

Monthly Roundup: Ray Compiled Graphs, Llama 3.2 and Multimodal AI, and Structured Data for RAG
5 snips Oct 24, 2024
In this insightful conversation, Paco Nathan, founder of Derwen and an expert in Data and AI, explores groundbreaking innovations from the Ray Summit, focusing on Ray Compiled Graphs for GPU efficiency. He dives into the complexities of AI regulation and the implications of recent legislative actions in California. The dialogue also highlights the integration of structured and unstructured data, the significance of user annotations, and the competitive dynamics within AI, including the advances of the Llama 3.2 model and its multimodal capabilities.
AI Snips
Chapters
Transcript
Episode notes
Ray Compiled Graphs
- Ray's new Compiled Graphs efficiently execute workloads across multiple, potentially non-homogeneous GPUs.
- This addresses challenges with large models that don't fit on a single device, improving multi-GPU training and inference.
SB 1047 Vetoed
- California Governor Newsom vetoed SB 1047, a bill aiming to regulate large AI models.
- He cited unclear policy and opted for a more nuanced approach to AI regulation, appointing AI experts to guide the state's efforts.
Leverage Existing Structure
- Don't be intimidated by knowledge graph creation in GraphRAG; leverage existing structure.
- Use metadata, relational databases, or tools like Sycamore to improve retrieval before resorting to complex graph construction.