In WIRED: MIT assistant professor and CSAIL member Yoon Kim says that the ways LLMs solve problems is mysterious at the moment & their step-by-step reasoning process could differ from human intelligence: “These are systems that would be potentially making decisions that affect many, many people,” he says. “The larger question is, do we need to be confident about how a computational model is arriving at the decisions?”
MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Higher Education
Cambridge, MA 154,202 followers
MIT CSAIL pioneers approaches to computing that improve how people work, play and learn.
About us
The MIT Computer Science and Artificial Intelligence Laboratory – known as CSAIL – is the largest research laboratory at MIT and one of the world’s most important centers of information technology research. CSAIL has played a key role in the computer revolution and developments such as time-sharing, massive parallel computers, public key encryption, mass commercialization of robots, and much of the technology underlying the ARPANet, Internet and the World Wide Web. CSAIL’s focus is developing the architecture and innovative applications for tomorrow’s information technology. Our research yields long-term improvements in how people live and work. CSAIL members (former and current) have launched more than 100 companies, including 3Com, Lotus Development Corporation, RSA Data Security, Akamai, iRobot, Meraki, ITA Software, and Vertica. The Lab is home to the World Wide Web Consortium (W3C), Wireless@MIT, BigData@CSAIL, Cybersecurity@CSAIL and the MIT Information Policy Project (IPP). Connecting to CSAIL CSAIL Alliances is your organization's pathway to CSAIL connections and serves as a gateway into the lab for industry and governmental institutions seeking closer engagement to the work, researchers and students of CSAIL. The program provides organizations with a proactive and comprehensive approach to developing strong connections with all CSAIL has to offer. Leading organizations come to CSAIL to learn about our research, to recruit talented graduate students, and to explore collaborations with our researchers. Through this program, we are able to better provide our members with access to our latest thinking and our deep pool of exceptional human and informational resources. For more information, please visit: http://cap.csail.mit.edu/
- Website
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http://www.csail.mit.edu/
External link for MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
- Industry
- Higher Education
- Company size
- 1,001-5,000 employees
- Headquarters
- Cambridge, MA
- Type
- Nonprofit
- Founded
- 2003
- Specialties
- Artificial Intelligence, Systems, and Theory
Locations
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Primary
32 Vassar Street
Cambridge, MA 02139, US
Employees at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Updates
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Generative AI is creating cutting-edge solutions that will revolutionize industries and empower businesses to thrive in the digital age. Our new six-week course leverages industry case studies, hands-on work with generative AI tools, and the latest thinking from 12 MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) faculty members to equip you with the knowledge and skills necessary to navigate the intricate world of generative AI. Use code CSAILINK10 to receive 10% off course registration. Everyone using the CSAILINK10 discount will also receive a copy of "The Heart and the Chip" by Professor Daniela Rus upon completion of the course. The course begins October 15. View the week-by-week schedule here and enroll today: https://ow.ly/CX6Z50Tmjo1
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Andrew Lo, Professor of Finance at MIT Sloan School of Management and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), believes that AI has the potential to democratize financial advice and assist everyday consumers in making crucial financial decisions. His research focuses on tackling the challenges associated with integrating AI into finance, such as addressing issues of responsibility and collaborating with financial advisors to ensure the practical utility of these tools. Professor Lo also serves as the faculty director for the FinTechAI@CSAIL research initiative. Hear from Prof. Lo in conversation with host Kara Miller in the latest Alliances podcast: https://bit.ly/4gbHboY
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An MIT Admissions video from the early '90s #tbt
MIT: The Movie (Redux)
https://www.youtube.com/
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🎉 Congratulations to Sophie Xuan for receiving the Outstanding Short Paper Award at the IEEE High Performance Extreme Computing Conference (HPEC)! Sophie, a sophomore majoring in 6-3 Computer Science and Engineering (EECS) at MIT, worked at JuliaLab this summer under the supervision of Professor Alan Edelman & is mentored by Rabab Alomairy, Ph.D. & Evelyne Ringoot. Her research focused on designing & implementing hardware-agnostic linear algebra functions in Julia, demonstrating her innovation & dedication. Her award-winning paper, titled "Synthesizing Numerical Linear Algebra using Julia," presents efficient implementations of LAPACK/BLAS functions in Julia. Sophie demonstrated how a single generic API can support various data types & hardware (CPU and GPU) without sacrificing performance. By leveraging Julia’s LLVM-based compilation & multiple-dispatch features, she created flexible & future-proof alternatives to traditional libraries. Notably, her implementation of functions like orthogonal matrix factorization highlighted the potential of Julia to match or surpass the performance of legacy libraries like LAPACK. Sophie will present her paper at the IEEE High Performance Extreme Computing Conference at 12 PM on September 27th 🌟 Agenda: https://lnkd.in/eiNM5y-n #HPEC #JuliaLang #NumericalComputing #MIT #JuliaLab
IEEE HPEC 2024 Prelim Agenda
https://ieee-hpec.org
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MIT professor on how LLMs could eventually provide trustworthy financial advice. Full video: https://bit.ly/3XNweCH
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Can LLMs learn to "phone a friend?" MIT CSAIL’s new "Co-LLM" algorithm can pair a general-purpose base LLM w/a more specialized model & help them work together. It reviews each token & sees where it needs to call upon an expert, leading to more accurate & efficient replies to medical prompts and math & reasoning problems: https://bit.ly/4gqx0wS Full X thread: https://bit.ly/3TBmusL
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Please find below a list of new resources highlighting research from across the lab.
September 2024 Newsletter
MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) on LinkedIn
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MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) PhD student Marianne Rakic works in the lab's Clinical and Applied Machine Learning Group. Rakic’s most recent project, Tyche, is a medical image segmentation model that aims at generalizing new tasks and capturing uncertainty in the medical image. “In biomedical imaging, segmentation consists in annotating pixels from an important structure, for example an organ, a lesion, or a cell part,” Rakic said. “It is a central task for both biomedical researchers and clinicians, and is typically solved with neural networks.” Rakic said that models like Tyche can help clinicians and researchers capture the inherent ambiguity of their data and limit their dependency on model retraining. Learn more about Marianne Rakic and her research: https://bit.ly/3TwtFT5
Marianne Rakic
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Generative AI represents a seismic shift in the way we approach tasks and projects. To ensure that professionals have a comprehensive understanding of these technologies, MIT xPRO has created the six-week online course: Driving Innovation with Generative AI. We invite you to a free webinar with Massachusetts Institute of Technology Prof. Antonio Torralba to learn more about this course. By attending the live webinar, you will also be able to participate in the Q&A following the presentation. The webinar occurs tomorrow, Tuesday, September 17 at 1 p.m. EST. Register: https://ow.ly/GMs950Tmmei
MIT xPRO Generative AI Webinar
learn-xpro.mit.edu