- I've worked on a variety of projects, from building analytical tools
- performing reactive chemical safety to live feed processing for
- frantic work environments looking to improve service. I also do
- personal experimentation leveraging open source info streams ranging
- from human traffic around campus to watershed temperature monitoring.
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- My philosophy is that if it isn't explainable then you didn't learn
- anything. Data without sound methodology is at best meaningless and at
- worst counterproductive and costly. That's why I focus on
- hypothesis-driven multivariate analysis, bringing logical transparency
- and literal deductions back into digital analysis. Rather than letting
- heuristics make decisions for the world we think we know, we should be
- making discoveries and building new knowledge.
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Bring the scientific method to AI.
+ I got my start ~2017 reverse engineering probablistic logic models in
+ games and developing interfaces to recreate my findings for friends.
+ Now I develop tracable AI built on deductive reasoning, maintaning
+ scientific methodology in an industry obsessed with implicit rules and
+ exclusive empiricism. As the analysis grew more sophisticated, so too
+ did the tech stack - to the point that I now manage most services,
+ like this website, end to end, container image to insight visual.
+ I get bored and throw random stuff on this website. It's a form of
+ unprofessional development and I swear by this form of learning.