Career: Baidu, chief scientist, May 2014 to present; co-founder and chairman of Coursera, 2012; Google Brain, project founder and leader, 2011-2012; Stanford University, faculty member since 2002. Ng developed some of the underpinnings of "deep learning," a computer-programming technique that uses powerful neural networks of processors to imitate some of the human brain's functions. The Baidu Silicon Valley AI Lab's speech-recognition system, Deep Speech, was named as a "breakthrough" technology by MIT Tech Review in February. A: Yes, our search system is powered by deep learning, but a lot of things at Baidu are powered by deep learning.

By now the world has heard about the rise and fall of Microsoft's Tay, an artificially intelligent bot that lived on Twitter, Kik, and GroupMe. To better understand where exactly Microsoft went wrong with Tay, I spoke with Brandon Wirtz, the creator of Recognant, a cognitive computing and artificial intelligence (AI) platform designed to aid in understanding big data from unstructured sources. Tay's Twitter conversations started out innocently enough, proclaiming her love for humans and wishing that National Puppy Day was every day. Upon analyzing Tay's tweets, Broad Listening found that Tay made four times more negative tweets than that of popular teen celebrities from Disney such as Peyton List, Laura Marano, China McClain, and Kelli Berglund.

Meet Tay, Microsoft's short-lived chatbot that was supposed to seem like your average millennial woman but was quickly corrupted by Internet trolling. "Unfortunately," a Microsoft spokesperson told BuzzFeed News in an email, "within the first 24 hours of coming online, we became aware of a coordinated effort by some users to abuse Tay's commenting skills to have Tay respond in inappropriate ways. Apple's Siri and Microsoft's Cortana can't hold much conversation, but they do carry out tasks like making phone calls and conducting a Google search. In China, Microsoft has a chatbot named Xiaoice that has been lauded for its ability to hold realistic conversations with humans.

In the final game of their historic match, Google's artificially intelligent Go-playing computer system has defeated Korean grandmaster Lee Sedol, finishing the best-of-five series with four wins and one loss.

When a RNN is trained on sequences of words, it learns to represent each word as a high dimensional vector which encodes the model's understanding of that word. If you take a step back and view the image as a whole, the large scale structure of the image is determined by words' part of speech. Nouns tend to lie in the center of the image, verbs tend to lie on the upper right side, and first names form a large orange cluster in the bottom left part of the image. The RNN learned all of this semantic understanding without a human ever having to code a definition of concepts like nouns, verbs, universities, cities, meetings, or social media.

A simple way to find great articles and resources on popular subjects such as data science, machine learning, deep learning, Python, R, data sets, dataviz, IoT, AI - or even Excel - is to use our data science search engine. This page, populated with pre-selected queries, is an excellent starting point. The search box can be found on DSC and all our channels, on all pages, at the very top, on the right-hand site. For instance, click here to find results for Python.

Google will create business tools and products based on its own artificial intelligence technology, seeking to entice more companies to rent its cloud-computing services. The company also said it won several new large cloud customers, including the interactive division of Walt Disney Co., which now runs a web-subscription service on Google's cloud, and Coca-Cola Co., which rented Google servers for a World Cup marketing campaign. While modern cloud systems are based on "decades-old" technology, Google said, the company's forthcoming products and services are designed for the next wave of cloud computing. Google will charge for these capabilities, a departure from its typical consumer-focused approach in which AI technology supports free Web-based services and apps such as Photos and Translate.

SAN FRANCISCO--(BUSINESS WIRE)--Executives previously from IBM Watson, GE Digital, Infosys, and MicroStrategy announced today that they have joined forces with TPG Growth to launch Noodle Analytics, Inc. (Noodle.ai), the Enterprise Artificial Intelligence company. Today's artificial intelligence technologies include machine learning, predictive data analytics, and data science. He is joined by Dr. Matt Denesuk, previously Chief Data Science Officer for GE Digital; Raj Joshi, previously Senior Executive Vice President of Professional Services at MicroStrategy; and Dr. Ted Gaubert, previously Chief Technology Officer of Infosys Consulting. The team brings deep experience in AI, big data, data science, machine learning, and data analytics across industries.

To do that, he and his team collected thousands of geotagged posts tweeted between July 2013 and July 2014 in New York state, and then winnowed them down to tweets containing booze-related keywords (ranging from "beer keg" to "shitfaced"). Each tweet passed through three human "Turkers," who were asked three questions: Q1: Does the tweet make any reference to drinking alcoholic beverages? Q3: if so, is it likely that the tweet was sent at the time and place the tweeter was drinking alcoholic beverages? The success rate--that is, the rate at which the machines' answers matched the Turkers' consensus--ranged from 92 percent for the algorithm answering Q1, to 82 percent for the drunk-spotting algorithm answering Q3.

For the vast majority of queries (for example, navigation, simple fact lookup, and others), search engines do extremely well. They also highlight many of the issues that are common to sophisticated AI question-answering systems. Rapid and ready-at-hand access, depth of processing, and the way they enable people to offload some ordinary memory tasks suggest that search engines have become more of a cognitive amplifier than a simple repository or front-end to the Internet. Although search engines are superb at finding and presenting information--up to and including extracting complex relations and making simple inferences--knowing how to frame questions and evaluate their results for accuracy and credibility remains an ongoing challenge.