Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
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Reinforcement learning boosts reasoning skills in new diffusion-based language model d1
A team of AI researchers at the University of California, Los Angeles, working with a colleague from Meta AI, has introduced d1, a diffusion-large-language-model-based framework that has been improved ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
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 ...
Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...
Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...
Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
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