SystemsThatLearn@CSAIL Initiative Launch
On March 29, 2017, MIT CSAIL launched the newest initiative, SystemsThatLearn@CSAIL. The research initiative will focus on accelerating the development, deployment and evolution of large-scale software systems that incorporate machine learning and artificial intelligence. The launch featured member industry insights and a panel discussion with the STL@CSAIL faculty.
To review the recording, please visit: SystemsThatLearn@CSAIL Launch
The next decade will usher in a new frontier of sophisticated systems that perform complex “human-like” tasks, with complex inferences and predictions. With data gathered from diverse sensors and mobile devices, computing power spread across embedded devices and datacenters, as well as ubiquitous network connectivity, we will need new tools to realize the potential of learning systems. We are already seeing practical applications of these systems in areas such as autonomous vehicles and personalized health care that have the potential to transform industries and societies.
The goal of the Systems That Learn initiative is to accelerate the development of systems and applications that learn. We intend to accomplish this goal through combining our expertise in Systems and Machine Learning to create new applications for understanding complex relationships from the avalanche of data available today. Systems That Learn has been created to to enable cross-collaboration and accelerate development of innovative human-like systems to serve the world.
Our work will leverage many world-class faculty in MIT Computer Science and Artificial Intelligence Laboratory, who have pioneered the field of machine learning and systems, towards advancing the state-of-the-art with select industry partners to address the hardest real-world business problems. MIT is uniquely positioned to accomplish this, through the rigorous research of our faculty coupled with our tradition of collaborating with industry to ensure our work is both relevant and practical. We anticipate many opportunities for direct, active collaboration and knowledge sharing though events, projects and directed research.
The goal of SystemsThatLearn@CSAIL membership is to promote in-depth interactions between industry and academia. Member companies will have the opportunity to be exposed to multiple research projects that span the full spectrum of machine learning/artificial intelligence and analytics. We will collaborate closely with industry to provide real-world applications and drive impact. Our team of world-class researchers covers the full spectrum of research in systems and machine learning.
Each member company will have one representative on the board. The board will advise the initiative on industry needs, provide feedback on existing research and advise future research direction through seeded projects. This board will help shape the priorities of the initiative.
Access New Research
Access in-depth exploration of CSAIL research in AI, machine learning and data analytics. As part of this initiative, we will leverage the work of 15+ existing research projects. Members will have unprecedented access to the research and the research teams.
Early Access to New Tools
Test application of tools developed to real-world situations and explore new projects.
Access tools created as part of the initiative via MIT open source license through the CSAIL Living Lab & Technology Portal.
Participate in in-depth interactions and shared learning on topics of particular interest to each company. Close interaction with the researchers engaged in what matters most to your company.
Access additional research groups, researchers, and students within MIT’s Computer Science and Artificial Intelligence Laboratory through CSAIL’s Alliance Program (CAP) at the Affiliate level.
Connect with the latest research from across CSAIL through workshops, technical talks, lectures and students poster sessions. Access the two-day lab-wide Annual Meeting and let your geek flag fly.
Members of your company are welcome to visit CSAIL for a private lab visit, tour, demos and meetings to network with faculty, students and other members throughout the year.
Student Profile Book
Profiles of students working in the Machine Learning, Artificial Intelligence, and Analytics space, published yearly.
Job Postings & Advertisement
Members have the opportunity to advertise open position announcements within CSAIL, as well as having company logos on the CSAIL Alliance Program site and on conference material.