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MIT Schwarzman College of Computing

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Bridging the gap between design and manufacturing for optical devices.

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, UncategorizedApril 3, 202434Views0Likes0Comments
Photolithography, a process used to etch features onto surfaces like computer chips and optical lenses, often results in devices that underperform due to tiny variations during manufacturing. To address this, researchers from MIT and the Chinese University of Hong Kong have employed machine learning to create a digital simulator that replicates a specific photolithography manufacturing…

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An automated setup instructs users about the appropriate timing for cooperation 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, UncategorizedApril 3, 202437Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that educates a user on when to trust an AI assistant's recommendations. During the onboarding process, the user practices collaborating with the AI using training exercises and receives feedback on their and the AI's performance. This system led to a 5% improvement…

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MIT researchers investigating the influence and uses of generative AI have received the second installment of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedApril 3, 202444Views0Likes0Comments
Last summer, MIT called upon the academic community to provide papers that suggest effective approaches and policy recommendations in the field of generative AI. Expectations were surpassed when 75 proposals were received. After reviewing these submissions, the institution funded 27 of the proposed projects. During the fall, the response to a second call for proposals…

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A novel computational method may simplify the process of engineering beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedApril 3, 202434Views0Likes0Comments

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AI hastens the resolution of complex issues or situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 27, 202437Views0Likes0Comments
Santa Claus can deliver presents worldwide in one night, but for companies like FedEx, this task isn't so simple - and it is so complex, dedicated software is often used to solve it. Known as a mixed-integer linear programming (MILP) solver, the software breaks down this vast optimization problem into smaller pieces and then employs…

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AI enhances the resolution of issues in intricate situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 26, 202436Views0Likes0Comments
Companies like FedEx find the task of efficiently routing holiday packages massively complex, often requiring the use of specialized software to find a solution. This software, called a mixed-integer linear programming (MILP) solver, is used to break down large optimization problems into smaller bits and find the best solution using algorithms. However, this process can…

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AI hastens the resolution of difficult situations through problem-solving.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 26, 202440Views0Likes0Comments
Numerous companies like FedEx grapple with the sophisticated problem of optimising the routing of holiday packages. Specialised software known as a mixed-integer linear programming (MILP) solver is often used to split this massive optimisation issue into smaller pieces, allowing generic algorithms to locate the most suitable solution. This time-consuming process sometimes forces companies to settle…

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AI enhances the resolution of issues in intricate situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 25, 202435Views0Likes0Comments
The task of optimizing the delivery of holiday packages is a complex issue for logistics companies like FedEx, which often leverages specialized software known as a mixed-integer linear programming (MILP) solver. This software breaks down complex optimization problems into smaller parts and employs generic algorithms to find the best solutions. However, this process can take…

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Surprisingly, large language models utilize a fairly straightforward method to access stored information.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 25, 202434Views0Likes0Comments
Large language models (LLMs), such as those used in AI chatbots, are complex, and scientists are still trying to understand how they function. Researchers from MIT and other institutions conducted a study to understand how these models retrieve stored knowledge. They found that LLMs usually use a simple linear function to recover and decode information.…

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What is the future outlook 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 25, 202437Views0Likes0Comments
At the "Generative AI: Shaping the Future" symposium, kickstarting MIT's Generative AI Week, iRobot co-founder and keynote speaker, Rodney Brooks, warned attendees not to overly idealise the potential of this emerging technology. Both OpenAI's ChatGPT and Google's Bard are examples of increasingly powerful tools underpinned by generative AI. Brooks emphasised that the unsubstantiated hype around…

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AI speeds up solution-finding in intricate situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 25, 202436Views0Likes0Comments
Efficiently routing holiday packages is an intricate computational problem for delivery companies such as FedEx. So complex is the problem that companies often implement specialized software, termed a mixed-integer linear programming (MILP) solver. Yet, the solver may take prolonged times to offer a solution, leading companies to conclude midway, settling for suboptimal solutions bounded by…

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What does the future entail for generative artificial intelligence?

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 24, 202437Views0Likes0Comments
iRobot co-founder and MIT Professor Emeritus, Rodney Brooks, warned about overestimating the capabilities of generative AI during a keynote speech at the "Generative AI: Shaping the Future” symposium. This marked the start of MIT’s Generative AI Week, which aimed to examine the potential of AI tools like OpenAI’s ChatGPT and Google’s Bard. Generative AI refers to…

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