Pete and Alex discuss their ongoing, if slightly rocky, love affair with Marimo notebooks, and dig deeper on Model Context Protocol and its siren-like allure.

Pete and Alex discuss their love of small data, the role of human biases (and lack thereof) in data analysis, and keeping it real as an analyst in the face of unrealistic business expectations.

Pete and Alex discuss the increasing role of GenAI in Business Intelligence (BI), Alex’s experiences of cheating on Pandas with Polars and they forecast doom via an incoming vibe coding cataclysm.

Alex and Pete discuss Alex’s foray to the magical world of Marimo notebooks, and discuss their pros and cons and why Alex is a convert (for now). Pete raises the problems that arise from finding that “unicorn” client too early in a business’s life.

Pete and Alex continue their epic chinwag on how to knowledge base. In this episode they discuss the challenges of Retrieval Augmented Generation (RAG), effectively chunking text data, how to know what “good” looks like, and Alex gets a bit shirty about LLMs apparently reinventing programming.

Alex and Pete discuss the nature of knowledge bases, what they are and what they’re not, some of the platforms and tools for creating and maintaining them, before realising that they have so much to say there’s going to need to be another episode!

Alex and Pete discuss the pitfalls of using averages as key performance indicators, and explore Decentralised Autonomous Organisations (DAOs) and their potential use in art collectives and other community-minded organisations, as well as the possible implications of AI in business decision-making.

Alex and Pete debate the merits of flat files versus complex databases – a battle as old as time (or at least, as old as relational databases). They also uncover CHIP.AI, a no-code AI assistant builder, proving that even the most technically challenged can harness the power of AI. Tune in for some data-science shenanigans!

Things get heated is Alex and Pete debate the merits of LLMs for authoring books, the dangers of using labels like “PhD level thinking” to models, and the limitations of the associated benchmarks, and observe the creaky state of the stock market from a tech and AI perspective. Here’s the links to various sources for […]

Alex and Pete discuss the creation of their podcast’s visuals and soundtrack using AI tools, the concept of the confusion matrix in machine learning, and the importance of questioning overly accurate models. They also explore how data can provide insights into workplace productivity and team dynamics.