Thank you. It seems largely ignored that LLMs still sample from a set of tokens based on estimated probability and the given temperature - but not on factuality or the described "confidence estimate" in the article. RAG etc. only move the estimated probabilities into a more factually based direction, but do not change the sampling itself
While this made me laugh and there is some truth to it, the nice thing when running the process described in the blog post is that you don't need to know what or how you want to count - the LLM has the knowledge to classify it correctly enough to get good estimations. Go and Rust are both good examples of words that have multiple meanings and are pre-/suffix to many other words.
In total numbers I got 539 jobs saying that they want Rust experience and 695 want Go experience. I think I should have added another line-chart showing the programming language distribution over time, thanks for the idea.
Yes, later this week I will follow up with something to tell a little bit about the animation and the sphere positioning, that graph was kind of the most fun in writing this blog post. Thank you for your feedback!
IMHO, I believe the peak was due to a combination of Zero Interest Rate Policy (ZIRP) and the pandemic, both of which have faded out this year. Elon Musk's highly publicized firing of a big part of the Twitter work force also set a precedent for lay-offs in the industry. But I am still optimistic that we will many such peaks ahead of us.