Here's one that I think sums it up pretty well:

"Engagement farming refers to a range of deceptive practices on social media designed to artificially inflate engagement metrics such as likes, shares, comments, and followers."

"Engagement farming employs various tactics to exploit social media algorithms, with the intent to appear more popular than actual user interest would warrant. Examples include posting controversial content to provoke emotional responses, repurposing successful posts without originality, and using automated systems for mass liking or following." [1]

If you don't think this is happening on HN (especially to mass downvote posts) you're naive.

[1] https://www.isme.in/engagement-farming-prof-sriram-prabhakar...

Why do you think all engagement farming would result in downvotes? You think HN posters are so keen at sniffing out bad actors that they would never reward them by accident?

It feels like you're being willfully dense about this. I can see why the other person accused you of being AI.

All sorts of reasons! One is that when you reach 1000 karma, you gain the ability to downvote comments.

You seem like a smart person. I'm sure you can think of some reasons why that might be useful.

I'm picturing something like folding@home, but where people donate their spare tokens to a service, and those tokens get distributed amongst all open source projects on GitHub. You don't think that would be cool? Like, someone might initialise a repo with only a readme and a to do list before they go to sleep, and then wake up to a complete software ecosystem that looks as if it's been in development since before they were born. Like, so much code that no one person could possibly understand it, and it all happened overnight while they were sleeping!

Think about it. Anthropic just reported that their codebase is now improving itself. We're moments away from every open source repo being able to do the same. Think of it like torrenting — you'll be able to open your repo to the public, and have a stream of code flow in from millions of contributors. More code than you could ever write in ten lifetimes, uploaded to your repository in a matter of days.

Ladybird doesn't know it yet, but they just left themselves in the dust.

edit: it looks like I was wrong and they're still hiring many software engineers. Not completely sure why that is just yet.

This excessively pro-AI article brought to you by private equity.

I mean, Github Copilot's pricing just went up considerably, so I guess they were right?

Also, to answer your question, I think a good baseline for "cheap" is probably whether you can charge the end user enough to make a profit and not have them complain about the price of your service, as they're currently doing. If you can't do that, you're probably not even in the ballpark of "cheap", so it's not worth getting any more specific.

NFTs? My company had nothing to do with blockchain but I ended up working on NFT integration regardless.

Having said that, expecting writers to devote equal time to the pros and cons of an argument can set up a false equivalence. It tells the reader that the benefits and drawbacks must be somewhat equal, even when they're not.

> If the only thing you can come up with is drawbacks, you're being willfully ignorant.

Does this also go the other way? If you can't come up with any drawbacks, you're being "wilfully ignorant"? You may want to amend your post!

I thought AI was supposed to be democratizing creativity and putting the power of Hollywood into the hands of regular people? What regular person can afford that kind of price tag? Isn't inference supposed to be cheap?