Musings on the making of software, and everything around it.

I've been doing plenty of R&D and simply toying around of recent with various ML models (computer vision & language models for the most) but have been particularly fascinated in Segment Anything (SAM) capabilities, and attempted to bring its magic into 3D through THREE.js

3rd's lesson's notes on the excellent Fast.ai Practical AI Ethics course - now getting into practical ways to apply ethical frameworks via tools and processes

Second lesson's notes on the excellent Fast.ai Practical AI Ethics course, this one treating on Algorithmic "fairness" & biases , what are they and discussions on how they can better be prevented

Decided to share my notes on the excellent Fast.ai Practical AI Ethics course, as I believe it to be essential information for anyone, particularly for software engineers & data scientists, "people in the room" in the making & training of AI models, hopefully to lead to bette ethical considerations. Lesson 1 is on Disinformation, and oh my this is scary already...

Knowledge and cultural capital play a crucial role in the organisation's resilience, and its ability to adapt to the unalienable constant of change, reinvent itself, and overcome its peculiar challenges; what constitutes the knowledge capital of a technology organisation, including its people skillset and expertise, how efficiently ideas and information flows, as well as its (first party) intellectual property, is highly indicative of its true value, making it an essential nurturing for its thriving