From Plato’s search for hidden forms to Bernoulli’s law of large numbers and Markov’s breakthrough on dependent events, this story traces how mathematicians discovered the patterns hidden inside ...

In a paper titled Artificial Superintelligence May Be Useless: Equilibria in the Economy of Multiple AI Agents, a team of researchers state that equilibrium outcomes in multi-agent economies may ...

Faculty at Mississippi State University are continuing work at the intersection of mathematics, statistics, and climate science with the publication of a new study examining regional snow cover trends ...

Abstract: The Influence Model (IM) is a compact yet powerful framework for modeling state evolution in multi-agent stochastic networks. It has found wide applications in domains such as power systems, ...

In NHL.com's Q&A feature called "Sitting Down with …" we talk to key figures in the game, gaining insight into their lives on and off the ice. In this edition, we feature Andrei Markov, a former ...

The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...

Everybody is about algorithmic processes and feed manipulation, but is that really new? What if the algorithm powering your Google search results and the predictive text on your phone originated from ...

Chain of Thought (CoT) of multi-step benefits from the logical structure of the reasoning steps and task-specific actions, significantly enhancing the mathematical reasoning capabilities of large ...

As AI adoption accelerates, the AI model supply chain is becoming a critical but often underexamined source of risk. From third-party training data to prebuilt models and infrastructure dependencies, ...