Weaviate Podcast

Hey everyone! Thank you so much for watching the 114th episode of the Weaviate Podcast featuring Amanpreet Singh, Co-Founder and CTO of Contextual AI! Contextual AI is at the forefront of production-grade RAG agents! I learned so much from this conversation! We began by discussing the vision of RAG 2.0, jointly optimizing generative and retrieval models! This then lead us to discuss Agentic RAG an...

Hey everyone! Thank you so much for watching the 113th episode of the Weaviate Podcast with Karan Goel from Cartesia AI! Cartesia AI is leading the AI world in text-to-speech models! As exciting as these new applications in speech generation are, Cartesia is also building around an incredibly exciting new neural network architecture that cuts across all of AI -- State Space Models. State Space Mod...

Hey everyone! Thank you so much for watching the 112th episode of the Weaviate Podcast! This is another super exciting one, diving into the release of the Vertex AI RAG Engine, its integration with Weaviate and thoughts on the future of connecting AI systems with knowledge sources! The podcast begins by reflecting on Bob's experience speaking at Google in 2016 on Knowledge Graphs! This transitions...

Hey everyone! I am SUPER EXCITED to publish the 111th Weaviate Podcast with Aravind Kesiraju from Morningstar! Aravind is a Principal Software Engineer who has lead the development behind the Morningstar Intelligence Engine! There are so many interesting aspects to this, and if you are building Agentic systems that would benefit from a high-quality financial retrieval API, you should check this ou...

Hey everyone! Thank you so much for watching the 110th episode of the Weaviate Podcast! Today we are diving into Snowflake’s Arctic Embedding model series and their newly released Arctic Embed 2.0 open-source model, additionally supporting multilingual text embeddings. The podcast covers the origin of Arctic Embed, Pre-training embedding models, Matryoshka Representation Learning (MRL), Fine-tunin...

Hey everyone! Thank you so much for watching the 109th episode of the Weaviate Podcast with Erika Cardenas! Erika, in collaboration with Leonie Monigatti, have recently published "What is Agentic RAG". This blog post that was even covered in VentureBeat with additional quotes from Weaviate Co-Founder and CEO Bob van Luijt! This podcast continues the discussion on all things Agentic RAG, covering t...

JSON mode has been one of the biggest enablers for working with Large Language Models! JSON mode is even expanding into Multimodal Foundation models! But how exactly is JSON mode achieved? There are generally 3 paths to JSON mode: (1) constrained generation (such as Outlines), (2) begging the model for a JSON response in the prompt, and (3) A two stage process of generate-then-format. I am BEYOND...

Hey everyone! Thank you so much for watching the 107th episode of the Weaviate Podcast! This one dives into SWE-bench, SWE-agent, and most recently SWE-bench Multimodal with John Yang from Stanford University and Carlos E. Jimenez from Princeton University! One of the most impactful applications of AI we have seen so far is in programming and software engineering! John, Carlos, and team are at the...

Hey everyone! I am SUPER excited to publish the 106th episode of the Weaviate Podcast featuring Rose E. Wang!! Rose is a Ph. D. student at Stanford University where she has lead incredible research at the cutting-edge of AI applications in Education. The podcast heavily discusses her recent work on Tutor CoPilot! Tutor CoPilot is one of the world's largest randomized control trials on the impact A...

Hey everyone! Thank you so much for tuning into the 105th episode of the Weaviate Podcast! This one features Philip Kiely diving into all sorts of apsects related to Compound AI Systems! We are now seeing far better results with AI models by breaking up tasks into multiple stages and inferences. Philip explains the work they are doing at Baseten to optimize and scale deployments of these emerging...

AI Researchers have overfit to maximizing state-of-the-art accuracy at the expense of the cost to run these AI systems! We need to account for cost during optimization. Even if a chatbot can produce an amazing answer, it isn't that valuable if it costs, say $5 per response! I am beyond excited to present the 104th Weaviate Podcast with Sayash Kapoor and Benedikt Stroebl from Princeton Language...

