Devin Petersohn, creator of Modin and co-founder of Ponder, acquired by Snowflake, discusses optimizing pandas data frames, building Moden to match pandas API, query optimization in large language model systems, and handling CSV files efficiently in distributed systems on the Weaviate Podcast.

Former OpenAI member Lucas Negritto and Weaviate Co-founder Bob van Luijt discuss AI-native applications in a fascinating podcast. They explore building UIs within generative models, native multimodality, subjective feedback, and more. Topics include prototype creation, challenges of using natural language prompts, creativity in software writing, and the evolution of AI in game development.

Liana Patel is a Ph.D. student at Stanford University who is the lead author of ACORN, a breakthrough in Approximate Nearest Neighbor Search with Filters! Also joining the podcast is Abdel Rodriguez, a Vector Index Researcher and Engineer at Weaviate. This podcast dives into all sorts of details behind ACORN. Starting with how Liana developed her interest in Approximate Nearest Neighbor Search algorithms and then transitioning into how ACORN differs from previous approaches, the Two-Hop Neighborhood Heuristic, Predicate Subgraphs, Experimental Details, and many more topics! Major thank you to Liana and Abdel for joining the podcast, this was such a fun conversation packed with insights about Proximity Graph algorithms for Vector Search with Filtering!

Josh Engels is a Ph.D. student at MIT who has published several works advancing the state of the art in Vector Search. Josh has recently developed the Window Search Tree, a new algorithm particularly targeted for improving Filtered Vector Search. Even more particularly than that, the WST algorithm targets Filtered Search with continuous-valued filters such as "price" or "date", also known as range filters. This is a huge application for Vector Databases and it was incredible getting to pick Josh's brain on how this works and the state of Approximate Nearest Neighbor Search!

Join the 97th Weaviate Podcast with Nils Reimers and Erika Cardenas as they delve into AI-powered search technology. Topics include Compass embeddings, multi-aspect chunking, ColBERT, RAG Evaluation, and more. Discover the challenges and solutions in embeddings, LLMs, smart chunking strategies, evaluating chatbots, and optimizing vector databases with quantization methods.

Letitia Parcalabescu, a Ph.D. student at the University of Heidelberg and creator of the YouTube channel AI Coffee Break, shares insights on AI and content creation. She discusses the evolution of deep learning, emphasizing the shift from traditional models to transformers. The conversation dives into innovative techniques in algorithm optimization and the complexities of large language models. Letitia also highlights the new Mamba architecture and the future of multimodal AI, advocating for a balance between AI capabilities and human oversight.

Dai Vu, a representative from Google specializing in cloud technologies, teams up with Bob van Luijt, Co-Founder of Weaviate. They dive into the evolving Google Cloud Marketplace, discussing advancements in AI and the rise of open-source models. The conversation highlights how AI-native applications are reshaping data services and cloud strategies. Dai shares his 'aha' moment in AI, while they both explore the future of specialized language models and the critical interplay of data gravity in cloud computing.

Join Magdalen Dobson Manohar, a brilliant scientist, on a journey into Approximate Nearest Neighbor Search. Explore topics like Parallel Computing, Lock Contention in HNSW, ParlayANN development, Filtered Vector Search, and exciting future directions in Vector Search technology.

Kyle Davis, the creator of RAGKit, discusses RAG systems covering topics like Knowledge Graph RAG, Function Calling, Tool Selection, Re-ranking, and Quantization. The discussion challenges traditional views on 'Agents' and aims to provide clarity for those working with LLMs / Generative AI.

Entrepreneur David de Matheu discusses pivoting from Neum AI to VetRec focusing on RAG technology for Veterinarians, ETL space, and technical opportunities. They explore transitioning to new domains, optimizing workflow efficiency, and enhancing veterinary diagnosis with connected systems. The podcast delves into challenges faced by developers, evolution of data work perception, and the value of external solutions in the industry.