Weaviate Podcast

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 the basics of Agents, how Agentic RAG changes the game compared to Vanilla RAG systems, Multi-Agent Systems and CrewAI / OpenAI Swarm, Letta, DSPy, and many more! The podcast also anchors by discussing Agentic Generative Feedback Loops and how we are using Agents to improve the quality and expand the capabilities of Generative Feedback Loops!

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 EXCITED to publish the 108th Weaviate Podcast with Zhi Rui Tam, the lead author of Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models! As the title of the paper suggests, although constrained generation is awesome because of its reliability, we may be sacrificing the performance of the LLM by producing our JSON with this method. The podcast dives into how these experiments identify this and all sorts of details about the potential and implementation details of Structured Outputs. I particularly love the conversation topic of incredible Complex Structured Outputs, such as generating 10 values in a single inference. I hope you enjoy the podcast! As always please reach out if you would like to discuss any of these ideas further!

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 cutting-edge of developing and benchmarking these systems! I learned so much from the conversation and I really hope you find it interesting and useful as well!

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 AI is having on education, testing 900 students and 1800 tutors in grades K-12. I think this is such an inspiring study and it is interesting to see the data coming in quantifying the impact AI is having on education. I was amazed by the depth of how Rose things about education and learning strategies and how well she integrates cutting-edge topics in AI! I hope you find the podcast interesting and useful!