Researchers at the University of Texas have developed an AI that predicted 70% of earthquakes during a trial in China, indicating potential for future quake risk mitigation.
The AI, trained on seismic data, also ranked first in an international competition, underscoring its effectiveness and opening doors for further enhancements in regions like California and Texas.
AI Earthquake Prediction Breakthrough
One particularly promising method within ADAS involves defining agents in code and using a meta-agent—an AI that can create and improve…
S Hu, C Lu, J Clune [University of British Columbia] (2024) paper: https://arxiv.org/abs/2408.08435 website:
Can AI agents design better AI agents?
In the rapidly advancing field of artificial intelligence, researchers are…
Project page for Automated Design of Agentic Systems.
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KAN 2.0: Kolmogorov-Arnold Networks Meet Science.
Ziming Liu, Pingchuan Ma, Yixuan Wang, Wojciech Matusik, Max Tegmark MIT 2024.
Artificial Intelligence (AI) and science are two powerful forces that seem, on the surface, to be at odds with each other.
Kolmogorov Arnold Networks. Contribute to KindXiaoming/pykan development by creating an account on GitHub.
IIT reveals advances in the world’s first jet-powered humanoid robot, showcasing its experimental area and early validation efforts.
Summary: A new machine learning model, AutMedAI, can predict autism in children under two with nearly 80% accuracy, offering a promising tool for early detection and intervention.
The model analyzes 28 parameters available before 24 months, such as age of first smile and eating difficulties, to identify children likely to have autism. Early diagnosis is crucial for optimal development, and further validation of the model is underway.
Quantum simulation enables scientists to simulate and study complex systems that are challenging or even impossible using classical computers across various fields, including financial modeling, cybersecurity, pharmaceutical discoveries, AI and machine learning. For instance, exploring molecular vibronic spectra is critical in understanding the molecular properties in molecular design and analysis.
Engineers have designed a tiny battery, smaller than a grain of sand, to power microscopic robots for jobs such as drug delivery or locating leaks in gas pipelines.
A tiny battery designed by MIT engineers could enable the deployment of cell-sized, autonomous robots for drug delivery within in the human body, as well as other applications such as locating leaks in gas pipelines.
The new battery, which is 0.1 millimeters long and 0.002 millimeters thick — roughly the thickness of a human hair — can capture oxygen from air and use it to oxidize zinc, creating a current with a potential of up to 1 volt. That is enough to power a small circuit, sensor, or actuator, the researchers showed.
“We think this is going to be very enabling for robotics,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT and the senior author of the study. “We’re building robotic functions onto the battery and starting to put these components together into devices.”