The difference is that now it is worthless: there is no learning, no person caring about the result, nothing aspirational for the public to look towards... we used to enjoy those challenges, used to be proud of solving complex problems... now? Yeah, whatever, execute execute commit push, let another LLM "review" and call it a day.
I wouldn’t be sad about defeating lower complexity challenges. There are always higher complexity challenges that arise once we start operating in a world when you can do more. The bar raises.
Yesterday I went to a bookstore: saw an interesting book cover then I thought "ah, looks like AI"... all excitement went away. There won't be a "new complexity frontier" for artists that used to draw book covers. Or writers, actors, writers, etc.
AI is currently not enabling any use case which previously was "too hard". It is just reducing the value of stuff by increasing the offer and making people delulu about what they can achieve without proper knowledge.
Making good stuff requires paying attention to a lot of details. Even "simple" stuff can become incredible complex once you actually learn about how it must be done. Most of what we humans do is working on that space, not chasing projects Manhattans.
What do we get if population is disconnected of the true complexity of creating stuff? Perceived value decreases and if everything is perceived equally bad people will stop caring about quality. That is why fascism likes uneducated people.
So, that is about the AI contribution to "value" itself.
Now, is it true that AI will allow us to create more complex stuff that is not practical now? I would strongly disagree. The reason is Kolmogorov complexity: it is not possible to find the shortest program that describes a task. Describing it with natural language will not magically give us permission to avoid having to describe that complexity. What is the point of switching from C to English, if I still have to specify every little detail in a much ambiguous and verbose language? Programming languages are not the challenge, they are the solution to the problem of having to specify complex tasks in a reproducible way.
Now gathering everything together: that is why I think that generative AI makes things worthless: value reduction, complexity perception reduction (which reduces value), a population ignorant of the complexity will choose subpar options because "they are all the same garbage" and we will not get any superior engineering capability anyway.
Once insurmountable challenges are now trivial to implement with, as you say, "low effort."
For those who were attracted to computing by the grind and the grand narrative that you, too, with sufficient effort, discipline, and merit, could become a revered craftsman, LLMs trivialize an entire lifetime of practice. I can't think of anything more demoralizing.
The equivalent is something like hand tool woodworking - it’s still a thing despite the advent of machines, but more of a niche. You can still aim to become excellent, but maybe you won’t be famous.
Writing whole software projects in assembly has been worthless and pointless for a couple of decades now. Even the projects who can put together a solid case will limit assembly to very specific components executed only in specific bits of a hot path. Perhaps the most performance-sensitive code we have today is high frequency trading and that field is dominated by C++.
Also, virtually all mainstream compiler suites have flags that output assembly,and that feature is largely ignored and unused.
What's next, human human contact abstracted away by brain stimulation?
And the transhumanist arsewipes gonna have a field day.
Never too late to ignite the nukes...
Of course! Corona/junta/scarecrowvirus don't transmit over the wire, while ads, taxes and surveillance do alright!
