Register for the Machine Learning in Business course taught by industry thought leaders from CSAIL and MIT Sloan School of Management. The upcoming machine learning course will provide a baseline to basic machine learning concepts and take you beyond primary application into effective implementation. The business course will demonstrate ways to develop sound machine learning strategies and empower you to apply cogent machine learning models within your current business structure. The course begins Wednesday, October 16. Register here: https://bit.ly/3KPLTIr
MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Higher Education
Cambridge, MA 155,747 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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Interested in software performance engineering? Professor Charles E. Leiserson and his team are passionate about improving performance engineering and educating the next generation of performance engineers. Share your feedback with the team and help advance this key research.
I am excited to be helping Charles E. Leiserson, John Owens, and others to launch Fastcode, an NSF-funded open-source community dedicated to advancing software performance engineering. If you care about software running fast (or otherwise consuming few resources), I would love to hear why performance engineering matters to you. Please share your story by signing up for a 10-minute interview at https://lnkd.in/eKCRvsPR. Thank you.
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MIT CSAIL researchers recently helped introduce a more efficient, less wasteful, and higher-precision technique that leverages heat-responsive materials to print objects that have multiple colors, shades, and textures in one step: https://lnkd.in/eYKGaX-k
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ICYMI: Dive into the world of digital security with MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Professor Vinod Vaikuntanathan. From safeguarding against quantum computing's looming threat to uncovering hidden risks in machine learning, his work is shaping the future of cryptography. Read more about Prof. Vaikuntanathan and his current research: https://bit.ly/3y3QjdC
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Applying generative AI to coding not only helps programmers work more efficiently but can also lend specific skills and capabilities when working collaboratively with a person. Learn about the strengths and pitfalls of using GenAI in coding from 12 Massachusetts Institute of Technology faculty in the Driving Innovation with Generative AI course. Use code LASTCHANCECSAIL to receive 15% off course registration. Everyone using the LASTCHANCECSAIL discount will also receive a copy of "The Mind's Mirror: Risk and Reward in the Age of AI" by Professor Daniela Rus upon completion of the course. The course begins October 15, so register today. Learn More and Register: https://ow.ly/f6Oi50TC6A1
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MIT CSAIL researchers recently revealed how humans & AI detect faces differently. Read more about their work in "Imagining faces in tree trunks and your morning eggs? AI can see them, too" in Science Magazine.
Imagining faces in tree trunks and your morning eggs? AI can see them, too
science.org
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Founding Director of the Massachusetts Institute of Technology Internet Policy Research Initiative MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Senior Research Scientist Daniel Weitzner says a lack of visibility about how personal data is being used is leading to an erosion of customer trust. However, companies increasingly need to leverage data for analytic advantage, generative AI applications, and more. His research focuses on solutions which would empower consumers with visibility and control of their data, facilitating a future of accountability and trust. Hear more about Weitzner's work in a conversation with Kara Miller in the latest Alliances podcast: https://bit.ly/4eUjIHq
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Today we celebrate all women in STEM in honor of #AdaLovelaceDay. Read about some of the innovative research from MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) faculty, researchers, and students: https://bit.ly/3V2hqzm
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Geoffrey Hinton, whose work in neural networks has led many to call him the “Godfather of AI”, co-wins the Nobel Physics Prize for AI research: https://bit.ly/47X7H1u
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For robots, simulation is a great teacher for learning multi-step tasks — especially compared to how long it takes to collect real-world training data. Still, it takes considerable time for humans to create simulations to teach robots new tasks. Cutting that time in half, “GenSim2” framework uses multimodal & reasoning large language models to supersize training data for robots: https://lnkd.in/ew-GtZju