Conversations at the intersection of data engineering and business

with Kostas Pardalis & Eric Dodds

Episode 159

October 11, 2023

with Bob van Luijt

 – CEO & Co-Founder at Weaviate

This week on The Data Stack Show, Eric and Kostas chat with Bob van Luijt, the CEO & Co-Founder at Weaviate. During the episode, Bob discusses the technical and business aspects of vector databases, delving into their differences from other types of databases and the opportunities they present. Bob shares his journey and how his love for music relates to his work in machine learning. The conversation also covers the progression of database complexity and the emergence of databases designed for specific data types, limitations of existing databases for vector processing, the importance of simplicity and user-friendliness in the user experience, generative feedback loops, and more.

Episode 158

October 4, 2023

with Nick Schrock

 – Founder, Dagster Labs

This week on The Data Stack Show, Eric and Kostas chat with Nick Schrock, Founder of Dagster Labs. During the episode, Nick discusses his background at Facebook and his involvement in successful open-source technologies like React and GraphQL. Nick explains the mismatch between the complexity and available tools in the data infrastructure space, leading him to start Dagster Labs. The group also talks about the challenges and fragmentation in the data engineering industry, the need for better abstraction layers, the role of orchestrators, comparing it to GraphQL’s role in product engineering, the importance of data orchestration in the future of data infrastructure and engineering, and more.

Episode 157

September 27, 2023

with Amr Awadallah

 – Founder and CEO of Vectara

This week on The Data Stack Show, Eric and Kostas chat with Amr Awadallah, the Founder and CEO of Vectara. During the episode, Amr discusses his extensive experience in the data industry and his new company, Vectara, which focuses on enabling companies to integrate capabilities in their products using large language models (LLMs) with security, reliability, and ease of use. The conversation also covers the advancements in data, computing, and algorithms that have led to emergent behaviors in neural networks, the practical applications of Vectara’s technology, the challenges and considerations in working with large language models, the importance of addressing technology misuse and aligning different value systems in society, and more.