Decoding Chess Boards: Ten Years of Computer Vision & AI | Part 1

[@chakra6666]

super awesome video, very cool to see all the different ways that you tried to solve the problem :)

[@samobot]

Cheers glad you enjoyed the process!

[@OMFGxIamxAxNinja]

This was an interesting watch! It was cool to see how different ML techniques could be used to solve the problem you were trying to solve, and your explanation on their respective drawbacks and advantages is fascinating. Would love to see part two of this!

[@samobot]

Cheers thanks for watching and glad you liked it! Yes I love trying to convey that often there isn't one 'true' algorithm for any problem, but different tradeoffs depending on what we're doing, which does surprisingly apply to the leetcode tech interview process too haha. And definitely, I'm working on the 2nd part now, stay tuned!

[@ATH42069]

this explainer Chad-tuber is top notch.

[@pfever]

Super cool, great work :)

[@samobot]

Cheers happy to hear it!

[@stayqurious]

still a learner but enjoyed every minute of this video!

[@samobot]

Happy to hear it!

[@stayqurious]

@@samobot i just started learning dsa and i want to be like u, if you were to give a single advice to young sam what it would be.

[@satellitesam]

@@stayqurious That's very nice of you to say! My suggestion: Try to find some toy application, game, or small project which uses computer programming techniques (say dsa) and also really excites you. Just start trying to code it up, start simple, and add on to it as you want, even if it takes years (...like this video heh), it's fun to do and since you're doing it by yourself you will pick up the skills of learning/researching/comparing/etc. as you go along. This is just one way to do things that worked for me, but I like it!

[@stayqurious]

@@satellitesam, thank you so much.

[@sirynka]

Have you implemented piece detection? If so I know who's job you're gonna take away (not really) There's russian channel that is reviewing chess games from various movies and cartoons. And he spends conciderable amount of time recreating the game from slivers of information.

[@samobot]

I've done some casual stuff in the past, but no real attempts yet! What's the channel? I think the step up from finding a chessboard to detecting pieces *accurately* is a pretty big one (I've seen some attempts at piece detection that work in very limited settings), part of the tough part is getting good data, synthetic data seems to have a lot of potential, so perhaps generating synthetic data with a comic-style rendering (perhaps even a stable diffusion Lora) may make this more possible. However, recreating games is a much larger problem than single image board or even piece detection. I appreciate the watch and comment, thanks!

[@brightonbackgammon7802]

@@samobot Schtopp!! I am from the future!! You will destroy chess as we know it with your amazing high fallutin' A.I.!! 😡 When combined with piece detection -> BCI -> internal chess engine in around 10 years time, just how exactly will you stop the chess cheaters please? 😉

[@samobot]

Hahaha thanks for the vote of confidence and while it's mostly in jest it is a good point, that chess detection could lead to more cheating in chess. I think the short term good news is that there still quite a large gap between finding the board and finding pieces, and honestly a human watching the game is easier to do and is probably how most such cheating would go anyway regardless of this software. Second, luckily most anti cheating mechanisms detect a human playing moves they likely wouldn't, and this does nothing to change that. Third, I'm a solo researcher so I highly doubt I'm at the forefront of chessboard detection, this is mostly a fun way for me to share my joy of computer vision and ML to others in a way people can hopefully connect with

[@brightonbackgammon7802]

​@@samobotglad you took it in good spirit! 1. Yes, for sure, a large gap now in 2024. However, I believe this gap will almost certainly be solved (probably by a self-iterating AI 'Agent') within 20 years, if not much less. 2. The anti-cheating algos might be fooled by strategically, deliberately throwing in a close 2nd or 3rd placed move by equity every now and then, at random. Perhaps the BCI co-pilot will even intelligently and dynamically optimise the frequency and scramble the pattern for anti-detection countermeasures 3. Your videos are great! Thanks for creating these 🥳

[@sirynka]

@samobot the channel is called "Борис Дядёра" (@boris_dyadyora)