There was a time when the idea of Magic: The Gathering crossing over with other franchises felt impossible. Magic just didn’t do that. When The Walking Dead showed up as a mechanically unique Secret ...

So, you want to learn Python, huh? It’s a pretty popular language these days, used for all sorts of things like making websites, crunching data, and even AI. The good news is, you don’t need to spend ...

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have introduced Recursive Language Models (RLMs), an inference-time paradigm that fundamentally reimagines how ...

Recently, a friend asked me a question that's been floating around every boardroom and business school: "With AI writing code, does programming still matter?" It's a fair question. Generative AI can ...

This is the fourth time I rebuilt this library from scratch to find the sweet spot between ease of use (beautiful is better than ugly!), testability (simple is better than complex!) and potential for ...

When something goes wrong with an AI assistant, our instinct is to ask it directly: “What happened?” or “Why did you do that?” It's a natural impulse—after all, if a human makes a mistake, we ask them ...

See here for an explanation of why there is no v13-v16 release. Kubernetes supports three minor releases at a time. "Support" means we expect users to be running that version in production, though we ...

MicroPython has become one of the most popular ways of programming microcontrollers, and the just-released MicroPython v1.24 adds support for the widely-used Raspberry Pi RP2350 and Espresif ESP32-C6 ...

Work is pushing AI pretty hard and some people are chewing up tokens like crazy. We had a session where one coworker showed his cursor setup and the different MCP servers he's tied into to automate ...

In today's edition of Data Science Code in Python + R we're going to tackle a fascinating concept. We're diving into the world of convolutions and recursion, two powerful tools you can utilize in your ...

While neural networks used in practice are often very deep, the benefit of depth is not well understood. Interestingly, it is known that increasing depth is often harmful for regression tasks. In this ...