Posted by Jeff Dean, Google Senior Fellow, Head of Google Research and Machine IntelligenceThis week, Vancouver, Canada hosts the 6th International Conference on Learning Representations (ICLR 2018), a conference focused on how one can learn meaningful and useful representations of data for machine learning. ICLR includes conference and workshop tracks, with invited talks along with oral and poster presentations of some of the latest research on deep learning, metric learning, kernel learning, compositional models, non-linear structured prediction, and issues regarding non-convex optimization.At the forefront of innovation in cutting-edge technology in neural networks and deep learning, Google focuses on both theory and application, developing learning approaches to understand and generalize. As Platinum Sponsor of ICLR 2018, Google will have a strong presence with over 130 researchers attending, contributing to and learning from the broader academic research community by presenting papers and…
Original Post: Google at ICLR 2018
[unable to retrieve full-text content]I recently was a guest speaker at the Stanford AI Salon on the topic of accessiblity in AI, which included a free-ranging discussion among assembled members of the Stanford AI Lab. There were a number of interesting questions and topics, so I thought I would share a few of my answers here.
Original Post: How to Make AI More Accessible
Posted by Steven Butschi, Head of Higher Education, GoogleScientists across nearly every discipline are researching ever larger and more complex data sets, using tremendous amounts of compute power to learn, make discoveries and build new tools that few could have imagined only a few years ago. Traditionally, this kind of research has been limited by the availability of resources, with only the largest universities or industry partners able to successfully pursue these endeavors. However, the power of cloud computing has been removing obstacles that many researchers used to face, enabling projects that use machine learning tools to understand and address student questions and that study robotic interactions with humans, among many more.In order to ensure that more researchers have access to powerful cloud tools, we’re launching Google Cloud Platform (GCP) research credits, a new program aimed to support faculty in…
Original Post: Announcing the Google Cloud Platform Research Credits Program
Posted by Pankaj Gupta and Anand Rangarajan, Engineering Directors, Google IndiaLast month, Google Bangalore hosted the Workshop on Artificial Intelligence and Machine Learning, with the goal of fostering collaboration between the academic and industry research communities in India. This forum was designed to exchange current research and industry projects in AI & ML, and included faculty and researchers from Indian Institutes of Technology (IITs) and other leading universities in India, along with industry practitioners from Amazon, Delhivery, Flipkart, LinkedIn, Myntra, Microsoft, Ola and many more. Participants spoke on the ongoing research and work being undertaken in India in deep learning, computer vision, natural language processing, systems and generative models (you can access all the presentations from the workshop here).Google’s Jeff Dean and Prabhakar Raghavan kicked off the workshop by sharing Google’s uses of deep learning to solve challenging problems and…
Original Post: Google’s Workshop on AI/ML Research and Practice in India
Posted by Olivier Bousquet, Principal Engineer, Google ZürichRecently, we announced the launch of a new AI research team in our Paris office. And today DeepMind has also announced a new AI research presence in Paris. We are excited about expanding Google’s research presence in Europe, which bolsters the efforts of the existing groups in our Zürich and London offices. As strong supporters of academic research, we are also excited to foster collaborations with France’s vibrant academic ecosystem.Our research teams in Paris will focus on fundamental AI research, as well as important applications of these ideas to areas such as Health, Science or Arts. They will publish and open-source their results to advance the state-of-the-art in core areas such as Deep Learning and Reinforcement Learning.Our approach to research is based on building a strong connection with the academic community; contributing to…
Original Post: Investing in France’s AI Ecosystem
[unable to retrieve full-text content]KDD-2018 invites submission of papers describing innovative research on all aspects of data science, and of applied papers describing designs and implementations for practical tasks in data science. Submissions due Feb 11.
Original Post: KDD 2018 Call for Research, Applied Data Science Papers
[unable to retrieve full-text content]This workshop will bring together experts in bio-acoustics with mathematicians and computer scientists with expertise in classification, clustering, and information theory to develop a unified approach. Apply by March 5.
Original Post: Bio-acoustic Structure, a NIMBioS Investigative Workshop, needs Data Scientists – Call for Applications