The point you make is important and valid, but I would like to correct the specific numbers for the audience watching from home. 100*2000 is 200 thousand, not two million, which comes to 1/10 millionth of the goal, or 0.00001%. Using the $1000 budget metaphor, that would make 1/10000 of a dollar or 1/100 of a cent.

Don’t feel bad about missing a zero here or there, especially early in the day <3

Speaking as a researcher in the AI/ML space, you see an interesting divergence at the upper end of familiarity. Some focus on the rapid recent growth of the technology and are quite enthusiastic about it, but others (myself included) focus much more on its limitations, especially driven by the type/quality of the training data used to make the models. I think it comes from different backgrounds prior to learning the tech. Computer science people tend to be in group one, whereas other scientists (biologists, physicists…) that adopt ML as a tool are more likely to be in group two. To be clear, all of this is my personal experience from personal interactions and literature review in graduate school, not some large scale survey.