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Cloud robotics intro

Published on May 23, 2014

Ken Goldberg, UC Berkeley and Matei Ciocarlie, Google

Ken Goldberg is the craigslist Distinguished Professor of New Media and Professor of Industrial Engineering and Operations Research (IEOR) at the University of California, Berkeley. He also holds an appointment in the Department of Radiation Oncology at the University of California, San Francisco. He is an artist, writer, inventor, and researcher in the field of robotics and automation.

In his visit to Google he joins a his friend Matei Ciocarlie to discuss "Cloud Robotics", a new paradigm that embraces the Internet. Ken took this concept and applied it to Google Goggles, a cloud-based object recognition platform. By adding grasp-planning information on top of the visual database, he's helping robotic systems not only recognize objects, but also learn ways to grasp and interact with them.
 

Cloud Robotics with Ken Goldberg

Published on May 23, 2014

Ken Goldberg is the craigslist Distinguished Professor of New Media and Professor of Industrial Engineering and Operations Research (IEOR) at the University of California, Berkeley. He also holds an appointment in the Department of Radiation Oncology at the University of California, San Francisco. He is an artist, writer, inventor, and researcher in the field of robotics and automation.

Cloud Robotics has potential to improve robot performance in at least five ways: 1) Big Data: indexing a global library of images, maps, and object data, 2) Cloud Computing: parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Open-Source / Open-Access: humans sharing code, data, algorithms, and hardware designs, 4) Collective Robot Learning: robots sharing trajectories, job planning, and outcomes, and 5) Crowdsourcing and call centers: offline and on-demand human guidance for evaluation, learning, and error recovery.
 

The enterprise data cloud, Mick Hollison (Cloudera) Strata Data Conference UK 2019

Uploaded on May 1, 2019

The last decade has seen incredible changes in our technology. The advent of big data and powerful new analytic techniques, including machine learning and AI, means that we understand the world in ways that were simply impossible before. The simultaneous explosion of public cloud services has fundamentally changed our expectations of technology: it should be fast, simple, and flexible to use.

Most enterprises now operate across multiple public clouds and in their own data centers and want the same flexibility and convenience they get in the public cloud, no matter where their data lives or their applications run. We’ve reached the point that the “enterprise data cloud” is a necessity. Mick Hollison describes the key capabilities that such a system requires and why hybrid and multi-cloud is the future for organizations that want to capitalize on the potential of machine learning and AI.
 

What is multicloud? How do you manage it?

Published on May 29, 2019

Multicloud management is the ability to manage multiple data centers or clouds—public or private—as if in a single environment. With a majority of enterprises using three or more clouds, it’s become the key to enterprise agility. But working across multiple clouds from multiple vendors poses challenges. Operations Managers and SREs strive for operational efficiency and the means to meet key SLOs and SLAs. The three keys are visibility, governance and automation.
 
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