Data Science Weekly - Issue 665

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Data Science Weekly - Issue 665<br>Curated news, articles and jobs related to Data Science, AI, & Machine Learning<br>Data Science Weekly<br>Aug 20, 2026

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Issue #665<br>Aug 20, 2026

Hello!<br>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.

Editor's Picks

Geolocating Random Islet Image Using Geometry & CUDA GPU Programming

This is a photo of a resort located on an island":

a) What is the name of the resort?<br>b) What are the coordinates of the island?<br>c) In which cardinal direction was the camera facing when the photo was taken?

In my opinion, solving this challenge with Google Lens is wasting a fun opportunity, so I decided to solve it with math and programming…

Improving heuristics for A* search<br>On my Introduction to A* page I cover the basics of the A* graph search algorithm for finding shortest paths…On this page I’ll show a way to speed up A* by adding “landmark nodes”….At the end of the page are demos of how this technique helps with maps from real games. I use grids for the visualizations on this page, but landmarks work for any type of graph, not only grids. The best part is that it’s not much code, sometimes only 20 lines. It can be combined with most other optimizations…

Everything after training<br>Training teaches a model what it knows. Inference is everything that happens afterward, every time somebody uses it, and it is where the bill actually lands. Serving a generative model well means working across a strange range of the stack: attention kernels at one end, GPU procurement across three clouds at the other. This is an interactive companion to Inference Engineering by Philip Kiely. It follows the book’s structure and covers the same ground, with the explanations rewritten and simulators built for the parts that are easier to understand by turning a dial than by reading a paragraph…

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Data Science Articles & Videos

Git at any scale<br>The challenge in hosting Git repositories at scale is inherent in the design of Git itself: a distributed version control system means that all instances of a repository are identical. There’s nothing special about the repository on a Git server that doesn’t apply to a repository on a developer’s laptop. Although at first it may appear that this makes hosting Git repositories straightforward (simply put an HTTP daemon in front of an on-disk copy of a repository and you’ve got a Git server going!), there are many hard scalability and reliability challenges that make this quite the opposite…

What’s the most counterintuitive statistical fact that’s actually true? [Reddit]<br>I’m looking for examples that completely changed the way you think about probability, statistics, or data analysis…

Harnesses are Situated Agents<br>Harrison Chase once excitedly shared an insight that agents are comprised of 4 things: a system prompt, a planning tool, a file system, and subagents. In the year-plus since he said that, I think this remains largely true. (Though you might tweak it to have general tools, etc.) Lately, we’ve been experiencing a wave of harnesses. It seems like everyday a new coding harness lands. I’m sure we’ll see another few dozen before the month is out…We’ve seen enough at this point that the common patterns are starting to emerge. Each brings something unique, but they’re more alike than different. And that’s great, because that lets us find the metapattern here. Which brings us back to “situated agents.”…

Learning MegaGem, from self-play to price discovery<br>We study MegaGem, a three-player, general-sum, imperfect-information auction game developed by Jane Street, and train a 4B specialist to play it…MegaGem combines three familiar strategic games. In Figgie, each player observes only part of the supply and must infer fair value from what others are willing to pay and what is revealed over time. In Splendor, public objectives create races while players also need to think about improving their own position, preserving flexibility, and blocking opponents. In poker, hidden hands and previous actions incentivize opponent modeling while position and stack sizes determine which late-game outcomes can still be forced. MegaGem further adds repeated sealed-bid auctions…

No, local models will not win<br>Every time a new open-weight AI model is released, people say that local models are the future. Why spend billions of dollars building out datacenters when everyone will just be able to run AI models on their laptops or phones? I think this idea is doomed. No matter how strong open-weight models get, most inference will always happen in AI datacenters….

What Is Reasoning<br>A few weeks ago a paper was shared that showed how to extract reasoning traces from...