What works, the pros and cons, and example code for each approach — If some of the terminology I use here is unfamiliar, I encourage you to read my earlier article on LLMs first. There are teams that are employing ChatGPT or its competitors (Anthropic, Google’s Flan T5 or PaLM, Meta’s LLaMA, Cohere, AI21Labs, etc.) for real rather for cutesy demos. Unfortunately, informative…

Maximize the leverage you get from data by applying product management principles — Many organizations aspire for their technology to go from being a cost to being a differentiator — this is true for data technologies as well. The way you’ll often hear this aspiration expressed is “we want to treat data as a product”. Different definitions A few years ago, what many executives meant…

What the best organizations will be doing in 2023 — Looking ahead to 2023, I foresee a few trends that will play out in the data and AI space. If you are a leader of a data function, it might be worth aligning your product roadmaps to take advantage of these trends. Becoming better in using data is a journey…

And how to use them effectively anyway — ChatGPT has sparked the imagination, and fears, of many people, but I find that many misunderstand what ChatGPT actually is. Instead, they get caught up in what it seems to be. My goal in this article is to get you to the point where you can come up with potential…

How to choose the product to build your data platform upon — An organization that seeks to get better at how they use data and AI will need to get their data architecture into shape. Assuming that you are going to be building your data platform on the cloud, you will find yourself trying to make the choice between Snowflake, Databricks, BigQuery…

The key question for infusing your organization with ML is “who” not “how”. — The big decision that you as a leader have to make on ML is who​ in your organization does different parts of the ML workflow. Who does the task influences the how — not considering this question at design phase is a key reason why many organizations find it difficult…

Keep It Simple: the complexity of full MLOps is rarely needed — MLOps started from a straightforward problem statement — that the technical debt associated with ML models becomes intolerable if the models are not adjusted over time to account for changes in the environment. Since that 2015 observation, ML models and frameworks have been built that make it relatively easy to…

And the limitations (today!) of this approach — The authors of Stable Diffusion, a latent text-to-image diffusion model, have released the weights of the model and it runs quite easily and cheaply on standard GPUs. This article shows you how you can generate images for pennies (it costs about 65c to generate 30–50 images). Start a Vertex AI Notebook The Stable Diffusion model…

A step-by-step guide to preparing for, and doing the hike. — I hiked the 18-mile one-way trail across the Enchantments in July 2022. In this article, I’ll talk about what the Enchantments are, how I prepared for the hike, the logistics of the hike, and share my experience of the hike itself. What are the Enchantments? The Enchantments is an area near Leavenworth in Central…