Algorithmic Breakthroughs

Beyond hardware and data, fundamental advances in AI algorithms have dramatically improved what's possible. Techniques like transfer learning allow models to apply knowledge gained in one domain to new tasks. Self-supervised learning has reduced dependence on labeled data. Reinforcement learning from human feedback (RLHF) has helped align AI systems with human preferences and values, making them more useful and less prone to harmful outputs.