@Erox

the arch user orpheus to roast . I made it with node.js , nest hosting and the node service manager npm , thts all .

It is just my portfolio .

I am building an alarm clock based on esp-32-c3 , mainly it has 7 switches , 1 lcd display , a buzzer and an enclosure to cover the pcb and mount components thts the brief view but here i am using >shift my specific key among the 7 , same like a keyboard , also two alarm specific switches for snooze and stop , thts some normal thing but i pulled this off with only 5 gpios . Also on software side i will be using esp-hal i mean rust unlike standard c++ arduino and esp ide's , as a rustacean thts my duty :D

AUREK is a Rust-based security wrapper for yay that scans AUR packages before It fetches and analyzes PKGBUILD files to detect suspicious or potentially malicious behavior, including remote script execution, unsafe sudo usage, dangerous commands, obfuscation, suspicious downloads, permission changes, systemd or cron modifications, and other risky patterns. aurek can also use a local gemma model through llama.cpp for context-aware analysis. This works alongside its heuristic and regex-based detection to provide a stronger security check while keeping the analysis on the user's machine.If something suspicious is found, aurek shows the detected issues and asks the user for confirmation before allowing yay to The project is designed to be extensible, with plans for more detection methods, package managers, and security features.

Imagine someone just got released form hospital with a bunch of medical documents , prescriptions and now he is unable to read those all(might be due to different native language or low english proficiency or even too much papers), so they wd like to rely on a llm . Same goes for insurance , business logs or even a dev like me but it is scary to thing abt all our private data is directly sent to the llm, i mean real humans will review the data for preparing better dataset, i felt uncomfortable so i build hbp100. Its a ai to save privacy from ai .It is a ml model built with thousands of examples and it just swaps private data with place holders like [email protected] with [EMAIL_1] , the llm gets enough context(and if using the placeholder kills context my ml is designed not to mask or mask based on confidence ) to work without using users real data and after response my engine again swaps the place holder with the real data and as it runs on the users device .