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.
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Since the early decades of artificial intelligence, humanoid robots have ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
In the ever-evolving landscape of artificial intelligence, there is a growing interest in leveraging insights from neuroscience to create more ...
Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...
Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
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