Movidius' new Fathom USB stick might be just the thing. The company is known for its Myriad 2 deep learning chip that allows DJI drones to avoid obstacles. The Fathom is essentially a portable version of the chip that can be plugged into the USB 3.0 port of Linux-based devices to run fully-trained neural networks while consuming very little power. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. It's compatible with Caffe and TensorFlow frameworks and is capable of 150 gigaFLOPS (150 billion floating-operations per second). That means developers can use it to do things like enable robots to understand natural human speech and recognize faces, and teach drones to navigate indoors and outdoors by themselves – all without the need to connect to the cloud.

Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods. In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological "labels" to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don't use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.