[scotchmi_st]

This is an interesting article if you read it like a howto for constructing a neural network for performing a practical task. But if you take it at face-value, and follow a similar method the next time you need to parse some input, then, well, I don't know what to say really.

The author takes a hard problem (parsing arbitrary input for loosely-defined patterns), and correctly argues that this is likely to produce hard-to-read 'spaghetti' code.

They then suggest replacing that with code that is so hard to read that there is still active research into how it works, (i.e a neural net).

Don't over-index something that's inscrutable versus something that you can understand but is 'ugly'. Sometimes, _maybe_, a ML model is what you want for a task. But a lot of the time, something that you can read and see why it's doing what it's doing, even if that takes some effort, is better than something that's impossible.

[thoughtlede]

I think the mention of 'spaghetti code' is a red herring from the author. If the output from an algorithm cannot be defined precisely as a function of the input, but you have some examples to show, that's where machine learning (ML) is useful.

In the end, ML provides one more option to choose from. Whether it works or not for you depends on evaluations and how deterministic and explainability you need from the chosen algorithm/option.

The thing that struck me is if RNN is the right choice given that it would need to be trained and we need a lot of examples than what we might have. That said, maybe based on known 'rules', we can produce synthetic data for both +ve and -ve cases.

[mr_toad]

The spaghetti code approach is basically an expert system. An old school algorithmic AI. Outside constrained domains these systems never really performed very well. Reality is just too messy.

Having a system where you can see why it works the way it does is all very well, but not if it keeps giving the wrong answers. In real world use getting the right answer is often more important than knowing how you got that answer.

[zelphirkalt]

You can make an expert system extensible though. You can make it definitely recognize some pattern and when there is a complaint about it not recognizing another pattern, you can add it. Hopefully you wrote the code in a way that easily allows adding new patterns, of course.

[meindnoch]

"Let's tuck all that unsightly spaghetti code behind this neat 1000x1000 matrix of floats!"