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principal component analysis (PCA)

In short, PCA is a technique to reduce complexity and find the most important patterns in our data.

Imagine we have a huge spreadsheet with tons of columns (like tracking a person's height, weight, age, income, shoe size, etc.). It's a lot of information to look at all at once.

PCA is a way to simplify that complex data.

It squishes all those columns down into just a few new, special columns called "principal components." These new components are smart combinations of the original ones and are designed to capture the *most important* information.

Think of it like this:

* Making a smoothie: We start with lots of different fruits (strawberries, bananas, blueberries, mangoes). Instead of trying to taste each fruit separately, we blend them into a smoothie. The smoothie captures the main flavor profile of all the fruits combined. PCA is like making a "data smoothie."
* Summarizing a movie: Instead of describing every single scene (the original data), we just tell someone the main plot points (the principal components). We lose some minor details, but we get the main story across much more efficiently.

what's it used for?

It's used all over the place!
* Machine Learning: To make it easier and faster for computers to find patterns.
* Image Recognition: To simplify images so a computer can recognize faces or objects.
* Finance: To find the main factors that influence the stock market.
Forwarded from HackerNews Summary
The /o in Ruby regex stands for "oh the humanity "

🔸The /o regex modifier in Ruby causes a regular expression to be evaluated only once, even if it's inside an instance method or loop, due to the once instruction in the Ruby VM. This can lead to non-deterministic behavior and thread safety issues, making it generally not recommended to use the /o modifier.

02 Aug 2025

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Winners of the International Obfuscated C Code Contest

https://github.com/ioccc-src/winner
CVE-2025-54801: Go Fiber Crashes in BodyParser Due to Unvalidated Large Slice Index in Decoder

When using Fiber's Ctx.BodyParser to parse form data containing a large numeric key that represents a slice index (e.g., test.18446744073704), the application crashes due to an out-of-bounds slice allocation in the underlying schema decoder.

The root cause is that the decoder attempts to allocate a slice of length idx + 1 without validating whether the index is within a safe or reasonable range. If idx is excessively large, this leads to an integer overflow or memory exhaustion, causing a panic or crash.

Impact:
- Application panic or crash on malicious or malformed input.
- Potential denial of service (DoS) via memory exhaustion or server crash.
- Lack of defensive checks in the parsing code causes instability.

#cve
https://vast.ai/

Why would a H200 cost less than an H100 on AWS?
.sh dig @ch.at "hello, who are you?" TXT +short
Do It by Code
.sh dig @ch.at "hello, who are you?" TXT +short
ExitCode: 0
"Hello! I\226\128\153m an AI language model created by OpenAI. How can I assist you today?"