sarahlwalks

Well, maybe I’m not cool enough to appreciate it, and maybe I’m more accustomed to the style of other languages, but if I see more than a few ifs in a file, it feels like a code smell, and it feels like some refactoring might be good. But I’m hearing that this profusion of error checking “if“ statements is the go way.

To me, the ideal in a language is to assume that everything will go right, to enunciate the core intention of the program, function, etc., and to handle errors somewhere else, maybe below the main code or something like that. Mixing it all in right there with the code, even if we end up concluding that this turns out to be the best way to deal with things, seems visually confusing to me when reading the code.

There actually is a text editor in there somewhere at least if you believe some of the MIT neckbeards. But you have to sort of tease it out with the proper meta key what-have-yous

We might get tired of so much free speech. Hang on a second....<touches ear> I'm being told I'm actually sick of it right now

I like that phrase! I'm probably going to steal it :-)

Machines -- at least today -- are extensions of human beings, and pretty democratic, really, compared to history. You can't really talk about limiting machines without also limiting humans. GPT is a tool. Almost anyone can use tools much like it. So what are we trying to protect against?

That seems like saying a steam shovel is bad because it moves dirt at scale. Machines do increase the reach of people, that is exactly what they are for.

You can only say that if you also say that the creativity of human beings themselves is just a way to launder copyright.

So, wait, in what sense is AI-generated content garbage? It is (admittedly by the author) fascinating and even beautiful. Is it the fact that it was generated by an algorithm, and the idea then is that all algorithmically-generated content is garbage? But the author doesn't even begin to deal with the idea that humans themselves operate according to algorithms: an algorithm is simply a strategy for doing something.

I won't even critique the rest of the article; there's no need. If AI-generated content is beneficial and helpful to humans, then I think one is hard-pressed to call it garbage, and the underlying thesis fails. And to my knowledge, no one — not even the article's author — denies that AI products can be beneficial.

AI is a tool, just like, say, Photoshop is a tool, or a compiler is a tool. No points are awarded for having human beings do by hand all the tedious work that tools can do better. In the end, creators, whether it be of paintings, or poetry, or essays, or software, will stand on the shoulders of these tools and thereby accomplish things that previous generations could only dream about.

One niche that ML seems to be growing into is /assisting/ humans, but not doing the whole task. ML might give you an image that is 90 percent what you want but needs a few tweaks.

If the task is clear enough, ML can take it on by itself, but this requires clear rules and an absolutely unambiguous definition of what winning means. For example, the best chess players in the world are machines, and are FAR better than the best human players. Same for Go (the game, not the programming language).

As far as I'm concerned, the question is how ML/AI stacks up against the competition -- humans. I don't know, but I'd bet the answer is that ML is much better. Let's say at least 20 percent better, but I imagine it's much higher than that.

Second, this is only saying that right now, ML's performance is "not that good." It says nothing about future technical advances. If you look at the track record of ML in the past three decades, it's amazing, and if that performance is repeated in the next three decades, who even knows what things might look like. (Machine sentience? Maybe.)

This is the rule and not the exception. It seems software always takes much longer and costs much more than you think it will. The smaller the task, the better it can be estimated, and the less likely you are to veer off into crazyland.

The best solution I know would be to hire a team and use agile methodology to focus on the most important things first, breaking them down into small tasks. The team might be people you hire, or it could be people from an agency, but the project needs a strong, hands-on leader who is committed to the goal. I have never known a toss-a-big-solution-over-the-wall approach to work really well. Those projects can vary from annoying to completely dysfunctional.