Weaviate Podcast #13. Rick Lamers, CEO, and Founder of Orchest.io. Orchest is a tool targeted at data scientists and this software simplifies building data pipelines.

Weaviate Podcast #12. Please check out Composer from MosaicML! https://github.com/mosaicml/composer Jonathan Frankle is the Chief Scientist at MosaicML and a PhD student in Machine Learning at MIT. Jonathan is the first author of “The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks” which won an ICLR best paper award. You can learn more about Jonathan Frankle here: http://www.jfrankle.com/.  Here is an explanation of how to use the Python library of Composer: https://www.youtube.com/watch?v=Xi_5w...

Weaviate Podcast #11. You can now use Weaviate as the document store for DocumentArray in Jina AI. We had the pleasure to talk with their CEO Han Xiao. See the timestamps below what it is all about, or check out the recap from Henry AI!

Weaviate Podcast #10. A guided conversation about HNSW by Connor Shorten between Yury Malkov, Staff ML Engineer at Twitter and the co-inventor of HNSW, and Etienne Dilocker, the co-founder of Weaviate. Check the timestamps below!

Weaviate Podcast #9. Karen Beckers, Data Scientist from Squadra Machine Learning Company, gives insightful information about how to use vector search in eCommerce in this podcast with Connor Shorten. Some topics are image-based datasets, vector search for data scientists, the future of eCommerce, and many more! See the timestamps below for more information.

Weaviate Podcast #8. Brady Neal from Oogway talks with Connor Shorten from Henry AI Labs about causal inference and many more. See the timestamps below to check out what this podcast is all about.

Weaviate Podcast #7. Arvind Neelakantan, Research Lead at Open AI, talks with Connor Shorten about their newly released embeddings API, his work at Open AI, the integration into Weaviate, and more.

Weaviate Podcast #6. Alex Cannan, a Machine Learning engineer at Zencastr, talks with Connor Shorten about a really exciting use case of applying search to look through podcast transcription. Topics discussed are the need for fine-tuning, building your own vector database versus Weaviate, data privacy for Deep Learning applications, and many more!

Weaviate Podcast #5. Katie is a knowledge management bot, continuously improving, self-learning, and trained by humans. Under the hood, Katie is powered by the Weaviate vector search engine, during this podcast, Katie's Michael Wechner will talk about all things vector search and more!

Weaviate Podcast #4. NLP frameworks like Deepset's Haystack are powerful tools to help data scientists and software engineers work with the latest and greatest in natural language processing. In this interview, Malte Pietsch will be talking about Haystack and how they leverage the Weaviate vector search engine as a persistent storage engine for their data and vector representations.