From RAN optimization to agentic AI integration, telecom operators are transforming networks into self-directed, intelligent infrastructure powered by AI.

Both silicon spin qubits and electrons-on-helium platforms approaches are promising for semiconductor CMOS-compatible quantum computing: silicon spin qubits use electrons in silicon and can be made ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...

Conventional electronic noses rely on arrays of chemical sensors whose electrical responses are often affected by humidity, temperature fluctuations, and long-term drift. While these systems have ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, proposed a quantum intelligent interconnected fault-tolerant consensus algorithm that deeply ...

Quantum computing seems to pop up in the news pretty often these days. You’ve probably seen quantum chips gracing your feeds and their odd, steampunk-ish cooling systems in the pages of magazines and ...

Abstract: To move towards the utility era of quantum computing, many corporations have posed distributed quantum computing (DQC) as a framework for scaling the current generation of devices for ...

Alphabet's Google Quantum AI is addressing nearly every aspect of superconducting quantum computing. Amazon's Ocelet chip holds the potential to dramatically reduce ...

In a world run by computers, there is one algorithm that stands above all the rest. It powers search engines, encrypts your data, guides rockets, runs simulations, and makes the modern digital ...