This obviously isn't core to the point OP is making, but I find it hard to believe that someone of "average" intelligence can't learn about advanced machine learning.
This obviously isn't core to the point OP is making, but I find it hard to believe that someone of "average" intelligence can't learn about advanced machine learning.
Recently, I've been in the position where I'm the only one taking ownership of new work and initiatives, sometimes to my own detriment. For example, I took on a feature that required an entire validation system be put in place. Though I succeeded in successfully completing the system, the feature was not fully complete. The validation system was not visible. Though if leverage, it would lighten everyones load, it largely went unnoticed and what was observed was that I pushed out a buggy feature. Though I resolved the bugs within a sprint, my reputation was damaged to the point where I took on a new feature and promised it would be done in a sprint. I succeeded but wasn't able to complete it due to the api team only finishing 2-3 of 8 apis. This sort of test I made for myself also had low visibility so even though it was an impressive feat by my team's efforts, it also largely went unnoticed.
Though the author is wrong to equate work-throughput with IQ, he's right to find a way to inform trusted management with this work ethic and he's right to make sure when high value tasks are taken on, that it be made clear to product so credit can be given.
I have team members that are doing the bare minimum but cross lots of t's and dot many i's and that gets them equal recognition as me who often misses deadlines but does lots of heavy lifting.
With machine learning, the concept or layman level explanation to support the application of the tech is definitely doable for the average person. But the average person won’t be able to get the math.
Folks I know with ADHD generally adapt well, with systems or coaching that they get from professionals or folks supporting them. Everyone is different, of course, and folks struggle with different things.
He’s right with the other stuff too imo. People who deliver get grace from non-core failures.
So while you could teach anyone, with enough effort, they would not actually enjoy the experience.
There's a difference between grokking an ELI5 explanation and being able to build, modify, or review an existing ML model
Maybe - but very possibly not.
I would say this gets possible at 120 and only easy at 140 at a guess.
Edit: i am serious
If by "ML concepts" you mean "how to implement ML" - do you really think that people who got to a job that required learning this, represent the population IQ distribution?
Most college students I took it with, probably average a standard deviation higher, did pretty middling in the class.