Meir's Monthly Learning Article

This month I want to highlight a video, The Misconception that Almost Stopped AI, by the Welch Labs YouTube channel. This video explores gradient descent – the method by which large language models (LLMs) are trained. Oftentimes I use my monthly articles to share a topic and apply my own learnings. This month I am sharing this video because it taught me a more about AI’s inner workings, and I find that worthwhile.

Simplifying complexity while retaining core truth is a challenging skill. I am not an LLM expert, so I deeply appreciate when someone is able to explain an incredibly complex topic in an understandable way. I strive to create simplified mental models that drive understanding and high-quality decisions in my life, both personally and professionally. I frequently see people fail at attempting to simplify complexity, either because the simplification removes too much context or because the simplification is not simple enough.

This video beautifully walks the line. If you are interested in understanding more on how LLMs work, this video is well worth your time.

“For gradient descent to become fully stuck in a local minimum, it would have to get stuck in every dimension at once…”