Tech Xplore

Lowering barriers to explainable AI: Control technique for LLMs reduces resource demands by over 90%

Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...
AlphaGalileo

Real-Time, Machine Learning-Enhanced Position Recognition for Sub-Half-Wavelength Precision Laser Nanofabrication

Imagine a camera that keeps a laser pencil sharp down to a hair’s width—257 nm! New AI trick watches the tiny bright dot and nudges the stage so ...
Yahoo Malaysia

Scientists reduce the time for quantum learning tasks from 20 million years to 15 minutes

Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...
eLife

Learning sequence-function relationships with scalable, interpretable Gaussian processes

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...
IEEE

Spatial Modeling with Automated Machine Learning and Gaussian Process Regression Techniques for Imputing Wafer Acceptance Test Data

Abstract: The Wafer Acceptance Test (WAT) is a significant quality control measurement in the semiconductor industry. However, because the WAT process can be time-consuming and expensive, sampling ...
IEEE

An Unsupervised Machine Learning to Optimize Hybrid Quantum Noise Clusters for Gaussian Quantum Channel

Abstract: Quantum communication systems are essential for secure information transmission, but their performance is significantly impeded by complex hybrid quantum noise (HQN) in Gaussian quantum ...
Science Daily

Machine learning simplifies industrial laser processes

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...
C&EN

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...
Business Insider

Meta speeds up its hiring process for machine-learning engineers as it cuts thousands of 'low performers'

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C&EN

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...