© 2024 Tim Menzies, [email protected]
BSD-2 license. Share and enjoy.
The SE and AI literature is full of bold experiments that try a range of new ideas. But some new ideas are better than others. With all little time, and lots of implementation experience, we can focus of which ideas offer the "most bang per buck".
I say all this since, for over two decades, I have been mentoring people about SE and AI. When you do that, after a while, you realize:
- When it is all said and done, you only need a dozen or so cool tricks;
- Other people really only need a few dozen or so bits of AI theory;
- Everyone could have more fun, and get more done, if we avoided the same dozen or so traps.
So I decided to write down that theory and those tricks and traps (see below). I took some XAI code (explainable AI) I'd written for semi-supervised multiple-objective optimization. Then I wrote notes on any part of the code where I had spent time helping helping people with those tricks, theory and traps.