lila VS awesome

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Lichess - Online Chess Server. Scala, TypeScript

> the player who committed more blunders lost 86% of the time

In some sense this is almost tautological. While finding an exact definition for a chess blunder isn't straightforward, here is one example from the Lichess UI:

https://github.com/lichess-org/lila/blob/b527746b179cdde6438...

Basically, if you make a move which decreases your winning probability more than 14% over the best move, that's a blunder. But winning probability is a nonlinear function of stockfish centipawns. A drop in 100 centipawns when you're up 15 points isn't a blunder. When the game was equal, it is.

Point is, by the time you know it's a blunder you already know something about the outcome of that move, that it swung the winning probability by more than 14%. So the analysis is kind of just measuring some function of winning probability and saying that it is highly correlated with winning probability.

If you want to improve make it your goal to play the best chess you can, not increase an arbitrary number. Watch YouTube series like John Bartholomew's "Climb the Rating Ladder" for some general insight into what you might be doing wrong. Read Irving Chernev's "Logical Chess: Move By Move" to see the thinking process of high level players. Do lots of puzzles (I like lichess.org for puzzles). And always analyze your games. When you analyze make it your goal to find at least two things you could have improved.

The easiest way to play against Stockfish is perhaps on https://lichess.org/, but it's not the only chess engine that evaluates positions with a neural network.

Lichess.com

if you actually like chess, try lichess.org, the free and open-source, no ads ever, premium alternative

In the days before "google it" was a synonym for "find it", we had different curated link sites, and even pyhsical magazines with hand-curated lists of links that people interested in a certain topic might find interesting. This still exists today in some forms, for example the "awesome lists" that you see for some programming topics, for example https://github.com/sindresorhus/awesome .

Just like there was a time when 90%-99% of all email traffic was viagra spam, I imagine in the future most of the internet by volume will be AI-generated trash, and those in the know will still circulate lists of where the other 1% can be found.

An even brighter scenario is that someone, maybe a kid tinkering in their garage, figures out how to make a search engine that finds the good stuff, doesn't immediately die to AI bot farms' SEO efforts, and is financially viable.

2. Awesome Lists

Software Engineering Blogs

He appears to be the original creator of the “Awesome X” repo: https://github.com/sindresorhus/awesome

Awesome React

I'm just going to leave this here: awesome git repo

You don't need any particular requirement to consult issues section on GitHub. If you need a place to follow along this post, my chosen repository for today's blog post is Awesome.

I have an awesome list GitHub repository that needs a few icons & a banner made. I was wondering if any students in graphic design would be willing to commission a few for me? I'm willing to pay either hourly, or by the project and can pay cash or venmo. Note that the art will end up as CC0, so you'd essentially be waiving any right to the artwork.

yah, come to think of it in the curated space, this reminds me of that awesome X family of github pages. Looks like someone compiled a bunch of them here https://github.com/sindresorhus/awesome#databases. I have found those to be highly valuable treasure troves pregnant with rich and relevant information.

10. Awesome