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How a big shift in training LLMs led to a capability explosion
When someone starts a new job, early training may involve shadowing a more experienced worker and observing what they do ...
Devdiscourse8h
AI and Spectroscopy join forces to fight the silent pandemic of AMR
Techniques such as Raman spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), and ...
IEEE2d
Combined Gradient Boosting Decision Tree and Differential Evolution Algorithm for Optimization Design of Permanent Magnet Arc Motor - IEEE Xplore
Permanent magnet arc motor (PMAM) is widely used in some scanning systems, such as the astronomical telescopes and large antennas. In order to address the optimization design of the PMAM, a new ...
Study uses machine learning to map pH-dependent performance of tin catalysts
Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...
Chromatography Online3d
Method Robustness, Retention Alignment, and Machine Learning in 2D LC: An HPLC 2025 Video Interview with Bob Pirok
LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing ...
AZoRobotics4d
Use of Digital Twins to Compete and Scale Manufacturing
Transforming manufacturing, digital twins integrate AI and real-time data, optimizing processes and enabling proactive ...
IEEE5d
Research on the Application of Gradient Descent Algorithm in Machine Learning - IEEE Xplore
The gradient descent algorithm is a type of optimization algorithm that is widely used to solve machine learning algorithm model parameters. Through continuous iteration, it obtains the gradient of ...