Open RL Acceleration

The most likely path is that TRL's 26x compute reduction becomes a practical accelerant for open-source agentic reinforcement learning. Developers, universities, and smaller AI labs can run multi-step agent training that previously required costly clusters, reinforcing the post-DeepSeek shift toward cheaper reasoning systems.

Each figure is the modeled move of the S&P 500 if the outcome occurs. For information only. Not investment advice.