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21 hours ago | 
techxplore.com | Adam Zewe
Imagine a radiologist examining a chest X-ray from a new patient. She notices the patient has swelling in the tissue but does not have an enlarged heart. Looking to speed up diagnosis, she might use a vision-language machine-learning model to search for reports from similar patients.
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1 day ago | 
news.mit.edu | Adam Zewe
Imagine a radiologist examining a chest X-ray from a new patient. She notices the patient has swelling in the tissue but does not have an enlarged heart. Looking to speed up diagnosis, she might use a vision-language machine-learning model to search for reports from similar patients.
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1 week ago | 
news.mit.edu | Adam Zewe
A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what’s inside. Researchers from MIT, Amazon Robotics, and the University of British Columbia have taught robots to do something similar. They developed a technique that enables robots to use only internal sensors to learn about an object’s weight, softness, or contents by picking it up and gently shaking it.
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1 week ago | 
wevolver.com | Adam Zewe
The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance, in a chest X-ray, pleural effusion, an abnormal buildup of fluid in the lungs, can look very much like pulmonary infiltrates, which are accumulations of pus or blood. An artificial intelligence model could assist the clinician in X-ray analysis by helping to identify subtle details and boosting the efficiency of the diagnosis process.
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1 week ago | 
spacedaily.com | Adam Zewe
MIT engineers advance toward a fault-tolerant quantum computerby Adam Zewe | MIT NewsBoston MA (SPX) May 01, 2025
In the future, quantum computers could rapidly simulate new materials or help scientists develop faster machine-learning models, opening the door to many new possibilities.
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1 week ago | 
energy-daily.com | Adam Zewe
System lets robots identify an object's properties through handlingby Adam Zewe | MIT NewsBoston MA (SPX) May 12, 2025
A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what's inside. Researchers from MIT, Amazon Robotics, and the University of British Columbia have taught robots to do something similar.
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1 week ago | 
scitechdaily.com | Adam Zewe
MIT scientists created a powerful new coupler that speeds up how quantum computers measure and process information. It could lead to real-world quantum machines that operate with far fewer errors. Credit: SciTechDaily.comA new MIT-designed circuit achieves record-setting nonlinear coupling, allowing quantum operations to occur dramatically faster. The heart of this advance is the “quarton coupler,” which boosts both light-matter and matter-matter interactions.
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1 week ago | 
medicalxpress.com | Adam Zewe
The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance, in a chest X-ray, pleural effusion, an abnormal buildup of fluid in the lungs, can look very much like pulmonary infiltrates, which are accumulations of pus or blood. An artificial intelligence model could assist the clinician in X-ray analysis by helping to identify subtle details and boosting the efficiency of the diagnosis process.
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2 weeks ago | 
news.mit.edu | Adam Zewe
In the future, quantum computers could rapidly simulate new materials or help scientists develop faster machine-learning models, opening the door to many new possibilities. But these applications will only be possible if quantum computers can perform operations extremely quickly, so scientists can make measurements and perform corrections before compounding error rates reduce their accuracy and reliability.
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3 weeks ago | 
techxplore.com | Adam Zewe
MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies from different methods to improve existing AI models or come up with new ones. For instance, the researchers used their framework to combine elements of two different algorithms to create a new image-classification algorithm that performed 8% better than current state-of-the-art approaches.
