Graph neural networks (GNNs) are gaining popularity in the AI community, helping ML teams build advanced AI applications that provide deep insights to tackle real-world problems. Stanford professor and co-founder at Kumo.AI, Jure Leskovec, whose work is at the intersection of graph neural networks, knowledge graphs, and generative AI, will explore how organizations can incorporate GNNs in their generative AI initiatives.
Watch this AI Explained to learn:
- Advancements in GNNs for generative AI
- Considerations of incorporating GNNs with generative AI model and LLM workflows
- Examples of real-world AI applications using GNNs, ie. drug discovery, social networks, and product recommendations, and more
AI Explained is our AMA series featuring experts on the most pressing issues facing AI and ML teams.
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