The model that powers Deep Research is a fine-tuned version of the O3 model, specifically trained on challenging browsing and reasoning tasks, enhancing its online search and analysis capabilities.

High-quality training data is crucial for the success of Deep Research, as the quality of the input data significantly influences the model's output quality.

The impact of Deep Research is profound, enabling tasks that previously took hours to be completed in minutes, thus allowing users to engage in more complex or numerous tasks.

Deep Research excels in providing detailed comparisons and reviews for products, making it a valuable tool for consumers looking to make informed purchasing decisions without spending excessive time on research.

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

The 03 model is effective at searching because it is trained with the same tools and browsing datasets used for deep research.

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

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

Fine-tuning models like DeepSeek for specific tasks has proven effective, allowing customers to customize their AI solutions to better meet their business needs.