[unable to retrieve full-text content]I want to recommend several credible sources of accurate information. Most of the writing on this list is intended to be accessible to anyone—even if you aren’t a programmer or don’t work in tech.
Original Post: Credible Sources of Accurate Information About AI
[unable to retrieve full-text content]Read on to find out how the two-decade-old minwise hashing computational barrier has been overcome with a significantly efficient alternative.
Original Post: Fundamental Breakthrough in 2 Decade Old Algorithm Redefines Big Data Benchmarks
Posted by Jeff Dean, Google Senior FellowAbout a year ago, the Google Brain team first shared our mission “Make machines intelligent. Improve people’s lives.” In that time, we’ve shared updates on our work to infuse machine learning across Google products that hundreds of millions of users access everyday, including Translate, Maps, and more. Today, I’d like to share more about how we approach this mission both through advancement in the fundamental theory and understanding of machine learning, and through research in the service of product.Five years ago, our colleagues Alfred Spector, Peter Norvig, and Slav Petrov published a blog post and paper explaining Google’s hybrid approach to research, an approach that always allowed for varied balances between curiosity-driven and application-driven research. The biggest challenges in machine learning that the Brain team is focused on require the broadest exploration of new…
Original Post: The Google Brain Team’s Approach to Research
Posted by Christian Howard, Editor-in-Chief, Research CommunicationsMachine learning (ML) is a key strategic focus at Google, with highly active groups pursuing research in virtually all aspects of the field, including deep learning and more classical algorithms, exploring theory as well as application. We utilize scalable tools and architectures to build machine learning systems that enable us to solve deep scientific and engineering challenges in areas of language, speech, translation, music, visual processing and more.As a leader in ML research, Google is proud to be a Platinum Sponsor of the thirty-fourth International Conference on Machine Learning (ICML 2017), a premier annual event supported by the International Machine Learning Society taking place this week in Sydney, Australia. With over 130 Googlers attending the conference to present publications and host workshops, we look forward to our continued colalboration with the larger ML research…
Original Post: Google at ICML 2017
Posted by Christian Howard, Editor-in-Chief, Research CommunicationsThis week, Vancouver, Canada hosts the 2017 Annual Meeting of the Association for Computational Linguistics (ACL 2017), the premier conference in the field of natural language understanding, covering a broad spectrum of diverse research areas that are concerned with computational approaches to natural language.As a leader in natural language processing & understanding and a Platinum sponsor, Google will be on hand to showcase research interests that include syntax, semantics, discourse, conversation, multilingual modeling, sentiment analysis, question answering, summarization, and generally building better systems using labeled and unlabeled data, state-of-the-art modeling, and learning from indirect supervision.If you’re attending ACL 2017, we hope that you’ll stop by the Google booth to check out some demos, meet our researchers and discuss projects and opportunities at Google that go into solving interesting problems for billions of people. Learn…
Original Post: Google at ACL 2017
Posted by Christian Howard, Editor-in-Chief, Research CommunicationsFrom July 21-26, Honolulu, Hawaii hosts the 2017 Conference on Computer Vision and Pattern Recognition (CVPR 2017), the premier annual computer vision event comprising the main conference and several co-located workshops and tutorials. As a leader in computer vision research and a Platinum Sponsor, Google will have a strong presence at CVPR 2017 — over 250 Googlers will be in attendance to present papers and invited talks at the conference, and to organize and participate in multiple workshops.If you are attending CVPR this year, please stop by our booth and chat with our researchers who are actively pursuing the next generation of intelligent systems that utilize the latest machine learning techniques applied to various areas of machine perception. Our researchers will also be available to talk about and demo several recent efforts, including the…
Original Post: Google at CVPR 2017
[unable to retrieve full-text content]Nominations sought for outstanding research and service contributions in the field of data mining and data science.
Original Post: IEEE ICDM 2017 Call For Award Nominations, due Aug 15