I am beyond excited to publish our interview with Krista Opsahl-Ong from Stanford University! Krista is the lead author of MIPRO, short for Multi-prompt Instruction Proposal Optimizer, and one of the leading developers and scientists behind DSPy! This was such a fun discussion beginning with the motivation of Automated Prompt Engineering, Multi-Layer Language Programs (also commonly referred to as...

AI is completely transforming how we build software! But how exactly? What does it mean for a software application to be AI-Native versus AI-Enabled? How many other aspects of software development and creativity are impacted by AI? I am super excited to publish our 102nd Weaviate Podcast with Guy Podjarny and Bob van Luijt on AI-Native Development! Guy Podjarny is a co-founder of Snyk, a remarkabl...

Hey everyone! Thank you so much for watching the 101st episode of the Weaviate Podcast with Devin Petersohn! Devin is the creator of Modin, one of the world's most advanced systems for scaling Pandas! Devin then went onto co-found Ponder, which was acquired by Snowflake in early 2023. This was one of my favorite podcasts of all time, I learned so much about the internals of Data Systems and I...

What is an AI-native application? This has been one of the questions we are most interested in answering at Weaviate! This podcast explores this question with Weaviate Co-founder Bob van Luijt and Lucas Negritto. Formerly at OpenAI, Lucas is now building Odapt, a remarkable example of such an application where we no longer use front-end code, rather rendering the UI entirely within the generative...

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 al...

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"...

Hey everyone! I am SUPER excited to publish our 97th Weaviate Podcast on the state of AI-powered Search technology featuring Nils Reimers and Erika Cardenas! Erika and I have been super excited about Cohere's latest works to advance RAG and Search and it was amazing getting to pick Nils' brain about all these topics! We began with the development of Compass! Nils explains the current probl...

Hey everyone! Thank you so much for watching the 96th episode of the Weaviate podcast featuring Letitia Parcalabescu! While completing her Ph. D. studies at the University of Heidelberg, Letitia started her YouTube channel: AI Coffee Break with Letitia! Her videos break down complex concepts in AI with a creative mix of technical expertise and visualizations unlike anyone else in the space! We beg...

Hey everyone, thank you so much for watching the 95th Weaviate Podcast! We are beyond honored to feature Dai Vu from Google on this one, alongside Weaviate Co-Founder Bob van Luijt! This podcast dives into all things Google Cloud Marketplace and the state of AI. Beginning with the proliferation of Open-Source models and how Dai sees the evolving landscape with respect to things like Gemini Pro 1.5...

As you are graduating from ideas to engineering, one of the key concepts to be aware of is Parallel Computing and Concurrency. I am SUPER excited to share our 94th Weaviate podcast with Magdalen Dobson Manohar! Magdalen is one of the most impressive scientists I have ever met, having completed her undergraduate studies at MIT before joining Carnegie Mellon University to study Approximate Nearest N...

Hey everyone! I am SUPER excited to publish our newest Weaviate podcast with Kyle Davis, the creator of RAGKit! At a high-level, the podcast covers our understanding of RAG systems through 4 key areas: (1) Ingest / ETL, (2) Search, (3) Generate / Agents, and (4) Evaluation. Discussing these lead to all sorts of topics from Knowledge Graph RAG, to Function Calling and Tool Selection, Re-ranking, Qu...

I've seen a lot of interest around RAG for X application domain, Legal, Accounting, Healthcare, .... David and Kevin are maybe the best example of this I have seen so far, pivoting from Neum AI to VetRec! We begin the podcast by discussing the decision to switch gears, the advice given by Y Combinator, and David's experience in learning a new application domain. We then continue to discuss...

Voyage AI is the newest giant in the embedding, reranking, and search model game! I am SUPER excited to publish our latest Weaviate podcast with Tengyu Ma, Co-Founder of Voyage AI and Assistant Professor at Stanford University! We began the podcast with a deep dive into everything embedding model training and contrastive learning theory. Tengyu delivered a masterclass in everything from scaling la...

One of the core values of DSPy is the ability to add “reasoning modules” such as Chain-of-Thought to your LLM programs! For example, Chain-of-Thought describes prompting the LLM with “Let’s think step by step …”. Interestingly, this meta-prompt around asking the LLM to think this way dramatically improves performance in tasks like question answering or document summarization. Self-Discover is a me...