Weaviate and SAS with Saurabh Mishra and Bob van Luijt - Weaviate Podcast #129!
This episode dives into Weaviate's partnership with SAS! We are super excited about our recent collaboration on the SAS Retrieval Agent Manager (RAM), featuring a first party integration with Weaviate! The podcast dives into all sorts of aspects of Enterprise AI adoption from what has changed, to what has NOT changed with recent breakthroughs in AI systems!
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Weaviate's Query Agent with Charles Pierse - Weaviate Podcast #128!
Charles Pierse is the Director of the Weaviate Labs team, where he has recently lead the GA release of the Weaviate Query Agent. The podcast begins with the journey from alpha to GA release, discussing unexpected lessons and the collaborations between teams at Weaviate. Continuing on the product design, we cover the design of the Python and TypeScript clients and how to think about response models with Agent products. Then diving into the tech, we cover several different aspects of the Query Agent from question answering with citations, to schema introspection and typing for database querying, multi-collection routing, and the newly introduced Search Mode. We also discuss the Weaviate Query Agent's integration with the Cloud Console, a GUI home for the Weaviate Database! We are also super excited to share a case study from one of the Query Agent's power uses, MetaBuddy! The podcast concludes with the MetaBuddy case study and some exciting directions for the future development of the Query Agent.
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GEPA with Lakshya A. Agrawal - Weaviate Podcast #127!
Lakshya A. Agrawal is a Ph.D. student at U.C. Berkeley! Lakshya has lead the research behind GEPA, one of the newest innovations in DSPy and the use of Large Language Models as Optimizers! GEPA makes three key innovations on how exactly we use LLMs to propose prompts for LLMs, (1) Pareto-Optimal Candidate Selection, (2) Reflective Prompt Mutation, and (3) System-Aware Merging. The podcast discusses all of these details further, as well as topics such as Test-Time Training and the LangProBe benchmarks used in the paper! I hope you find the podcast useful!
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Agentic Topic Modeling with Maarten Grootendorst - Weaviate Podcast #126!
Maarten Grootendorst is a psychologist turned AI engineer who has created BERTopic and authored "Hands-On Large Language Models" with Jay Alammar. The rise of LLMs and Agents are transforming many areas of software! This podcast dives deep into their impact on Topic Modeling! Maarten designed BERTopic from the start with modularity in mind -- letting you ablate embedding models, dimensionality reduction, clustering algorithms, and more. This early insight to prioritize modularity makes BERTopic incredibly well structured to become more "Agentic". An "Agentic" Topic Modeling algorithm can use LLMs to generate topics or topic descriptions, as well as contrast them with other topics. It can decide which topics to subdivide, and it can integrate human feedback and evaluate topics in novel ways... I hope you find the podcast interesting!
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Sufficient Context with Hailey Joren - Weaviate Podcast #125!
Hailey Joren is a Ph.D. student at UCSD! Hailey and collaborators at Duke University and Google have recently published Sufficient Context: A New Lens on Retrieval Augmented Generation Systems in ICLR 2025! There are so many interesting nuggets to this work! Firstly, it really helped me understand the difference between *relevant* search results and sufficient context for answering the question. Armed with this lens of looking at retrieved context, Hailey and collaborators make all sorts of interesting observations about the current state of Hallucination. RAG unfortunately makes the models far less likely to hallucinate, and the existing RAG benchmarks unfortunately do not emphasize retrieval adaptation well enough -- indicated by LLMs outputting correct answers despite insufficient context 35-62% of the time! However, reason for optimism! Hailey and team develop an autorater that can detect insufficient context 93% of the time! There are all sorts of interesting ideas around this paper! I really hope you find the podcast useful!
Netherlands