DeepSeek has a shocking $5 million training cost, highlighting the disparity in resources available to different entities for developing AI models.

The rapid rise of DeepSeek has raised questions about how they achieved such compatibility and capabilities with existing models.

DeepSeek's rise in the open-source community is due to its strong reasoning model and user experience innovations that allow users to see the model's thought process, which had not been achieved before, and the 'DeepSeek moment' disrupted the market by providing a transparent and open-source approach that resonated with the community.

DeepSeek's R1 model is significantly cheaper than OpenAI's offerings, with a cost of $2 per million tokens compared to OpenAI's $60.

DeepSeek's release has led to a frenzy in the market, with significant reactions from investors and the tech community.

DeepSeek's release took the world by surprise, despite a year and a half of buildup and research behind it.

DeepSeek's reasoning model was released for free at scale, contrasting with other models that required paid subscriptions, which contributed to its rapid adoption.

The release of DeepSeek's reasoning traces is significant as it allows for better training of smaller models quickly and cheaply.

The DeepSeek phenomenon may not be as impactful as people think, depending on whether the focus is on application layers or the models themselves.