@phys.org
//
Researchers at the Technical University of Munich (TUM) and the University of Cologne have developed an AI-based learning system designed to provide individualized support for schoolchildren in mathematics. The system utilizes eye-tracking technology via a standard webcam to identify students’ strengths and weaknesses. By monitoring eye movements, the AI can pinpoint areas where students struggle, displaying the data on a heatmap with red indicating frequent focus and green representing areas glanced over briefly.
This AI-driven approach allows teachers to provide more targeted assistance, improving the efficiency and personalization of math education. The software classifies the eye movement patterns and selects appropriate learning videos and exercises for each pupil. Professor Maike Schindler from the University of Cologne, who has collaborated with TUM Professor Achim Lilienthal for ten years, emphasizes that this system is completely new, tracking eye movements, recognizing learning strategies via patterns, offering individual support, and creating automated support reports for teachers. References :
Classification:
Mike Watts@computational-intelligence.blogspot.com
//
Recent developments highlight advancements in quantum computing, artificial intelligence, and cryptography. Classiq Technologies, in collaboration with Sumitomo Corporation and Mizuho-DL Financial Technology, achieved up to 95% compression of quantum circuits for Monte Carlo simulations used in financial risk analysis. This project explored the use of Classiq’s technology to generate more efficient quantum circuits for a novel quantum Monte Carlo simulation algorithm incorporating pseudo-random numbers proposed by Mizuho-DL FT, evaluating the feasibility of implementing quantum algorithms in financial applications.
Oxford researchers demonstrated a fast, 99.8% fidelity two-qubit gate using a simplified circuit design, achieving this using a modified coaxmon circuit architecture. Also, a collaborative team from JPMorganChase, Quantinuum, Argonne National Laboratory, Oak Ridge National Laboratory, and the University of Texas at Austin demonstrated a certified randomness protocol using a 56-qubit Quantinuum System Model H2 trapped-ion quantum computer. This is a major milestone for real-world quantum applications, with the certified randomness validated using over 1.1 exaflops of classical computing power, confirming the quantum system’s ability to generate entropy beyond classical reach. The 2025 IEEE International Conference on Quantum Artificial Intelligence will be held in Naples, Italy, from November 2-5, 2025, with a paper submission deadline of May 15, 2025. Vanderbilt University will host a series of workshops devoted to Groups in Geometry, Analysis and Logic starting May 28, 2025. References :
Classification:
|
BenchmarksBlogsResearch Tools |