124 private links
Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good company.
Everything you wanted to know about the JSON format.
Super nice story about the Unix OS.
A website about selecting and classifying text editors used in programming systems. These are the programming text editors such as Emacs, VI, Multiedit, slick, Slickedit, ISPF, Notepad, VI and VIM that are used by the vast majority of programmers on UNIX, Windows, VAX, and Mainframe systems. The structure of the website allows any vistor to leave their opinions, knowledge, and mark on the website for others to enjoy.
A website about selecting and classifying text editors used in programming systems. These are the programming text editors such as Emacs, VI, Multiedit, slick, Slickedit, ISPF, Notepad, VI and VIM that are used by the vast majority of programmers on UNIX, Windows, VAX, and Mainframe systems. The structure of the website allows any vistor to leave their opinions, knowledge, and mark on the website for others to enjoy.
Roben Kleene: Introducing `rep` & `ren`: A New Approach to Command-Line Find & Replace, and Renaming
How to Use Rep
Record a chess game live and upload the PGN to Lichess - GitHub - Pbatch/CameraChessWeb: Record a chess game live and upload the PGN to Lichess
TDOA Sound Localization is determining the source of a sound when all you know is the differences in the time of arrival of the sound event…
CSS is powerful, you can do a lot of things without JS. - GitHub - you-dont-need/You-Dont-Need-JavaScript: CSS is powerful, you can do a lot of things without JS.
Convert PDF to markdown quickly with high accuracy - GitHub - VikParuchuri/marker: Convert PDF to markdown quickly with high accuracy
I use a system I call homegit to manage config files and scripts in my home directory on all my machines. The idea is simple: a Git repository rooted at ~ that I push to GitHub. I’ve used this system for 6 years and like it a lot. See below to set it up for yourself!
Automatically generated from the github page.
Your CLI home video recorder 📼. Contribute to charmbracelet/vhs development by creating an account on GitHub.
A curated list of modern Generative Artificial Intelligence projects and services - GitHub - steven2358/awesome-generative-ai: A curated list of modern Generative Artificial Intelligence projects a...
Gitless: a simple version control system built on top of Git
Online various measurement unit converters such as Temperature Converter, Area Converter, Angle Converter, Weight Converter etc
The accomplishments of large language models are attributed to the architecture that they follow - Transformer Models
A video editor with motion smoothing.
Super cool post on how to use electric grid frequency variations to match them into recorded sound clips, and basically allowing to timestamp the clip.
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still.
Twenty five years ago, The Big Lebowski blew into theaters like a tumbleweed on an empty street.
Domestic audiences barely showed up, with the comedic detective tale only earning $18 million. Audiences gave it a B CinemaScore. Critics sniffed that it wasn’t as good as Joel and Ethan Coen’s last release, the Oscar-winning Fargo.
But that was just, like, their opinion, man.
“I thought it was going to be a big hit,” star Jeff Bridges tells THR, along with sharing some of his personal behind-the-scenes photos from the film’s set, many of which appeared in his 2003 book, Pictures. “I was surprised when it didn’t get much recognition. People didn’t get it, or something.”
Comprehensions are a fantastic language feature in Python. They are an elegant alternative to manually constructing and populating data structures. Comprehensions are declarative – they just say what they are, as opposed to the implicit logic of manual looping. When it comes to simple object creation, comprehension should be used whenever possible. This goes not just for lists, but also for dictionaries and sets.
However, a widely perceived drawback to comprehensions is that they are harder to debug. When something goes wrong with a manual loop, the first thing to do is to print out the iterated values as they turn up. But the values of a list comprehension can’t be accessed, so print-debugging isn’t possible. To deal with this, it’s common to unravel the comprehension into a manual loop. Manual loops are uglier and more complicated and more error-prone than comprehensions, but that’s the price that must be paid for debuggability.
Cycling is one of the most sustainable modes of transportation. Increased ridership reduces fossil fuel consumption and pollution, saves space, and improves public health and safety. However, the bicycle itself has managed to elude environmental critique. Studies that calculate the environmental impact of cycling almost always compare it to driving, with predictable results: the bicycle is more sustainable than the car. Such research may encourage people to cycle more often but doesn't encourage manufacturers to make their bicycles as sustainable as possible.
Over many centuries, man’s obsession with time has led to increasing accurate ways to measure it. As the precision of techniques and instruments has increased over the years, so the units used to define time have become ever smaller.
The minute and the second have given way to the SI units of the millisecond, the microsecond, the nanosecond, the picosecond, and the femtosecond, which is the the length of time that light takes to travel the diameter of a virus.
Large Language Models (LLM) are on fire, capturing public attention by their ability to provide seemingly impressive completions to user prompts (NYT coverage). They are a delicate combination of a radically simplistic algorithm with massive amounts of data and computing power. They are trained by playing a guess-the-next-word game with itself over and over again. Each time, the model looks at a partial sentence and guesses the following word. If it makes it correctly, it will update its parameters to reinforce its confidence; otherwise, it will learn from the error and give a better guess next time.