YES! I study AI, and this is exactly how I feel!

Side note-One of my favorite things to do is ask people what their use case for using AI is, and watch them sputter out “uh…emails and productivity and things.”

The original paper itself, for those who are interested.

Overall, this is really interesting research and a really good “first step.” I will be interested to see if this can be replicated on other models. One thing that really stood out, though, was that certain details are obfuscated because of Sonnet being proprietary. Hopefully follow-on work is done on one of the open source models to confirm the method.

One of the notable limitations is quantifying activation’s correlation to text meaning, which will make any sort of controls difficult. Sure, you can just massively increase or decrease a weight, and for some things that will be fine, but for real manual fine tuning, that will prove to be a difficulty.

I suspect this method is likely generalizable (maybe with some tweaks?), and I’d really be interested to see how this type of analysis could be done on other neural networks.

My thoughts exactly. Growth is a byproduct of quality. Similarly, if the Fediverse grows too much and quality starts to slip, we should also let it shrink until quality comes back. I think our aim should be quality, and anything else is just a side effect.

Building a signup wizard to use that information to select a instance would seem to be the best approach.

That’s actually not a bad idea. I’m not on board with mining contacts, but I think there’s a simple, transparent way to do this that can actually be fun: a personality quiz. Sure, if someone knows what instance to join already, they can override this. But if they don’t, they get like five questions, and then they are matched to an instance.

I think what they’re saying is that Americans don’t pay attention and forgot how terrible the Trump presidency was because it’s been a few years. Most people think that “we’re better now” and any major issues have abated without understanding that nothing has fundamentally changed. Because of all that, Trump will win the election. The DnD portion of the post is just what got OP to think about this.

Sad thing is that there’s merit to the argument. It’s the old trope of “Americans have short memories.”

This is a much better article. OP’s article just shows the author’s surface understanding of how coding works and how well an LLM can actually code. There’s way more that goes into a programming task than just coding.

I see LLMs as having the potential of being almost like a super library. I can prompt GPT, Claude, etc. to write me a custom function that I copy, paste, test, scrutinize, and almost certainly change. It’s a tool that will make someone a more productive programmer. It won’t completely subsume a human’s ability to be creative and put the pieces together.

At the absolute worst over the next decade, I could see programming changing from writing and debugging code to prompting, stitching together, and debugging.

Yeah, you’re right on a lot of chatbots just being paraphrased responses from the support database, but for a lot of people, that’s all they want or need. There are a great number of people who just don’t want to read the entire article to find their answer. For that, I don’t really mind chatbots because I get the use case. What I hate is when there isn’t an option to go to the next tier of support without going in circles forever with the stupid bot.