MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)

Our MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) team responded to the White House’s call for guidance on strategic considerations for a US AI Action plan. In our response we offered recommendations in five key areas based on our analysis of foundational computer science challenges, evolving market conditions, and the public policy context in which AI systems operate. Here are the key highlights of our of recommendations:   1) Continue support for funding basic AI research, which is essential to driving the next breakthroughs and keeping the US at the forefront of innovation, discovery, and real-world AI integration. Any reduction in funds will severely undermine the US’s ability to maintain a competitive edge and secure its future in AI.   2) Prioritize the discovery and development of new AI architectures, with the goal of achieving Artificial Super Intelligence, which will go beyond the Large Language Models by integrating real-world awareness, common-sense reasoning, and physical intelligence.   3) Increase investment in AI applications for scientific discovery to create high-efficiency, high-accuracy models that can accelerate breakthroughs in physics, biology, chemistry, medicine, and engineering.   4) Maintain a stable regulatory framework that ensures AI reliability, security, and legal compliance, leveraging existing sectoral regulations wherever possible.    5) Invest in job transition and retaining programs to ensure that workers displaced by AI can continue prospering and contributing to the economy.

Working in the Model-based Embedded and Robotic Systems (MERS) Group with Professor Brian Williams, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) PhD candidate Dominique Regli is designing human-activity recognition (HAR) systems which can support eldercare and senior living communities. “The world is currently experiencing a global aging phenomenon in which the proportion of people of the age of 65 is rapidly increasing, and we do not have the nursing support resources to appropriately respond to this,” Regli says. She is exploring HAR methods that are minimally invasive, privacy-preserving, and robust to empower a future of robotic home assistants. Read more about Dominique Regli and her research: https://bit.ly/3FCu9mz

AI chatbots have scoured almost the entire Internet to train themselves on how to write sentences & draw pictures, but it'll take much longer to get all that data to train robots. "I would say that these models are not going to work just the way they are being trained today," says MIT assoc. prof. Pulkit Agrawal in NPR: https://lnkd.in/eQiQigpG

✨ A huge welcome to our inaugural cohort of MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Diplomats! ✨ These nine passionate Massachusetts Institute of Technology alumni are helping expand CSAIL’s reach and increasing industry attention for MIT’s revolutionary AI and computer science research. CSAIL Diplomats serve as key advocates for innovation, bridging the gap between groundbreaking academic discoveries and real-world applications. The CSAIL Alliances Diplomat Program was created to connect MIT and CSAIL alumni with the cutting-edge research happening at CSAIL and amplify its impact in the business world. Learn more about the MIT CSAIL Alliances Alumni Diplomat Program: https://lnkd.in/e92PgV4U #CSAILAlliances #MIT #Innovation #CSAILDiplomats #TechLeadership

MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Associate Professor Jacob Andreas describes the “weird translation problem” that he’s working on, interpreting how sperm whales communicate, in the latest Alliances podcast. Listen: https://bit.ly/4hZL0y5

A new programming language from MIT could enable high-performance coding that can compete w/state-of-the-art libraries w/a few hundred lines of code, instead of tens or hundreds of thousands. Called "Exo 2," the approach enables reusable scheduling libraries external to compilers: https://bit.ly/3XMK2Nq

ICYMI: MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) PhD student Yung-Sung Chuang is passionate about exploring the limits of LLMs and wants to bring them closer to a human-like understanding of language. More: https://bit.ly/3ZafyWB

The best way to understand what might come next in the field of generative AI is knowing how the technology works now. Get hands-on experience with the current tools and technologies in Driving Innovation with Generative AI, featuring 12 Massachusetts Institute of Technology faculty. The course begins Monday, April 14. Register today: https://ow.ly/yXxL50Trca9

MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Assistant Professor Andreea Bobu has been passionate about computer science since second grade, when a simple coding exercise in Romania’s Informatics Club sparked a lifelong mission: using technology to make life easier. Her journey led her to Massachusetts Institute of Technology where she explored AI, probability, and medical imaging before pivoting to human-robot interaction. She now leads the Collaborative Learning and Autonomy Research (CLEAR) Lab, focusing on creating intelligent systems that enhance human performance. In a full-circle moment, Professor Bobu now teaches Introduction to Robotics—the very course that first introduced her to the field. Read more about Professor Bobu and her research: https://bit.ly/3FuAZKA

New MIT framework could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human: https://lnkd.in/ek3G8Sng