The article says stupid, not dumb. If I'm not mistaken, the difference is like being intelligent versus being smart. When you stop using the brain muscle that's responsible for researching, digging thru trash and bunch of obscure websites for info, using critical thinking to filter and refine your results, etc., that muscle will become atrophied.

You have essentially gone from being a researcher to being a reader.

$100 billion and the electricity consumption of France seems a tad pricey to save a few minutes looking in a book...

Same, I use it to put me down research paths. I don't take anything it tells me at face value, but often it will introduce me to ideas in a particular field which I can then independently research by looking up on kagi.

Instead of saying "write me some code which will generate a series of caverns in a videogame", I ask "what are 5 common procedural level generation algorithms, and give me a brief synopsis of them", then I can take each one of those and look them up

But when it works, it can save a lot of time.

I wanted to use a new codebase, but the documentation was weak and the examples focused on the fringe features instead of the style of simple use case I wanted. It's a fairly popular project, but one most would set up once and forget about.

So I used an LLM to generate the code and it worked perfectly. I still needed to tweak it a little to fine tune some settings, but those were documented well so it wasn't an issue. The tool saved me a couple hours of searching and fiddling.

Other times it's next to useless, and it takes experience to know which tasks it'll do well at and which it won't. My coworker and I paired on a project, and while they fiddled with the LLM, I searched and I quickly realized we were going down a rabbit hole with no exit.

LLMs are a great tool, but they aren't a panacea. Sometimes I need an LLM, sometimes ViM macros, sed or a language server. Get familiar with a lot of tools and pick the right one for the task.

I get these kinds of things all the time at work. I'm a writer, and someone once sent me a document to brief me on an article I had to write. One of the topics in the briefing mentioned a concept I'd never heard of (and the article was about a subject I actually know). I Googled the term, checked official sources ... nothing, it just didn't make sense. So I asked the person who wrote the briefing what it meant, and the response was: "I don't know, I asked ChatGPT to write it for me LOL".

I agree. I was almost skipping it because of the title, but the article is nuanced and has some very good reflections on topics other that AI. Every technical progress is a tradeoff. The article mentions cars to get to the grocery store and how there are advantages in walking that we give up when always using a car. Are cars in general a stupid and useless technology? No, but we need to be aware of where the tradeoffs are. And eventually most of these tradeoffs are economic in nature.

By industrializing the production of carpets we might have lost some of our collective ability to produce those hand-made masterpieces of old, but we get to buy ok-looking carpets for cheap.

By reducing and industrializing the production of text content, our mastery of language is declining, but we get to read a lot of not-very-good content for free. This pre-dates AI btw, as can be seen by standardized tests in schools everywhere.

The new thing about GenAI, though is that it upends the promise that technology was going to do the grueling, boring work for us and free up time for us to do the creative things that give us joy. I feel the roles have reversed: even when I have to write an email or a piece of coding, AI does the creative piece and I'm the glorified proofreader and corrector.