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AI model recognizes specific stages of breast tumor that may evolve into aggressive cancer.

Artificial Intelligence, Broad Institute, Cancer, Computer science and technology, Diagnostics, Disease, Electrical Engineering & Computer Science (eecs), Health, Health care, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 24, 202437Views0Likes0Comments

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The AI model is capable of recognizing specific stages of breast tumors that have a high probability of developing into invasive cancer.

Artificial Intelligence, Broad Institute, Cancer, Computer science and technology, Diagnostics, Disease, Electrical Engineering & Computer Science (eecs), Health, Health care, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 23, 202437Views0Likes0Comments
Ductal carcinoma in situ (DCIS), a type of tumor that can develop into an aggressive form of breast cancer, accounts for approximately 25% of all breast cancer diagnoses. DCIS can be challenging for clinicians to accurately categorize, leading to frequent overtreatment for patients. A team of researchers from the Massachusetts Institute of Technology (MIT) and…

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Methods for evaluating the dependability of a multi-functional AI model prior to its implementation.

Algorithms, Artificial Intelligence, Computer science and technology, Data, Human-computer interaction, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedJuly 16, 202433Views0Likes0Comments
Foundation models, or large-scale deep-learning models, are becoming increasingly prevalent, particularly in powering prominent AI services such as DALL-E, or ChatGPT. These models are trained on huge quantities of general-purpose, unlabeled data, which is then repurposed for various uses, such as image generation or customer service tasks. However, the complex nature of these AI tools…

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A new AI model has the potential to enhance procedures in a robot-operated warehouse.

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, Research, Robots, School of Engineering, UncategorizedJune 10, 202432Views0Likes0Comments
MIT researchers have developed a deep-learning model to improve the efficiency of warehouse robots. The team used a neural network architecture to encode features including the robots' paths, tasks, and obstacles in the warehouse. This enabled the model to predict where congestion was most likely to occur and take measures to counteract it. The groundbreaking method…

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A new AI model has the potential to improve efficiency in automated warehouse processes.

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, Research, Robots, School of Engineering, UncategorizedJune 10, 202432Views0Likes0Comments
MIT researchers have designed an artificial intelligence solution to help robotic warehouses operate more efficiently. Automated warehouses, which employ hundreds of robots to pick and deliver goods, are becoming more commonplace, especially in industries such as e-commerce and automotive production. However, coordinating this robot workforce to avoid collisions, while also maintaining a high operational pace,…

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A fresh AI model has the potential to enhance efficiency in an automated warehouse operation.

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, Research, Robots, School of Engineering, UncategorizedJune 9, 202436Views0Likes0Comments
In an enormous robotic warehouse, hundreds of robots zip back and forth, picking up items and delivering them to human workers for packing and shipping. This is becoming an increasingly common scene in various industries, from e-commerce to automotive manufacturing. However, managing these large numbers of robots, ensuring they reach their destinations effectively, and avoiding…

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A new AI model could enhance efficiency in an automated warehouse.

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, Research, Robots, School of Engineering, UncategorizedJune 8, 202433Views0Likes0Comments
In the growing field of warehouse automation, managing hundreds of robots zipping through a large warehouse is a logistical challenge. Delivery paths, potential collisions and congestion all pose significant issues, making the task a complex problem that even the best algorithms find hard to manage. To solve this, a team of MIT researchers has developed…

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A new AI model could potentially enhance efficiency in a robotic warehouse.

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, Research, Robots, School of Engineering, UncategorizedJune 7, 202429Views0Likes0Comments
In order to improve efficiency in large-scale robotic warehouses, a team of researchers from the Massachusetts Institute of Technology (MIT) have developed a deep learning model which assists in navigating robots to decongest warehouse floors. The way this model works is by splitting the hundreds of robots into smaller, manageable groups which are easier for…

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