On the name "Respectify": it immediately reminded me of Linus Torvald's famous quote "respect should be earned". That quote, in its literal form, strikes a chord with me. While I share his sentiment towards respect, I think that lacking respect towards any individual shouldn't entitle you to be an asshole – but that's something that Linus has historically been from time to time. In that context, the quote sounds like a sorry excuse.

In my opinion, the toxicity of communication shouldn't be framed in terms of respect, but in terms of "basic human decency". To me, using the word "respect" sounds like the right to non-toxic communications should be earned. I'd rather have that as the baseline, which is a value that I expect you to share.

Maybe call it Decentify? Or Detox?

Science works by scientist having a model of reality and then testing that model against reality, gathering evidence that fits or doesn't fit the model, evaluating how well the model corresponds to reality.

If there is a widely accepted model in the archaeological community, and the new data contradicts it, the wording "than archaeologists thought" seems plausible enough.

Of course, depending on the model, the model itself might admit regimes of "non-applicability", or have some measure of confidence... If archeologists have large uncertainty whether human ancestors made tools 500,000 years back or not, then they shouldn't be surprised upon finding evidence that the ancestors did.

I don't know any specifics about this case, just arguing that that kind of wording by itself is not always wrong by default.

"It Is Difficult to Get a Man to Understand Something When His Salary Depends Upon His Not Understanding It"

...might be my issue indeed. Trying to balance it by not being too stubborn though. I'm not doing AI just to be able to dump on them, you know.

The thing that differentiates LLM's from my stupid but cute vacuum cleaner, is that the (at least OpenAI's) AI model is cocksure and wrong, which is infinitely more infuriating than being a bit clueless and wrong.

Yet. Most of my criticism is not after running the code, but after _reading_ the code. It wrote code. I read it. And I am not happy with it. No even need to run it, it's shit at glance.

> you give it a simple task. You’re impressed. So you give it a large task. You’re even more impressed.

That has _never_ been the story for me. I've tried, and I've got some good pointers and hints where to go and what to try, a result of LLM's extensive if shallow reading, but in the sense of concrete problem solving or code/script writing, I'm _always_ disappointed. I've never gotten satisfactory code/script result from them without a tremendous amount of pushback, "do this part again with ...", do that, don't do that.

Maybe I'm just a crank with too many preferences. But I hardly believe so. The minimum requirement should be for the code to work. It often doesn't. Feedback helps, right. But if you've got a problem where a simple, contained feedback loop isn't that easy to build, the only source of feedback is yourself. And that's when you are exposed to the stupidity of current AI models.

- 25 fu hand (chiitoitsu) 16 / 32 / 64

- 30 fu hands: 10 / 20 / 39 / 58

- 40 fu hands (especially toitoi, but also some others with koutsu's) 13 / 26 / 52

As long as you don't have any kans (and you mostly shouldn't call those), the others are a rounding error.

One of my New Year's resolutions for this year is that I try and go playing in a mahjong parlor for the first time in my life. Still trying to get a bit better before going there.

However, I find it also unlikely that the networks are totally separate, and I wonder if there are any evidence of areas that encode the "core/abstract" linguistic de/serialization (multidimensional and messy internal semantic information ←→ linear morphophonological information) both ways, or at least mechanism that manages to use gained input network competence to "train" or "manage" output network competence.

Why? Because even though, as you say, there is a differing performance in perception and production, there is also plenty of evidence of gaining linguistic competence from input, and then managing to convert that to performance in output.

You can use it as a normal Rust library, or you can use the JavaScript/WASM wrapper to highlight source code on a web page.

Do you have any evidence for this?

I am a former linguistics student (got my masters), and, after years of absenteeism in academia, interested in the current state of the affairs. So: "quite separated in our heads" Evidence for? against?

By this point, I realized that the OP uses a normal mouse. The MacBook trackpad is so good that I feel weird using a mouse these days. Also, the travel between the keyboard and trackpad is much smaller.