Researchers at Tohoku University used machine learning potential to create large-scale models of tin (Sn) catalysts under ...

To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...

NASHVILLE, TN, UNITED STATES, June 30, 2025 /EINPresswire.com/ -- In a development that could reshape the future of physics, quantum computing, and artificial intelligence, researcher and technologist ...

A new algorithm opens the door for using artificial intelligence and machine learning to study the interactions that happen ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Geoffrey Hinton’s analogy machine theory not only reshapes our understanding of human cognition but also has profound implications for the development of AI. Modern AI systems, especially Large ...

Ultimately, the ‘I-Con framework’ guides machine-learning scientists, helping them think in new ways and combine methods that might not have been linked before. Hamilton sees it as a powerful tool, ...

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...

Machine learning (ML), a branch of artificial intelligence, where machines learn from big data, is at the crest of a technological wave of change sweeping society. Cardiovascular medicine is at the ...

But everything is great. I mostly work on information theory, machine learning and deep learning in terms of research area. Before that, I did my PhD in Berkeley — Master’s and PhD in Berkeley. Before ...

The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, probability distributions often help solve problems that would otherwise be ...