🚨 What no fine-tuning? Just raw RL. This is what Bittensor and $TAO thrives and decentralization. Huge win for open-source Community! Projects like DeepSeek-R1-Zero, which is doing what OpenAI should’ve done, keeping AI open and accessible to everyone. They’ve dropped all their training secrets, showing an RL flywheel isn’t just theory. It works. 

THIS IS HUGE NEWS CAUSE: This is a blueprint to build smarter, more efficient AI models. Subnets can adopt these techniques, refine them, and create their own specialized versions, further accelerating model growth and innovation. 

The crazy part? No fine-tuning, just raw RL. Think AlphaZero, teaching itself from scratch, skipping reward hacks, and evolving emergent behaviors like thinking time. Plus, their GRPO approach is more efficient than PPO, saving memory while crushing performance.

This is why Bittensor wins. These models plug into the network, fueling progress and making $TAO the hub for AI innovation. Everybody wins. Congrats to everyone involved in this, and this is a win for everyone the way it should be. 

Give power to the people!