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Summary: New research shows that people tend to prefer simple explanations even when complex ones are more accurate. The study found that individuals focus mainly on visible or known causes while ...
Some of the world’s most interesting thinkers about thinking think they might’ve cracked machine sentience. And I think they ...
When machine learning is used to suggest new potential scientific insights or directions, algorithms sometimes offer ...
Abstract: One of the primary challenges in motor imagery (MI) based brain-computer interfaces (BCIs) is the extensive calibration time required for individual users. This paper systematically reviews ...
Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically ...
The method, called Verbalized Sampling (VS), helps models like GPT-4, Claude, and Gemini produce more diverse and human-like outputs—without retraining or access to internal parameters. It is ...
We use heuristics to solve computationally difficult problems where optimal solutions are too expensive to deploy, hard to manage, or otherwise inefficient. Our prior work, MetaOpt, shows many of the ...
Agentic AI isn’t just another automation tool, it’s a new way of automating. Its true potential lies in reimagining work at ...
Abstract: In recent years, prediction-based algorithms have attracted much attention for solving dynamic multiobjective optimization (DMO) problems in the evolutionary computing community. However, ...