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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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Reprogramming domestic robots to possess a certain degree of common sense.

Aeronautical and astronautical engineering, Algorithms, Artificial Intelligence, Assistive technology, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Human-computer interaction, Machine learning, Research, Robotics, Robots, School of Engineering, UncategorizedMarch 25, 202434Views0Likes0Comments
Robots are becoming increasingly adept at handling complex household tasks, from cleaning messes to serving meals. However, their ability to handle unexpected disturbances or difficulties during these tasks has been a challenge. Common scenarios like a nudge or a slight mistake that deviates the robot from its expected path can cause the robot to restart…

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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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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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