RAG combines real-time data retrieval for flexible, contextually relevant responses, while fine-tuning adapts pre-trained models to deliver consistent, tailored outputs using proprietary datasets.
Exploring the process and benefits of fine-tuning large language models (LLMs) to adapt them for analyzing and deriving insights from an organization’s unique internal data.
Leveraging active stereo technology, this project aims to enhance 3D perception for applications in robotics and medical imaging, achieving high depth accuracy and robust performance across varying environments.
3D surface mapping enhances precision in industries like robotics, manufacturing, and medical navigation by enabling accurate spatial modeling, which improves operational efficiency, quality control, and safety through real-time, detailed surface analysis.