Please go to our Facebook page to see photos from our best retreat yet!
(This article has originally been published on Medium.com.) Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. And, unfortunately, it distracts us. There is a different narrative that one can …
The online version of our April 2018 Newsletter can be found here.
Prof. Ion Stoica and Xin Jin, a former postdoc in RISELab (now a faculty at John Hopkins University), have received the best paper award for their paper on NetChain which shows that it is possible to do coordination in distributed systems at line speed. You can read more about it at the official NSDI link.
UC Berkeley’s pathbreaking entry-level course on the Foundations of Data Science (Data 8) is launching on edX on April 2. This makes the fastest-growing class in UC Berkeley history available to everyone. Foundations of Data Science teaches computational and inferential thinking from the ground up. It covers everything from testing hypotheses, applying statistical inferences, visualizing distributions and drawing conclusions—all while coding in Python and using real world data sets. The course is taught by award-winning Berkeley professors and designed by a team of faculty working together across Berkeley’s Computer Science and Statistics Departments, led by RISE faculty Michael Jordan. The three 5-week online courses cover: Foundations of Data Science: Computational Thinking with Python, starting on April 2, teaches the basics …
You can read the full article here. For more info on Prof. Popa, please go to her page.
Our biggest retreat so far (182 registered attendees!) happened January 10 – 12, 2018, at Monterey Tides hotel. We had lots of productive interactions (presentations, meeting, poster sessions), but also managed to have some fun kayaking at the Elkhorn Slough! You can see the photos on our Facebook page.
Berkeley-based startup incubator and venture capital fund The House is launching an AI-specific initiative backed by Google that is meant to take advantage of the technical and academic expertise in the field coming out of UC Berkeley. The faculty involved in the program include Databricks co-founder and UC Berkeley professor Ion Stoica, Berkeley Artificial Intelligence Research lab co-director Trevor Darrell and UC Berkeley professor Michael Jordan, one of the most influential computer scientists working in AI. You can read the whole article here.
Alibaba Group launched a massive global research program, “Alibaba DAMO Academy”, by committing $15B in funding. The Academy aims to increase technological collaboration worldwide, advance the development of cutting-edge technology, and strive to make the world more inclusive by narrowing the technology gap. The Academy will cooperate with the University of California, Berkeley through its RISE Lab on areas such as secured real-time computing. For more information, please read this article.
RISELab’s Raluca Ada Popa gave a keynote talk on security for machine learning systems at the GE Industrial Machine Learning Workshop 2017. https://wise.io/imlw17/ Her talk discussed security threats in deploying machine learning systems as well as three promising approaches to address some of these: secure multi-party computation, differential privacy and hardware enclaves.
The RISELab faculty—who cover the fields of machine learning, systems, security, and hardware—have just published a vision paper on systems challenges for AI. They argue that future AI systems must make timely and safe decisions in unpredictable environments, be robust against sophisticated adversaries, and process ever increasing amounts of data across organizations and individuals without compromising confidentiality. These challenges will be exacerbated by the end of the Moore’s Law, which will constrain the amount of data these technologies can store and process. They propose several open research directions in systems, computer architecture, and security that can address these challenges and help unlock AI’s potential to improve lives and society. Link to the press release: https://news.berkeley.edu/2017/10/16/berkeley-experts-on-how-to-build-faster-safer-and-more-secure-ai-systems/
Link: https://www.youtube.com/playlist?list=PLTPaZLQlNIHqJf8GYCly6m2Pl8pBqPLpR. Please subscribe to our channel!
This is the YouTube Live Stream link for Friday, 9/8/17: https://www.youtube.com/watch?v=JKwCXafHmgg
PLEASE NOTE: tutorials are not Live Streamed – they will be made available on the event page at a later date
Apologies for the earlier problems; the live stream link is working now: https://www.youtube.com/watch?v=lmQOEjymzUk
For the latest agenda updates and link to the Live Stream (starting at 9 AM), please go to the event website: https://risecamp.berkeley.edu/.
In case you missed it (it went out on August 1, 2017), you can still read a web copy here. If you’d like to be added to our mailing list, please fill out this form.
Meet Ray, the Real-Time Machine-Learning Replacement for Spark
Join RISELab at NSDI’17 on March 27th through the 29th in Boston. There we will be presenting the Opaque and Clipper systems. Please see the below links to read the final versions of the papers and try pre-release versions of the software and check out slides and videos from their previous talks. Opaque system: The paper is already available here Software is available here Slides and video from a previous talk here Clipper system: The paper is available here Software is available here Slides and video from a previous talk here