4 ms·
This is of course a kind of a toy counterexample. But still, it does seem to illustrate the fundamental problem with a lot of ML-based solutions: "Just becaus
by vanusa 6y ago
This is of course a kind of a toy counterexample. But still, it does seem to illustrate the fundamental problem with a lot of ML-based solutions:
"Just because you can, doesn't mean you should"
I mean yeah - it is kind of neat (and interesting, in a fundamental way) that we can just "throw" a learning algorithm at an ever more, and ever broadening class of problems. But from a basic engineering perspective - it doesn't mean you want to. For a whole bunch of obvious reasons.
Then again, if your company leadership has gurgled the kool-aid, and decided that "our customers want an AI solution, because it's like, new and shiny" ...
- npdeep 6y agoThat's what I feel too. I am a big fan of machine learning but I just wish it wasn't the first thing people jump to.
- danielscrubs 6y agoI’m more and more convinced we are living in a prestige economy. 10 lines of code and you’ve added to your prestige. No college education necessary, you don’t have to compete on kaggle, you don’t have to make anything useful in comparison to the competition. Just prestige in starting a car, saying you can make a car and walking away.
- bryal 6y agoReminds me of a post on here in 2018, "It Takes Two Neurons to Ride a Bicycle (2004)" [1], where many of the commenters rightfully pointed out that instead of turning this into a machine learning problem, you could just implement a PID controller [2] to solve the problem. With control theory you can model a dynamic process like this more directly, and the theories have been around for a long time already. ML shouldn't be applied where it's not necessary. [1] https://news.ycombinator.com/item?id=16215130 https://news.ycombinator.com/item?id=16215130 [2] https://en.wikipedia.org/wiki/PID_controller https://en.wikipedia.org/wiki/PID_controller