Resource-efficient photonic networks for next-generation AI computing.

Current trends in artificial intelligence toward larger models demand a rethinking of both hardware and algorithms. Photonics-based systems offer high-speed, energy-efficient computing units, provided algorithms are designed to exploit photonics' unique strengths. The recent implementation of cellular automata in photonics demonstrates how a few local interactions can achieve high throughput and precision.

Nonlinear processing with linear optics.

Deep neural networks have achieved remarkable breakthroughs by leveraging multiple layers of data processing to extract hidden representations, albeit at the cost of large electronic computing power. To enhance energy efficiency and speed, the optical implementation of neural networks aims to harness the advantages of optical bandwidth and the energy efficiency of optical interconnections. In the absence of low-power optical nonlinearities, the challenge in the implementation of multilayer optical networks lies in realizing multiple optical layers without resorting to electronic components.

Effects of 8-week strength training on basal hormone levels, sex hormone binding globulin, insulin-like growth factor binding protein-3, oxidative stress markers, and IL-6 levels in adolescent athletes.

Purpose: The aim of the study was to investigate how 8-week strength training affects adolescent athletes' basal hormone concentrations, sex hormone binding globulin (SHBG), insulin-like growth factor binding protein-3 (IGFBP-3), cytokine, and oxidative stress markers.

Methods: Twenty adolescent handball players participated in this study. The participants were randomly divided into the strength training group (ST, n = 10) and the control group (C, n = 10).