AI Internship Navigator
Find a realistic entry point into a CS career
What it does
An evidence-informed career and internship matcher for early CS students. Explore eight career paths, rank realistic next experiences, identify skill gaps, and receive a seven-day action plan using BLS and O*NET data.
An explainable internship matching tool for early computer science students.
Explore where computer science graduates work, then turn your current skills and available time into a realistic next project or internship. These eight directions cover the largest and fastest-growing technical occupations in current U.S. labor projections. Compare scale, momentum, and the kind of problems each path solves. Source: U.S. Bureau of Labor Statistics, 2024 National Employment Matrix. “Web & UX” combines web developers and web/digital interface designers; its growth rate is employment-weighted. Transform data into decisions, models, and reliable AI experiences. Turn repeated technical problems into clear, scalable solutions. Translate user pain points into a feasible system…from ai-internship-navigator.wiry-tang-7257.chatgpt.site
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OpenTrailPaper is open-source bike computer firmware for the LilyGO T5S3 4.7" E-Paper PRO. It supports offline maps, GPX routes, FIT recording and Bluetooth sensors.
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Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com