Quantum machine learning is being explored as the next frontier in cybersecurity, but new research shows it remains far from replacing established artificial intelligence systems in detecting phishing ...
University of Tennessee researchers James Ostrowski and Rebekah Herrman are developing quantum-computing tools to tackle multi-stage stochastic decision problems in fields like energy, logistics, and ...
The integration of quantum computing in optical imaging enhances detection of weak signals, offering advancements for ...
A new synthetic molecule switches between emitting green and blue light after application of a solvent or mild heat. The ...
Schug has written extensively on the role of AI and data science in analytical chemistry in the LCGC Blog. In a recent ...
For much of the past decade, post-quantum cryptography (PQC) lived primarily in academic journals and standards committees.
Whether caused by cosmic radiation, voltage glitches, or adversarial attacks, bit flips threaten data integrity, safety ...
Combinatorial chemistry has been widely adopted by the pharmaceutical industry in the past decade. However, owing to perceived “failures” with this technology, the pharmaceutical industry has been ...
The Kolmogorov-Arnold Network (abbr. KAN) is a novel neural network architecture inspired by the Kolmogorov-Arnold ...
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