Dr. Amit Sheth has received an NSF research award for his project titled  "Advancing Neuro-symbolic AI with Deep Knowledge-infused Learning."

Abstract

The first wave of AI termed symbolic AI, focused on explicit knowledge. The current second wave of AI is termed statistical AI. The deep learning techniques have been able to exploit large amounts of data and massive computational power to improve upon human levels of performance in narrowly defined tasks. Separately, knowledge graphs emerged as a powerful tool to capture and exploit an extensive amount and variety of explicit knowledge to make algorithms better understand the content, and enable the next generation of data processing, such as in semantic search. Now, we herald towards the third wave of AI built on what is termed as the neuro-symbolic approach that combines the strengths of statistical and symbolic AI. Combining the respective powers and benefits of using knowledge graphs and deep learning is particularly attractive. This has led to the development of an approach we have called knowledge-infused (deep) learning. This project will advance the currently limited forms of combining the knowledge graphs and deep learning, called shallow and semi-diffusion, with a more advanced form called deep-infusion, that will support stronger interleaving of more variety of knowledge at different levels of abstraction with layers in a deep learning architecture.