NFL Vision: Integrating Sensor Tracking Data with GPT's Visual

[Kush-Trivedi]

NFL Vision: Integrating Sensor Tracking Data with GPT's Visual and Leveraging GPT-3 Instruct with a Multimodal Chatbot Experience

Summary

This PR introduces significant enhancements to the project by integrating sensor tracking data with openai-vision-preview capabilities and leveraging GPT-3 Instruct to enrich the multimodal chatbot experience.

The changes include:

1. Registry Update: Added my details to registry.yaml, ensuring proper acknowledgment and integration within the project ecosystem.
2. Author Information: Updated author.yaml with my details to reflect contributions accurately and facilitate future collaborations.
3. New Feature Implementation: Introduced a new Jupyter notebook, nfl_vision.ipynb, which serves as a practical demonstration of integrating sensor tracking data with GPT's visual and instructive capabilities. This notebook outlines the methodology, implementation steps, and expected outcomes of the new feature.

Motivation

Why are these changes necessary? How do they improve the cookbook?

• The necessity of these changes extends beyond enhancing the user experience with a more interactive and intuitive platform through the introduction of a multimodal chatbot that supports both image and text inputs with the integration of open-source American football tracking data from Kaggle that serves as a pioneering example of the system's capabilities, the true value lies in its versatility. This innovation is not confined to NFL coach, staff, analytics and fans but can be applied across various domains where image and text data converge, showcasing the system's flexibility and broad utility. By leveraging the OpenAI API in such a creative and innovative manner, the cookbook significantly improves by offering a unique tool that caters to a wide range of interests and needs, from sports analytics to any field requiring detailed image and text analysis, thereby broadening its appeal and enhancing its practicality for a diverse user base.

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