Fatfort
fat-fort is an early-stage effort in adversarial machine learning and computer-vision robustness — auditing where models break, and how to certify that they don’t. Built in the open, honest about the stage: no invented clients, no borrowed logos, no certifications that don’t exist yet.
The mark is a 2×2 grid whose corners read TT · TF · FT · FF. fat-fort is the FF corner (in red); its sibling tutorsfirst is the TF corner — two cells of the same matrix.
What it explores
- Adversarial examples
- tiny, deliberate perturbations that flip a model’s prediction while looking unchanged to a human.
- Certified robustness
- provable guarantees over a bounded neighbourhood of an input — not merely “we couldn’t break it”.
- Honest evaluation
- robustness claims are easy to overstate; the real work is measuring them without fooling yourself.
Pointers
- fatfort.com — the project’s home.
- tutorsfirst — sister project (tutorsfirst.com.au), an Australian tutoring marketplace where every tutor is credential-verified.
- abaj.ai — main site, writing, and past work.
Reach the fort at hello@fatfort.com.
Backlinks (3)
1. TutorsFirst /roam/tutorsfirst/
tutorsfirst is an Australian tutoring marketplace — find a trusted, verified tutor by subject, level and suburb. Browsing is free, tutors list free and keep 100% of their lesson fees, and students pay one small flat connection fee to swap contact details. No subscriptions, no commission.
“We all die. The goal isn’t to live forever, the goal is to create something that will.” — Chuck Palahniuk
Originally the AI suffix stood for archived intellect, however these days it has concretised to becoming an Augmenting Infrastructure — a place from which to branch out in many directions.
Within this site you will find self-contained material in the form of project posts and blog posts, but also external links 1 to other work – my own as well as not.