"because there are no immediate practical uses for this"
It depends on how hard a problem you're trying to solve. If you're writing the MVP of some CRUD app that supports a handful of users, you don't care about efficient algorithms. But if you ever hope to scale up to support massive numbers of users without using up massive amounts of extraneous servers (think of Google's or Facebook's data centers, and what their power and cooling costs), then knowing how to create efficient algorithms is of tremendous practical importance - it could mean the difference between profit and loss.
Another example on a small scale: If you want to write a game that drives a virtual reality display in real time with realistically rendered imagery, knowing how to write efficient algorithms is also going to be very important.
But if you ever hope to scale up to support massive numbers of users without using up massive amounts of extraneous servers
When the time comes that a self-taught engineer is scaling to these massive numbers, there should be money in the budget to hire people with expertise in efficient algorithms.
"there should be money in the budget to hire people with expertise in efficient algorithms"
1. Wouldn't you rather be the developer who built the scalable software that drives your company toward its IPO rather than the developer whose skills suddenly became useless just as the company was getting really profitable? Why should they even keep the first developer around after they hire someone else to clean up their mess?
2. Does your company really want to have to re-write all its critical code just as that code is starting to make money for them? It's OK for an MVP to be lacking features; features can always be added later. But if its fundamental architecture isn't efficient and scalable, you're going to run into a brick wall at the most inconvenient time.
In the grandfather post it was suggested that it was a founder who was self taught. If I am the founder and I am self-taught, I have to build what I can into the early version and when I have enough money hire someone to build it better. That day might be a few months from now, or years, or it may never come at all.
It depends on how hard a problem you're trying to solve. If you're writing the MVP of some CRUD app that supports a handful of users, you don't care about efficient algorithms. But if you ever hope to scale up to support massive numbers of users without using up massive amounts of extraneous servers (think of Google's or Facebook's data centers, and what their power and cooling costs), then knowing how to create efficient algorithms is of tremendous practical importance - it could mean the difference between profit and loss.
Another example on a small scale: If you want to write a game that drives a virtual reality display in real time with realistically rendered imagery, knowing how to write efficient algorithms is also going to be very important.