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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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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, 202436Views0Likes0Comments
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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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, 202432Views0Likes0Comments
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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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, 202438Views0Likes0Comments
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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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, 202439Views0Likes0Comments
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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New algorithm delivers detailed understanding for computer vision.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Imaging, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 19, 202437Views0Likes0Comments
MIT researchers have developed an algorithm called FeatUp that enables computer vision algorithms to capture both high-level details and fine-grained minutiae of a scene simultaneously. Modern computer vision algorithms, like human beings, can only recall the broad details of a scene while the more nuanced specifics are often lost. To understand an image, they break…

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Method allows AI in peripheral devices to continuously update its knowledge over time.

Algorithms, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Internet of things, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Mobile devices, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedMarch 7, 202439Views0Likes0Comments
Machine learning models are widely used today in smart devices like smartphones, with diverse applications like autocorrecting keyboards or improved chatbot responses. However, fine-tuning these models requires considerable computational resources and transfers of data to and from cloud servers – which can pose both energy and security issues. The team of researchers from MIT and…

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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, 202440Views0Likes0Comments
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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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, 202435Views0Likes0Comments
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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A versatile approach to assist artists in enhancing animation.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedMarch 7, 202438Views0Likes0Comments
MIT researchers have developed a new tool that provides better control to animators in shaping their characters. The new technique works by generating mathematical functions, known as barycentric coordinates, that describe how 2D and 3D shapes in animations can move, stretch, and deform in space. By using these functions, an animator can tailor the movement…

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Numerous AI systems assist robots in carrying out intricate strategies with greater clarity.

Algorithms, Artificial Intelligence, Computer science and technology, Computer vision, Data, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, Robotics, School of Engineering, UncategorizedMarch 7, 202438Views0Likes0Comments
MIT's Improbable AI Lab has developed a novel multimodal framework for artificial intelligence (AI) called the Compositional Foundation Models for Hierarchical Planning (HiP). The aim of this system is to help robots conduct complex tasks that involve numerous smaller steps, from household chores to more elaborate industrial processes. Traditionally, AI systems have required paired visual,…

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