Tips for probabilistic software - jxnl.co
when in doubt, measure more, but more importantly: think hard about what you are optimizing for.
Ya Xu • Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing
how we should adjust probabilities when we encounter new data,
Rhiannon Beaubien • The Great Mental Models Volume 1: General Thinking Concepts
I followed this curiosity, to see if a tool that can generate something mostly not wrong most of the time could be a net benefit in my daily work. The answer appears to be yes, generative models are useful for me when I program. It has not been easy to get to this point. My underlying fascination with the new technology is the only way I have manag... See more
Simon Willison’s Weblog
How to write complex software
grantslatton.com
First, from Hill Climbing: even if you’re in the habit of sometimes acting on bad ideas, you should always act on good ones. Second, from the Metropolis Algorithm: your likelihood of following a bad idea should be inversely proportional to how bad an idea it is. Third, from Simulated Annealing: you should front-load randomness, rapidly cooling out
... See moreBrian Christian, Tom Griffiths • Algorithms to Live By: The Computer Science of Human Decisions
Probabilistic thinking is essentially trying to estimate, using some tools of math and logic, the likelihood of any specific outcome coming to pass. It is one of the best tools we have to improve the accuracy of our decisions.