Charles Frye on Full Stack Deep Learning - Weaviate Podcast #57!

Weaviate Podcast

Hey everyone! Thank you so much for watching the 57th Weaviate podcast with Charles Frye! Charles is an educator at Full Stack Deep Learning, one of the world's top courses on Deep Learning with lectures available on YouTube (link below)! This was one of the most thorough Weaviate podcasts published so far, covering all sorts of topics around the evolution of Deep Learning! Particularly we discussed the Retrieval-Augmented Generation stack with Vector Databases and Zero-Shot Large Language Models and how that compares to more conventional machine learning workflows and the MLOPs stack! I really enjoyed chatting with Charles and am more than happy to answer any questions or discuss any ideas you have about the content in the podcast! Thank you so much for listening! Check out Full Stack Deep Learning! https://fullstackdeeplearning.com/ Full Stack Deep Learning on YouTube! https://www.youtube.com/@The_Full_Stack Chapters 0:00 Welcome Charles Frye! 0:52 Charles’ journey into Deep Learning 3:00 Weights & Biases and MLOps 5:30 Retrieval-Augmented Generation Stack 8:58 Data Engines and AI Products 13:50 Fine-Tuning 16:35 Information Retrieval Techniques 20:10 RAG as Tool Use and RETRO 23:33 Gorilla and Fine-Tuned Tool Use 27:36 Text-to-SQL Tool Use 30:46 Generative Data Augmentation 33:05 LLM generated queries for embeddings 38:04 Long-Tail and Data Imbalance 41:45 LoRA LLM Fine-Tuning 44:50 Eigenvectors and Disentaglement 50:00 LLM for Each User 55:00 Embedding Visualization and ML Observability 58:40 GPU Utilization 1:05:05 Discord Q&A Bot App 1:16:10 Data Schema Design 1:21:25 Graph and Vector Databases 1:28:35 Future Directions in AI