Hello!
Once a week, we write this email to share the links we thought were worth sharing in the Data Science, ML, AI, Data Visualization, and ML/Data Engineering worlds.
And now…let’s dive into some interesting links from this week.
Things I want in a modern relational query language
I think one of the biggest causes of NoSQL is that while SQL is a powerful language because of the ideas behind it, it’s often implemented in clumsy and archaic ways. A language that learns from SQL could make relational data better to manipulate for programmers. I’ll try to think of things similar to those that I have dealt with in real-world situations and how a better query language could have helped. I’d love discussion on what else could be done…
ROC, Paper, Scissor, Shoe
We see ROC-AUC so often with classification models, we know the higher the better, but there is always that, well it depends scenario. I’ve always wanted to know what the pitfall is, how to avoid it, and how to do better. Let’s go from the basics on how to code ROC-AUC from scratch to decision curve analysis!…A new Observable
For more than a year, we’ve been quietly building an all-new Observable…Why undertake such a foolhardy effort? In short, we want Observable to be great. We aspire to deliver the best experience and anything less leaves us intensely dissatisfied…But also: AI. AI has enabled a vastly wider audience to wield code. Rather than obviating the need to understand code, we believe our mission to make code more accessible is more urgent than ever. We reimagined how computational notebooks could work with agents as the primary interface. Our new agent-first notebooks, called chats, are radically different from our human-first notebooks and yet seamlessly interoperate with them…
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Pre-release of Polars 2.0
We don’t aim to make a big feature release of Polars 2.0. In fact we hope it to be a boring experience for you. The reason we bump this major version is that we can get rid of design decisions made in the past that currently block us and then we want to change defaults to more sensible settings that will benefit a greater audience. The biggest default change will be that all LazyFrame queries now will run on the streaming engine. Casual Polars users can therefore expect huge improvements in memory usage and performance. In aggregate we expect the streaming engine to be easily 5x faster…A brief guide to French polling data
I was between jobs until recently, and had planned to contribute to public efforts around polling data and modeling. It turns out I will not have time to do anything substantial before the 2027 French presidential election, so I thought I should share the small amount of research I’m sitting on, in case someone else wants to pick it up…
A safe MySQL upgrade that wasn’t so safe
I get a notification that my database version has reached end of life, and it has to be upgraded. And the AWS extended support fees are a good motivator to upgrade as soon as possible. I had a green replica up, so I upgrade that, check that everything works correctly, and then switch over. Quick and easy, right? I thought so. However, not everything was correct…The Harness Is the Thing
When I started out as a developer, I had a graybeard observe for me that Moore’s law also applies to software…The last eighteen months have been a particular window of relentless improvement. Tab completions have given way to agentic coding which has given way to managing your agents with a harness. I’ve gone from being awed at the productivity gains to settling into the game and squeezing the lemon to see what I can get…What is a Harness?
If you’re main-lining into the AI newsfeed these days…your archetypal harness may already be an agent harness. And, this post was not written for you. This was written for those who may be curious to know what an agent harness is, but don’t, and have been too embarrassed to ask…Plot a pedigree in R: seven packages, each built for a different job
Seven R packages can plot a pedigree — kinship2, Pedixplorer, ggpedigree, pedtricks, optiSel, purgeR and visPedigree. We run the same breeding pedigree through each of them, time the results, and show which one fits which workflow…Mushroom hunting with LLMs: what can go wrong?
You see a mushroom in a forest, take a photo, and pass it to an AI chat…It might help with identification… but should we trust it with our health or life?…Introduction to Computer Graphics
WELCOME TO Introduction to Computer Graphics, a free, on-line textbook covering the fundamentals of computer graphics and computer graphics programming. This book is meant for use as a textbook in a one-semester course that would typically be taken by undergraduate computer science majors, with at least two semesters of programming as a prerequisite…Lessons from Operating a Large-Scale Distributed Database with a Replicated Key-Value Engine
This paper presents operational insights from running a log-structured merge-tree (LSM-tree)-derived key-value engine as the storage foundation of eBay’s cloud-native distributed database, which serves trillions of requests per day. We describe practical challenges and operational responses in snapshot binding and installation, scan overhead caused by visibility checks and predicate evaluation, CPU-constrained compaction, write amplification and noisy-neighbor effects in multi-tenant environments, and programmable compaction for unified maintenance…
Why AI Still Can’t Load the Dishwasher
In this episode of Building 32, MIT CSAIL associate professor Vincent Sitzmann explains why building AI that understands and interacts with the physical world is a fundamentally different challenge. Sitzmann explains why today’s AI still struggles with seemingly simple physical tasks and how researchers are teaching machines to see, predict, and interact with the world around them…Agents Still Can’t Automate Excel
AI agents have become much better at building and editing Excel workbooks over the past six months but still struggle to evaluate them. Agents especially struggle in environments where the Excel application isn’t installed, an increasingly common bottleneck as AI moves to always-on, scaled cloud setups. In those environments, agents may silently fall back to shadow analysis in hidden Python scripts…
CDC Wastewater Viral Activity Level Maps: Why Are They Bluer?
My favorite statistical podcast is actually about virology. The hosts of This Week in Virology (TWiV) are superb data communicators, and they often highlight statistical virtues or shortcomings of the virology and infectious disease papers they discuss…In TWiV 1352, recorded on August 26, 2026, Dr. Daniel Griffin used a statistical term that was new to me, saying that the Centers for Disease Control and Prevention (CDC) had “bluewashed” COVID-19 heat maps…With the new classification, states were shifted from redder colors toward the blue end in the map: Dr. Griffin called this shift bluewashing…Let’s look at the effect of the category change on state classification, and then explore why, statistically, the new method used to calculate categories led to the shift…Undo for Shiny, and the three problems that make it interesting
Shiny has no undo. Adding it means solving three problems: restoring a widget you have never heard of, stopping the echo loop, and a bug that only R’s lazy evaluation could produce…
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* Based on unique clicks.
** You can find last week's issue #666 here.
A research gap is not just “nobody has studied this before” [Reddit]
Public to Private Equity in the United States: A Long-Term Look
A RAG That Says “Not in This Document” Has to Show Four Kinds of Evidence
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Thank you for joining us this week! :)
Stay Data Science-y!
All our best,
Hannah & Sebastian