Nicolay Gerold

How AI Is Built

Real engineers. Real deployments. Zero hype. We interview the top engineers who actually put AI in production. Learn what the best engineers have figured out through years of experience. Hosted by Nicolay Gerold, CEO of Aisbach and CTO at Proxdeal and Multiply Content.

Author

Nicolay Gerold

Category

Technology

Podcast website

www.howaiisbuilt.fm

Latest episode

Sep 11, 2025

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Episodes

#011 Mastering Vector Databases, Product & Binary Quantization, Multi-Vector Search 07.06.2024

Ever wondered how AI systems handle images and videos, or how they make lightning-fast recommendations? Tune in as Nicolay chats with Zain Hassan, an expert in vector databases from Weaviate. They break down complex topics like quantization, multi-vector search, and the potential of multimodal search, making them accessible for all listeners. Zain even shares a sneak peek into the future, where ve...

#010 Building Robust AI and Data Systems, Data Architecture, Data Quality, Data Storage 31.05.2024

In this episode of "How AI is Built", data architect Anjan Banerjee provides an in-depth look at the world of data architecture and building complex AI and data systems. Anjan breaks down the basics using simple analogies, explaining how data architecture involves sorting, cleaning, and painting a picture with data, much like organizing Lego bricks to build a structure. Summary by Section Introduc...

#009 Modern Data Infrastructure for Analytics and AI, Lakehouses, Open Source Data Stack 24.05.2024

Jorrit Sandbrink, a data engineer specializing on open table formats, discusses the advantages of decoupling storage and compute, the importance of choosing the right table format, and strategies for optimizing your data pipelines. This episode is full of practical advice for anyone looking to build a high-performance data analytics platform. Lake house architecture: A blend of data warehouse and...

#008 Knowledge Graphs for Better RAG, Virtual Entities, Hybrid Data Models 20.05.2024

Kirk Marple, CEO and founder of Graphlit, discusses the evolution of his company from a data cataloging tool to an platform designed for ETL (Extract, Transform, Load) and knowledge retrieval for Large Language Models (LLMs). Graphlit empowers users to build custom applications on top of its API that go beyond naive RAG. Key Points: Knowledge Graphs: Graphlet utilizes knowledge graphs as a filteri...

#007 Navigating the Modern Data Stack, Choosing the Right OSS Tools, From Problem to Requirements to Architecture 17.05.2024

From Problem to Requirements to Architecture. In this episode, Nicolay Gerold and Jon Erich Kemi Warghed discuss the landscape of data engineering, sharing insights on selecting the right tools, implementing effective data governance, and leveraging powerful concepts like software-defined assets. They discuss the challenges of keeping up with the ever-evolving tech landscape and offer practical ad...

#006 Data Orchestration Tools, Choosing the right one for your needs 10.05.2024

In this episode, Nicolay Gerold interviews John Wessel, the founder of Agreeable Data, about data orchestration. They discuss the evolution of data orchestration tools, the popularity of Apache Airflow, the crowded market of orchestration tools, and the key problem that orchestrators solve. They also explore the components of a data orchestrator, the role of AI in data orchestration, and how to ch...

#005 Building Reliable LLM Applications, Production-Ready RAG, Data-Driven Evals 03.05.2024

In this episode of "How AI is Built", we learn how to build and evaluate real-world language model applications with Shahul and Jithin, creators of Ragas. Ragas is a powerful open-source library that helps developers test, evaluate, and fine-tune Retrieval Augmented Generation (RAG) applications, streamlining their path to production readiness. Main Insights Challenges of Open-Source Models: Open-...

Lance v2: Rethinking Columnar Storage for Faster Lookups, Nulls, and Flexible Encodings | changelog 2 29.04.2024

In this episode of Changelog, Weston Pace dives into the latest updates to LanceDB, an open-source vector database and file format. Lance's new V2 file format redefines the traditional notion of columnar storage, allowing for more efficient handling of large multimodal datasets like images and embeddings. Weston discusses the goals driving LanceDB's development, including null value support, multi...

#004 AI with Supabase, Postgres Configuration, Real-Time Processing, and more 26.04.2024

Had a fantastic conversation with Christopher Williams, Solutions Architect at Supabase, about setting up Postgres the right way for AI. We dug deep into Supabase, exploring: Core components and how they power real-time AI solutions Optimizing Postgres for AI workloads The magic of PG Vector and other key extensions Supabase’s future and exciting new features Had a fantastic conversation with Chri...

#003 AI Inside Your Database, Real-Time AI, Declarative ML/AI 19.04.2024

If you've ever wanted a simpler way to integrate AI directly into your database, SuperDuperDB might be the answer. SuperDuperDB lets you easily apply AI processes to your data while keeping everything up-to-date with real-time calculations. It works with various databases and aims to make AI development less of a headache. In this podcast, we explore: How SuperDuperDB bridges the gap between AI an...

Supabase acquires OrioleDB, A New Database Engine for PostgreSQL | changelog 1 17.04.2024

Supabase just acquired OrioleDB, a storage engine for PostgreSQL. Oriole gets creative with MVCC! It uses an UNDO log rather than keeping multiple versions of an entire data row (tuple). This means when you update data, Oriole tracks the changes needed to "undo" the update if necessary. Think of this like the "undo" function in a text editor. Instead of keeping a full copy of the old text, it just...

#002 AI Powered Data Transformation, Combining gen & trad AI, Semantic Validation 12.04.2024

Today’s guest is Antonio Bustamante, a serial entrepreneur who previously built Kite and Silo and is now working to fix bad data. He is building bem, the data tool to transform any data into the schema your AI and software needs. bem.ai is a data tool that focuses on transforming any data into the schema needed for AI and software. It acts as a system's interoperability layer, allowing systems tha...

#001 Multimodal AI, Storing 1 Billion Vectors, Building Data Infrastructure at LanceDB 05.04.2024

Imagine a world where data bottlenecks, slow data loaders, or memory issues on the VM don't hold back machine learning. Machine learning and AI success depends on the speed you can iterate. LanceDB is here to to enable fast experiments on top of terabytes of unstructured data. It is the database for AI. Dive with us into how LanceDB was built, what went into the decision to use Rust as the main im...

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