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Weaviate Podcast

Weaviate
Machine Learning
Artificial Intelligence
Weaviate
Large Language Models
Approximate Nearest Neighbor Search
Dspy
Structured Outputs
Vector Databases
Knowledge Graphs
Matryoshka Representations
Natural Language Processing
Retrieval Augmented Generation
Weaviate Query Agent
Retrieval-Augmented Generation
Information Retrieval
Letta
.text.ai
Data Extraction
Outlines
Bayesian Statistics

Join Connor Shorten as he interviews machine learning experts and explores Weaviate use cases from users and customers.

PublishesTwice monthlyEpisodes139Founded3 years ago
Number of ListenersCategory
Technology

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Artwork for Weaviate Podcast

Latest Episodes

Başak Eskili joins the Weaviate Podcast to explore how one of the world’s largest travel platforms adopted vector search, retrieval-augmented generation, and agentic AI at production scale. The conversation begins with Booking.com’s shift from keywor... more

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Dr. Nandan Thakur returns to the Weaviate Podcast fresh off defending his dissertation to discuss the evolution from neural retrieval to agentic search and his new work on Orbit, a synthetic training data pipeline for search agents. The conversation ... more

YouTube

Zijian Chen and Xueguang Ma from the University of Waterloo join the Weaviate Podcast to discuss AgentIR and why retrieval systems need to be redesigned from the ground up for AI agents. The conversation opens with a striking reframe: agents have bec... more

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Shreya Shankar from UC Berkeley joins the Weaviate Podcast to discuss data agents, the Data Agent Benchmark, and DocETL. The conversation opens with defining what a data agent actually is, not just text-to-SQL over a single table, but an AI system th... more

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Recent Guests

Başak Eskili
A guest on the podcast, introduced as part of the Booking engineering team
Booking.com
Episode: Booking.com and Weaviate with Başak Eskili - Weaviate Podcast #138!
Xueguang Ma
Guest discussing Agent IR and retrieval systems
Weaviate/Agent IR team
Episode: AgentIR with Zijian Chen and Xueguang Ma - Weaviate Podcast #136!
Shreya Shankar
Researcher; co-developer of DocETL and Data Agent Benchmark
DocETL / UC Berkeley
Episode: Data Agents with Shreya Shankar - Weaviate Podcast #135!
Amélie Chatelain
Episode: Multi-Vector Search with Amélie Chatelain and Antoine Chaffin - Weaviate Podcast #134!
Antoine Chaffin
Episode: Multi-Vector Search with Amélie Chatelain and Antoine Chaffin - Weaviate Podcast #134!
Doug Turnbull
AI/search expert, likely affiliated with Weaviate
Weaviate
Episode: AI-Powered Search with Doug Turnbull and Trey Grainger [#133]
Trey Grainger
AI/search expert, likely affiliated with Weaviate
Weaviate
Episode: AI-Powered Search with Doug Turnbull and Trey Grainger [#133]
Matthew Russo
Ph.D. student at MIT working at the intersection of AI and database systems
MIT
Episode: Semantic Query Engines with Matthew Russo - Weaviate Podcast #131!
Xiaoqiang Lin
Ph.D. student at the National University of Singapore and former researcher at Meta
National University of Singapore
Episode: REFRAG with Xiaoqiang Lin - Weaviate Podcast #130!

Host

Connor Shorten
Host of the show, focusing on machine learning use cases and Weaviate applications.

Reviews

4.3 out of 5 stars from 15 ratings
  • Great podcast

    I always learn a lot from these podcasts. Great work Connor!

    Apple Podcasts
    5
    Tod_45
    United Statesa year ago
  • Too much giggling

    Keep it informative. I don’t know what you’re laughing at. I don’t understand your inside jokes but it’s uninteresting. use a better mic. Edit your Podcasts and redo it if it sounds crappy like this one did.

    Apple Podcasts
    1
    Pluteski
    United States2 years ago
  • Extremely distracting audio issues.

    Podcast Addict
    2
    marr75
    2 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Some episodes feel overly long or heavy on inside jokes, which can distract from content.
Valuable technical depth and practical strategies for AI tooling.
Audiences appreciate guest diversity and actionable insights for enterprise AI applications.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#231
Denmark/Technology

Talking Points

Recent interactions between the hosts and their guests.

Search Agents with Nandan Thakur - Weaviate Podcast #137!
Q: What are the key challenges and milestones you see for evaluating search agents going forward?
Key challenges include building meaningful benchmarks that reflect real-world usage, evaluating precision and recall in multi-hop and long-horizon tasks, and developing efficient, cost-aware architectures that can perform high-quality reasoning without prohibitive compute or API costs. Milestones involve scalable benchmarks like BrowseComp variants, multilingual and multi-model extensions, and practical deployment patterns such as internal search APIs and memory systems.
Search Agents with Nandan Thakur - Weaviate Podcast #137!
Q: And so maybe even before we talk about Orbit, if I could just ask, how do you currently define a search agent?
A search agent is best viewed as a system that uses a browser-like toolset to browse and retrieve information from multiple sources, combining search and reasoning to answer questions. It is more than a single retrieval step; it orchestrates several tools and often performs iterative verification to reach reliable results.
Data Agents with Shreya Shankar - Weaviate Podcast #135!
Q: What exactly is a data agent, and why is it such a broad concept?
A data agent is envisioned as a system that can access multiple databases and data sources, understand schemas, perform necessary computations, and reason to provide accurate answers to user questions, even when data lives in disparate formats.
Pyversity with Thomas van Dongen - Weaviate Podcast #132!
Q: How do you see the line between diversification algorithms and topic modeling?
Diversification algorithms are faster and can efficiently handle real-time scenarios, unlike clustering algorithms which may be slow and complex.
Pyversity with Thomas van Dongen - Weaviate Podcast #132!
Q: What are the different algorithms in Pyversity and how do they differ?
These algorithms, like MMR and DPP, differ in how they balance relevance and diversity, with DPP optimized for volume in the embedding space.

Audience Metrics

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Frequently Asked Questions About Weaviate Podcast

What is Weaviate Podcast about and what kind of topics does it cover?

This show centers on machine learning, AI tooling, and practical deployments of retrieval, vector databases, and AI-assisted workflows. Episodes frequently feature researchers, engineers, and industry practitioners discussing topics like semantic search, RAG, LLM optimization, and enterprise AI integration, often with hands-on guidance, real-world use cases, and demonstrations of new tools. A notable strength is the depth of technical detail presented by guests who are active contributors to cutting-edge AI research or product development, making it valuable for listeners who want implementable insights and a clear view of where AI tooling is headed.

A standout aspect is the consistent focus on retrieval-augmented approaches and the interp... more

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Which podcasts are similar to Weaviate Podcast?

These podcasts share a similar audience with Weaviate Podcast:

1. Training Data
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How many episodes of Weaviate Podcast are there?

Weaviate Podcast launched 3 years ago and published 139 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Weaviate Podcast?

Recent guests on Weaviate Podcast include:

1. Başak Eskili
2. Xueguang Ma
3. Shreya Shankar
4. Amélie Chatelain
5. Antoine Chaffin
6. Doug Turnbull
7. Trey Grainger
8. Matthew Russo

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