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What does the future have in store for generative AI?

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, School of Engineering, Special events and guest speakers, Staff, Students, UncategorizedMarch 7, 202476Views0Likes0Comments
The "Generative AI: Shaping the Future" symposium, the kickoff event of MIT’s Generative AI Week, drew hundreds of attendees both from academia and industry. Rodney Brooks, iRobot co-founder and keynote speaker, warned attendees against uncritically overestimating the capabilities of generative AI, a technology increasingly powering tools such as OpenAI’s ChatGPT and Google’s Bard. Generative AI…

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Eric Evans is set to resign from his role of director at the MIT Lincoln Laboratory.

Administration, Artificial Intelligence, Center for International Studies, Collaboration, Community, Cybersecurity, Department of Defense (DoD), Department of Political Science, Leadership, Lincoln Laboratory, Machine learning, School of Engineering, School of Humanities Arts and Social Sciences, Security studies and military, Staff, UncategorizedMarch 7, 202475Views0Likes0Comments
Eric Evans is stepping down as the director of MIT Lincoln Laboratory on July 1, 2024. He has led the lab through 18 years of technology research and development for national advancements, serving as an influential advisor to senior government officials on technology strategy. Following his departure, Evans will adopt the role of fellow in…

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Engineers from MIT have devised a method to decipher the behavior of material surfaces.

Artificial Intelligence, Chemistry, Department of Defense (DoD), DMSE, Machine learning, Materials science and engineering, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 7, 202485Views0Likes0Comments
MIT researchers have developed a machine learning-based method for designing new compounds or alloys for use as catalysts in chemical reactions. Traditional methods of designing such materials rely on static observations of a single configuration, out of millions of possibilities, and the intuition of experienced chemists. However, the new method employs machine learning algorithms to…

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The automated system instructs users on appropriate timings for collaboration with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 7, 202468Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an onboarding process that efficiently combines human and AI efforts. The system educates a user when to collaborate with an AI assistant and when not. This method can find situations when a user trusts the AI model's advice, but the model is incorrect. The…

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MIT team publishes research papers on the management of AI.

Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Government, Machine learning, MIT Schwarzman College of Computing, Policy, School of Engineering, Technology and society, UncategorizedMarch 7, 202468Views0Likes0Comments
A committee of leaders and scholars from the Massachusetts Institute of Technology (MIT) has released a series of policy papers providing a regulatory framework for artificial intelligence (AI). The goal is to enable the US to maintain its leadership position in AI, preventing potential harm from novel technologies and promoting their societal benefits. The central…

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MIT’s Generative AI Week promotes conversation among different fields.

academics, Algorithms, Architecture, Artificial Intelligence, Biology, Civil and environmental engineering, Comparative Media Studies/Writing, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, DMSE, EAPS, Education, Electrical Engineering & Computer Science (eecs), Ethics, Faculty, Health, Laboratory for Information and Decision Systems (LIDS), Machine learning, Media Lab, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, MIT Sloan School of Management, Robotics, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Special events and guest speakers, Staff, Students, teaching, Technology and society, UncategorizedMarch 7, 202475Views0Likes0Comments
In late November, Massachusetts Institute of Technology (MIT) held a Generative AI Week involving faculty, staff, and students from the institution. The event served as a platform to discuss the opportunities and important applications of generative artificial intelligence technologies across varied disciplines. The week's agenda included a main symposium and four subject-specific symposia. MIT President…

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A technology expert in computing is extending the limits of geometrical studies.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedMarch 7, 202472Views0Likes0Comments
Justin Solomon, an associate professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), is making use of modern geometric techniques to address intricate problems, many of which don't appear to be linked to shapes. He extrapolates from the foundations laid more than 2,000 years ago by the…

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Bridging the gap between design and production of optical gadgets.

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedMarch 7, 202477Views0Likes0Comments
Researchers from MIT and the Chinese University of Hong Kong have developed a digital simulator that seeks to improve photolithography's precision, often used in computer chips and optical devices manufacture. The process uses light to etch intricate designs onto surfaces, but minor discrepancies often cause devices' final performance to deviate from designers' initial intentions. The…

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Deep neural networks exhibit potential in modelling human auditory systems.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedMarch 7, 202480Views0Likes0Comments
MIT researchers have been utilizing computational models derived from deep neural networks which mimic the structure and function of the human auditory system, a development that could help in the design of better hearing aids, cochlear implants, and brain-machine interfaces. This represents a significant step in understanding how the human brain processes sound and how…

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Three students from MIT have been chosen as the first fellows for the MIT-Pillar AI Collective.

Artificial Intelligence, Awards, Computer science and technology, Data, Deshpande Center, Electrical Engineering & Computer Science (eecs), Graduate, Harvard-MIT Health Sciences and Technology, honors and fellowships, Innovation and Entrepreneurship (I&E), Machine learning, postdoctoral, School of Engineering, Students, UncategorizedMarch 7, 202480Views0Likes0Comments
The MIT-Pillar AI Collective has selected Alexander Andonian, Daniel Magley, and Madhumitha Ravichandra as its three inaugural fellows for the fall 2023 semester. All are on the cusp of concluding a master’s or PhD program and will aid in conducting research in artificial intelligence (AI), machine learning, and data science, backed by the program. The…

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Computational model accurately represents the transient transition states in chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedMarch 7, 202469Views0Likes0Comments
Chemists often struggle to predict the outcome of a chemical reaction as it depends on the so-called "transition state," a fleeting moment into which molecules enter and from which they can never return unchanged. The challenge lies in the fact that the transition state is extremely ephemeral and difficult to capture in real-world experiments. This…

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