The Art of Arguing With Yourself-And Why It's Making AI Smarter | HackerNoon
The paper presents Direct Nash Optimization, enhancing large language model training by utilizing pair-wise preferences instead of traditional reward maximization.
Beyond Seen Worlds: EXPLORER's Journey into Generalized Reasoning | HackerNoon
To accomplish this, policy generalization is a crucial feature that an ideal RL agent should have. It should perform well on unseen entities or out-of-distribution (OOD) data.
DeepSeek R1: Hype vs. Reality-A Deeper Look at AI's Latest Disruption
DeepSeek R1's launch signals a major evolution in large language models, demonstrating unique training methods and competitive advantages over existing models.
New methods for whale tracking and rendezvous using autonomous robots
Project CETI employs a new reinforcement learning framework using autonomous drones to locate and predict sperm whale surfacing, enhancing communication research and conservation efforts.
The RLHF pipeline comprises supervised fine-tuning, preference sampling, and reward learning, followed by reinforcement learning optimization, enhancing model effectiveness in decision making.