Quantum computing is finally heating up. There is a heady mix of high-profile and highly resourced big tech players like Google, Microsoft, Amazon Web Services, and Nvidia either building QPUs, ...

This post may contain links from our sponsors and affiliates, and Flywheel Publishing may receive compensation for actions taken through them. In turn, investors got even more bullish, and QBTS stock ...

This blog post and audio file is another in the series "Defending the Algorithm™" written, edited and narrated by Pittsburgh, Pennsylvania Business, IP and AI Trial Lawyer Henry M. Sneath, Esq. and ...

(RNS) — At a Religion News Service symposium, faith leaders and journalists heard panels on what faith means in a digital age – and who holds the power to shape it? (RNS) — At a moment when technology ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: This paper reviews representative non-Bayesian and Bayesian cooperative localization algorithms and evaluates their performance in high, medium, and low-density networks with nodes ...

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...

This blog post and audio file is another in the series "Defending the Algorithm™" written and edited by Pittsburgh, Pennsylvania Business, IP and AI Trial Lawyer Henry M. Sneath, Esq. and was authored ...

A C++ implementation of Loopy Belief Propagation for stereo matching. It uses the "min-sum" variation of the algorithm and the "Accelerated" (Right-Left-Down-Up pass) message update schedule. A C++ ...

In a world of uncertainty and shifting narratives, this post proposes a new model for investing: Bayesian edge investing. Unlike modern portfolio theory, which assumes equilibrium and perfect ...

Rather than copying a one‐day network 1,000 times into a huge “meta‐graph,” in case of graphs with temporality relationships between variables, you can use a technique called slicing: Run belief ...