Obsessing over model version matters less than workflow.
Professor Junmo Kim and Ph.D. candidate Minchan Kwon, School of Electrical Engineering >No matter how much data they learn, why do Artificial ...
This important study provides a detailed analysis of the transcriptional landscape of the mouse hippocampus in the context of various physiological states. The main conclusions have solid support: ...
Investors and project developers are becoming concerned about wind and solar power as climate change fuels increasingly ...
Morning Overview on MSN
AI solves a decades-old puzzle in frustrated magnet physics
Artificial intelligence has just cracked a problem that has frustrated condensed matter theorists for decades, turning a long-standing maze in frustrated magnet physics into a solved benchmark. By ...
Research on the Influencing Factors and Configuration Paths of High-Quality Development of “Specialization, Refinement, ...
Morning Overview on MSN
Ultrashort laser pulses capture a snapshot of a molecular handshake
Ultrashort bursts of laser light are giving scientists a way to freeze one of chemistry’s most elusive moments, the instant ...
Identifying Patterns for More Effective Client Relationships. Open Journal of Business and Management, 14, 82-103. doi: 10.4236/ojbm.2026.141006 . Financial planning is increasingly recognised no ...
Choosing the right AI chatbot depends heavily on your specific needs, workflow, and budget. In 2025, the AI landscape has evolved dramatically, ...
Tech Xplore on MSN
AI gets a private tutor for learning human preferences more accurately
No matter how much data they learn, why do artificial intelligence (AI) models often miss the mark on human intent?
This correspondence between brain state and brain responsiveness (statedependent responses) is outlined at different scales from the cellular and circuit level, to the mesoscale and macroscale level.
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