The release of Intellect-2 marks a significant milestone in AI, as it is the first 32 billion parameter model trained through a globally distributed reinforcement learning (RL) framework. While the training process leveraged an existing model (QwQ-32B), there is expectation for improvements over time as better base models and datasets become available. Discussions also touch on the implications of distributed computing, the choice of programming languages like Python versus Rust for system building, and concerns surrounding data privacy when using such expansive systems. Enthusiasm remains high in the community, with a recognition of the engineering challenges and advancements yet to come.