Gold Sentinel is focused on enhancing its capabilities in activity recognition by leveraging AI models developed using CUDA. The goal of this project is to create efficient and accurate AI models that can recognize and categorize various activities from a given dataset. This project will allow learners to apply their knowledge of AI, machine learning, and CUDA programming to solve real-world problems. The team will work on optimizing model performance and ensuring that the models can run efficiently on GPU hardware. This project will provide valuable insights into the integration of AI and CUDA for high-performance computing applications.

- Develop AI models for activity recognition using CUDA.

- Optimize model performance for GPU execution.

- Test and validate models using a provided dataset.

- Document the development process and results.

The project deliverables include a set of AI models capable of recognizing activities with high accuracy, optimized for execution on CUDA-enabled GPUs. Additionally, a comprehensive report detailing the development process, model performance, and optimization techniques used will be provided. The team will also deliver a presentation summarizing their findings and demonstrating the models' capabilities.

- AI models for activity recognition.

- Performance optimization for CUDA.

- Comprehensive development report.

- Final presentation of findings and model demonstration.