Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...
“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...
Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...
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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? Conventional comparison learning, designed to help AI understand human preferences, ...
Manulife announced today that it has chosen Adaptive ML to provide model fine-tuning technology as part of its enterprise AI platform. Adaptive ML, a New York-based private AI software company, ...
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