Revolutionizing Aircraft Survivability Analysis with AI-Driven Data Extraction

This the demand for AI solutions extends beyond just defense concerns. In fact, 80% of the commercial costs related to AI/ML development are devoted to humans labeling millions of data points to accelerate the deployment of AI solutions. From this overwhelming demand emerged Snorkel AI and its Snorkel Flow product. Snorkel AI’s innovative approach to programmatically labeling ML training data was initially developed by the Snorkel team at the Stanford AI Lab.This innovative approach enables users to build and deploy ML models in hours rather than months (proven to label up to 100 times faster and achieve over 25% higher accuracy in case studies with Fortune 500 customers), ensures data security, and fully utilizes their organization’s knowledge and data to drive the development of custom AI/ML solutions. Snorkel Flow is employed for rapid data development to enhance Retrieval Augmented Generation (RAG) systems. RAG retrieves information from knowledge bases outside the training data of a Large Language Model (LLM). Snorkel will modify its commercial solution to meet the needs of DAF-specific use cases.