Summary
Austin: event on machine learning fundamentals.
Why it matters
Fundamentals matter: data, evaluation, and failure modes are what keep AI projects from turning into demo-ware.
Tokenmaxxing angle
Run small experiments first, measure wins, then scale. Don’t burn tokens/compute before you can evaluate improvement.
Source takeaway
The listing frames this as a event at Kitty Cohen's focused on machine learning fundamentals.