21–30 of 253 posts
Very wow. Shame they assumed everyone has "bc"...
P ./cool.sh: line 31: bc: command not found ./cool.sh: line 34: bc: command not found ./cool.sh: line 37: bc: command not found E ./cool.sh: line 31: bc: command not found ./cool.sh: line 34: bc: command not found ./cool.sh: line 37: bc: command not found Very wow. Shame they assumed everyone has "bc"...
> I guess Uniqlo is run through Windows though: one thing that struck me was the font, which I’m almost certain is Consolas, Surely this would use whatever font the virtual terminal profile was set to? I don’t know of any method to choose a virtual terminal font from bash and don’t see any code that addresses it?
They're referring to the font on the T-shirt.
I thought it was funny that the author used a variety of OCR tools with mixed success before spending a lot of time manually fixing up the output from the best one, rather than just typing it in
I thought it was funny that the author used a variety of OCR tools with mixed success before spending a lot of time manually fixing up the output from the best one, rather than just typing it in
OCRing this is a nightmare and is a good benchmark to any self-proclaimed good OCR/vision model. I think though it could likely be easily OCR'd if you give the image to any decent agentic harness with a good vision model, e.g. newest Claude/GPT ones, and tell them to split the image per lines, and then just OCR each line individually. I wonder if the script itself was written by an LLM before obfuscation? There seem…
The congratulations text is both in English and Japanese. Contains a single heart emoji.
There was an intention to have a cyan to orange gradient, but the range starts in an ANSI block, ends halfway through the 256 color block and 256 terminal colors are not arranged like a gradient at all.
There's no sleep at the end of the loop where I feel like an LLM would add that defensively.
OCRing this is a nightmare and is a good benchmark to any self-proclaimed good OCR/vision model. I think though it could likely be easily OCR'd if you give the image to any decent agentic harness with a good vision model, e.g. newest Claude/GPT ones, and tell them to split the image per lines, and then just OCR each line individually. I wonder if the script itself was written by an LLM before obfuscation? There seem…
Definitely LLM. No humans write that many comments.
My code usually clocs at 50/50 (or thereabouts)[0]. Has, since my very first real engineering project (in 1987)[1]. I discuss in detail, here[2].
But one reason that I like LLMs, is that they help me to write even more documentation. I have found that I can instruct an LLM to revise my documentation, and make it even more effective.
[0] https://github.com/ChrisMarshallNY (My GH profile. Pretty much everything there, is like that -has, since long before LLMs were a broken rubber on the drug store shelf).
[1] https://littlegreenviper.com/wp-content/uploads/2022/07/TF30... (Downloads a PDF)
OCRing this is a nightmare and is a good benchmark to any self-proclaimed good OCR/vision model. I think though it could likely be easily OCR'd if you give the image to any decent agentic harness with a good vision model, e.g. newest Claude/GPT ones, and tell them to split the image per lines, and then just OCR each line individually. I wonder if the script itself was written by an LLM before obfuscation? There seem…
Definitely LLM. No humans write that many comments.
Especially in a case like this, I would definitely write a lot of comments to aid in understanding, thus increasing trust so people would try it out and tinker with it.