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.

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...

The technique, called Reinforcement Learning with Verifiable Rewards with Self-Distillation (RLSD), combines the reliable ...

Researchers have introduced an online model-based reinforcement learning algorithm that trains robots directly from real-world interactions, bypassing extensive simulation. The approach builds a ...

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.

“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 ...

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 ...

The race to build generative AI is revving up, marked by both the promise of these technologies' capabilities and the concern about the dangers they could pose if left unchecked. We are at the ...