Lesson learned building AI

This will be a short post. I toyed with plenty of AI and types of AI. LLM, Reinforcement Learning, Alphazero, from scratch or using large framework, etc There are a few major key points : If an AI can cheat, it will. It's a well known behavior since the infancy of AI. It will maximize reward by any means. If there is a bug to exploit, it will find it. Garbage-in, Garbage-out, is greatly underestimated. The quality of an AI is all about the quality of data. Not only for LLM but also for RL. I'm a DBA, my job is data. But even then, when it comes to AI it's not a fun job: Data quality is difficult to evaluate and this evaluation is time consuming. Sanity checklist If you're planning to work on AI, here are some things to remember: You'll never have enough compute power (yes, i repeat it again). You'll never have enough memory. Make everything resumable . Do not wait the end of a 12h long processing to save outgoing results. Save them asap. (learned the hard way and still manage to forget