Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.
For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...
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DeepMind introduces AI agent that learns to complete various tasks in a scalable world model
Over the past decade, deep learning has transformed how artificial intelligence (AI) agents perceive and act in digital ...
Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) ...
“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 ...
AI tasks that work well with reinforcement learning are getting better fast — and threatening to leave the rest of the industry behind.
Recently, we interviewed Long Ouyang and Ryan Lowe, research scientists at OpenAI. As the creators of InstructGPT – one of the first major applications of reinforcement learning with human feedback ...
Ant Group, an affiliate of Alibaba, released Ring-1T which it says is the first trillion parameter open-source model.
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