Join Connor Shorten as he interviews machine learning experts and explores Weaviate use cases from users and customers.
Weaviate Podcast
Claim This Podcastby Weaviate
4.4(14 reviews)
140 episodes
Updated Daily
Accepts GuestsHas SponsorsLocation 🇺🇸
79
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality91
Social0
YouTube86
Engagement84
Podcast Overview
Join Connor Shorten as he interviews machine learning experts and explores Weaviate use cases from users and customers.
Language
🇺🇲
Publishing Since
12/5/2021
Unlock The Full Podcast Authority Score Report
See how your podcast performs across key metrics
79
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality91
Social0
YouTube86
Engagement84
8
Excellent Areas
2
Good Performance
9
Growth Opportunities
excellent
Episode Length
1h 3m
Performing excellently!
good
Publishing Consistency
Every 11 days
Recommendations available
Unlock the full report to see detailed tips
poor
Episode Thumbnails
Recommendations available
Unlock the full report to see detailed tips
+16 More Metrics
Unlock comprehensive insights including:
- • YouTube presence analysis
- • Social media reach metrics
- • RSS compliance scoring
- • Podcast 2.0 features
- • Technical standards
What's Included in Your Full Report
Detailed Analytics
- Complete breakdown of all 19 authority metrics
- Personalized recommendations for each metric
- Industry benchmarks and comparisons
- Technical RSS feed analysis and compliance scoring
Growth Strategies
- Step-by-step action plans for improvement
- Quick wins to boost your score immediately
- Pro tips from successful podcasters
Get your free podcast insights report
See how your show performs across every key metric
Instant delivery
No spam
Attract Better Guests
High authority scores make your podcast more attractive to industry leaders and influencers who want to appear on credible shows.
Secure Sponsorships
Sponsors look for podcasts with proven authority and engagement. Your score demonstrates your podcast's value to potential partners.
Grow Your Audience
Understanding your strengths and weaknesses helps you make data-driven decisions to expand your listener base effectively.
1 verified contact email on file for Weaviate Podcast
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
June 1, 2026
Knowledge Engineering with Bradley Allen - Weaviate Podcast #139!
<p>Dr. Bradley Allen brings five decades of AI history into a deep conversation on knowledge engineering, neurosymbolic AI, and the future of enterprise intelligence. The discussion begins with the boom-and-bust cycle of rule-based expert systems, AI winters, and why today’s large language model wave may be different. The conversation then turns to how knowledge is organized in practice, from personal piles of papers searched on demand to formal knowledge graphs built with classes, relations, ontologies, A boxes, T boxes, description logic, and subsumption-based reasoning. Allen explains why semantic web and biomedical ontology successes still leave unresolved questions about cost, maintenance, and whether LLMs can dynamically structure information in ways that preserve meaning. That leads into natural language concept definitions, LLM-based classifiers, rationales, probabilistic reasoning, and the challenge of updating classes as new edge cases emerge.From there, the focus widens to vector databases, semantic search, RAG, topic modeling, distributional semantics, and the ongoing revision required for systems that can never be “once and done.” Allen connects modern LLM behavior to the long history of formal languages, from Frege, Russell, Wittgenstein, Turing, and Gödel to theorem proving, soundness, completeness, paraconsistency, paracompleteness, and the pragmatic tradition of meaning through use. The closing stretch explores world models, reinforcement learning, tool-using agents, enterprise knowledge workflows, role-based access control, governance, normativity, and alignment, ending on the need to build accountable AI systems that channel powerful technology toward responsible outcomes.</p>
May 18, 2026
Booking.com and Weaviate with Başak Eskili - Weaviate Podcast #138!
<p>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 keyword matching to semantic retrieval as internal teams needed embeddings, similarity search, and eventually GenAI RAG workflows. Başak explains why OpenSearch was a practical first step on AWS, how adoption grew across teams, and why hundreds of millions of embeddings, strict latency requirements, complex filtering, and rising concurrency pushed the platform toward Weaviate.The discussion then moves into Booking.com’s partner-to-guest messaging agent, a production GenAI system that helps accommodation partners answer guest questions about check-in, parking, special requests, and reservation details. Başak breaks down the tool-calling architecture, where Weaviate retrieves relevant response templates while GraphQL APIs fetch property and booking context. The agent can suggest templates, craft grounded replies, or decline to answer and leave the conversation to a human, highlighting the practical role of human-in-the-loop design. Evaluation spans offline datasets, LLM-as-a-judge scoring, A/B testing, and live partner feedback.From there, Başak describes the platform engineering behind AI at Booking.com: a central MCP server for internal APIs and external tools, a GenAI gateway for model access, PII reduction, guardrails, prompt injection detection, logging, traceability, and cost tracking across large-scale LLM usage. She also details Booking.com’s evaluation process of Weaviate, including 100 million embeddings, filtered vector search, multi-threaded concurrency testing, reads during writes, and cost-efficient infrastructure provisioning.The episode closes with Başak’s path from computer science and NLP to MLOps and AI platforms, then looks ahead to practical AI, personalized travel agents, and memory systems that capture user preferences, session context, semantic memory, and long-term personalization for future agentic travel experiences.</p>
May 5, 2026
Search Agents with Nandan Thakur - Weaviate Podcast #137!
<p>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 opens with reflections on his PhD journey, tracing the field's shift from ColBERT-style models and sparse retrievers through RAG and into today's agentic search paradigm where LLMs iteratively search, reason, and refine.The discussion dives deep into how Orbit generates multi-hop, riddle-style training queries using DeepSeek's API on a personal laptop over four to six months, making high-quality search agent training data accessible without massive compute budgets. Thakur draws a sharp distinction between deep research (broad, multi-tool report generation) and search agents (focused on search and browse tools to answer specific questions), then connects Orbit's multi-hop queries to BrowseComp's filter-style riddles where each clue narrows the answer space like a funnel. The conversation explores the design of deep research harnesses, chunking strategies, Anthropic's contextual retrieval for entity disambiguation, context compaction to manage bloated agent contexts, and memory services like Weaviate's Engram for compressing search results between reasoning rounds.From there, the episode tackles sequential versus parallel search trajectories, the pass@K approach to rollouts in GRPO training, and whether isolated trajectories should share progress through message passing. Thakur makes a compelling case for training search agents to produce keyword-focused queries optimized for BM25 versus semantic queries for dense retrieval: the idea that one query does not fit all search engines. The conversation closes on future directions: efficiency-focused Pareto frontiers for search agents, long-form report generation evaluation through TREC RAG, and the coming wave of multilingual and multimodal search benchmarks.</p>
140 total episodes available
Recent guests on Weaviate Podcast
Guests from recent episodes — sign up to see every guest that has ever appeared on this show.
Hailey Joren
Guest
Nandan Thakur
Guest
Rajesh Jayaram
Guest
Roberto Esposito
Guest
Similar Podcasts
Discover related shows you might enjoy
Deep-dive analytics for Weaviate Podcast
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is Weaviate Podcast?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 9 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.