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MIT Schwarzman College of Computing

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AI expedites 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 24, 202442Views0Likes0Comments
Companies like FedEx utilize intricate software to efficiently deliver holiday parcels, but these complex processes can often take hours or even days to complete. The software, known as a mixed-integer linear programming (MILP) solver, is often halted partway through by firms, accepting the best solution that can be gleaned in a particular timeframe, even if…

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What lies ahead 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, 202438Views0Likes0Comments
Speaking at MIT's "Generative AI: Shaping the Future" symposium, key speaker and iRobot co-founder Rodney Brooks warned against overstating the capabilities of Generative AI, a form of machine-learning that produces new content based on its training data. With examples like OpenAI's ChatGPT and Google’s Bard, Brooks cautioned of the consequence of believing that one technology…

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AI enhances the speed of resolving issues in complicated 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 24, 202437Views0Likes0Comments
Efficiently routing packages during the holiday season is a complex problem for companies like FedEx, a task often tackled with specialized software, known as mixed-integer linear programming (MILP) solvers. Although they break down the problem into smaller parts and use generic algorithms to find solutions, they could still take hours or days to complete. MIT and…

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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 23, 202437Views0Likes0Comments
Rodney Brooks, co-founder of iRobot and keynote speaker at MIT’s “Generative AI: Shaping the Future” symposium, warned attendees not to overestimate the capabilities of this emerging AI technology. Generative AI is used to create new material by learning from data they were trained on, with applications in art, creativity, functional coding, language translation and realistic…

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AI enhances the speed of resolving 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 23, 202433Views0Likes0Comments
While delivering holiday presents may seem straightforward for fictional characters like Santa Claus, for companies like FedEx, the task represents a complex optimization problem. To solve it, these companies usually utilize specialized software known as mixed-integer linear programming (MILP) solvers. These solvers break down large optimization problems into smaller pieces, utilizing generic algorithms to identify…

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What does the upcoming era entail for AI that can generate its own content?

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 23, 202438Views0Likes0Comments
During the "Generative AI: Shaping the Future" symposium held as part of MIT's Generative AI Week, experts discussed the opportunities and risks of generative AI, a type of machine learning that creates realistic outputs such as images, text, and code. The keynote speaker, Rodney Brooks, co-founder of iRobot and professor emeritus at MIT, warned against…

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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 23, 202439Views0Likes0Comments
Santa Claus delivers presents with the help of magic, but delivering holiday packages isn't quite as simple for companies like FedEx. These businesses often rely on advanced software called mixed-integer linear programming (MILP) solvers to route their deliveries. Yet, while these solvers break down complex problems into smaller, more manageable segments, it can still take…

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What does the future entail for AI that is capable of generating its own content?

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 22, 202438Views0Likes0Comments
Generative artificial intelligence (AI) possesses great potential but equally great risks if misused or overestimated, warned Rodney Brooks, co-founder of iRobot, at MIT’s "Generative AI: Shaping the Future" symposium. The event kicked off the university's Generative AI Week on 28 November and attracted hundreds of academia and industry representatives to the institution's Kresge Auditorium. Generative…

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AI enhances the speed of solving 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 22, 202440Views0Likes0Comments
The logistics of delivering holiday packages by companies such as FedEx requires specialized software for efficient routing, given the immense complexity of the optimization problem. The software currently in use, known as a mixed-integer linear programming (MILP) solver, often takes days to arrive at a solution, and even then, the companies have to accept solutions…

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What is the outlook for generative AI in the future?

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 22, 202441Views0Likes0Comments
At the “Generative AI: Shaping the Future” symposium held on Nov. 28, Rodney Brooks, iRobot co-founder and a keynote speaker, cautioned attendees against overestimating the capabilities of generative AI. Noting that “No one technology has ever surpassed everything else”, Brooks stressed that flippant assumptions about the inferred abilities of generative AI could lead to failure.…

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A single step allows AI to produce high-grade images at a speed 30 times quicker.

Algorithms, Artificial Intelligence, Arts, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Data, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 22, 202439Views0Likes0Comments
In the age of artificial intelligence, computers can generate "art" using diffusion models. However, this often involves a complex, time-consuming process requiring multiple iterations for the algorithm to perfect the image. MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have now launched a new technique that simplifies this process into a single step using…

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A fresh approach relies on collective input from the public to assist in the education of robots.

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, MIT-IBM Watson AI Lab, Research, Robots, UncategorizedMarch 21, 202436Views0Likes0Comments
A team of researchers from MIT, Harvard University, and the University of Washington have developed a novel reinforcement learning technique using crowdsourced feedback. The technique allows AI to learn complex tasks more quickly and without relying on an expertly designed reward function. The conventional reward function designed by dedicated human experts has been replaced by…

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