GolDDranks

I find it odd that more people don't realize that we are talking about risk of elevated *general intellectual-domain capabilities* as a resource. To be clear, I'm not claiming that LLM + RF is necessarily THE technology that poses the risk, the risk is in recursive self-improvement and whatever technologies will result.

It's very clear to that any specifics couldn't capture the risks, because the capabilities, including the risks, are one level higher than any specific techonolgy. It is the process of advancing technology itself, in accelerating speed, that poses the risk.

I've heard that the so-called "yellowish" skin color that non-tanned East Asians tend to have, is due to relative abundance of subcutaneous fat. If that's true, is that captured by the haemoglobin dimension or is it a yet another degree of freedom?

I love the idea, and I developed something similar of myself in the past (https://github.com/golddranks/kobuta), but... this reeks of slop. With Rust code, edition="2021" is a dead giveaway.

It's very hard when you are overworked to a near-burnout state. I needed to quit to save myself.

I'm am not willing to wager my mental health for staying if I feel the current work environment would be detrimental for that.

Why aren't the role tags preprocessed algorithmically/deterministically and then fed in as one-hot-encoded vectors alongside the semantic word embeddings? I'd imagine that it would be easier to train to _stay_ in the role an not confuse it, if the current role marker is explicitly set as a part of each input token, and not just implied by some past token. Plus a input separate from the word embedding would be unforgeable.

Thank you!

I am currently quitting a company of 10 years of employment. And I keep hearing how everything's shit. Btw. I'm located in Tokyo where it isn't as bad, apparently, but...

Let's see. My plan:

- Have my own company and start looking for customers. (Rust consulting)

- Keep looking for job opportunities, but don't succumb for shit jobs.

It might be that I'm too hopeful, but you can't know unless you try.

Anyway, I may join the "everything is shit" crowd in half a year if nothing pans out, but until then, I'm hopeful.

Indeed, I realized I had my timeline a bit off after posting that. Of course, we have Lisp ca. 1960. (Pascal appeared 1970, but I don't think that's widely considered memory-safe. ML 1973, and that never got a widespread industry use.)

What I mean is: we had memory safe system-implementation languages in wide spread production use only after/around the times of the publication of that memo; importantly, Java.

We had memory-safe experimental programming languages, and scripting languages before that. And of course, around those times, hardware was fast enough that you could start implementing systems with scripting languages (Perl, Python, Ruby, JavaScript)

And the bit I want to correct is, of course, the point is if they are actually used. In that sense, I'd correct the introduction of Rust around 2023-2026 in actual, wide-spread use.

I disagree. I think that after 1992, we got memory safe languages that brought a meaningful improvement to the status quo. And after 2015, we've got low-level memory safe languages (Rust, as the major example. There are others, more experimental.)

The average programmer doesn't get better – if anything, we might be getting worse, because the tools allow us to, and the capitalist reality doesn't optimize for great programs or programmers but for more money.

But, at least, the tools are way better than in 1992, and I think we, as a collective profession, have learned a thing or two.

I think it was way too easy to guess corretly based on exluding obviously incorrect choises and then going with vibes.

There were many words I couldn't have explain the meaning of at all, if I wouldn't have had the options, but having the options made it easy. I wouldn't count those correct answers as a part of my vocabulary (even passive), even if I could answer with relative confidence.

Little known, but a warm recommendation, both for the puzzles and atmosphere: The Swapper. (disclaimer: I did some coding work for this game)

This is interesting, as Ralf's articles always are. I wonder if/how will this concept be formalized. Rust is slowly but surely moving in good direction with regards to formal model of the language.

I applaud your goal!

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?

Fortunately only a few. Djikstra's is obviously the most reasonable system.

I can't get that demo to work. Tried with both Firefox and Chrome.

I'm not so sure if that's too wrong.

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.

I don't love these kinds of throwaway comments without any substance, but...

"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.

Yeah, you're right, and the snark might be warranted. I should consider it the same as my stupid (but cute) robot vacuum cleaner that goes at random directions but gets the job done.

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.

Just a supplementary fact: I'm in the beneficial position, against the AI, that in a case where it's hard to provide that automatic feedback loop, I can run and test the code at my discretion, whereas the AI model can't.

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.

I feel like I'm taking crazy pills. The article starts with:

> 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.

It helps if you think that there are only three kinds of hands:

- 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.

Agreed! I've been playing both offline and in the web client Jantama / Mahjong Soul. Not too far from getting into the gold room.

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.

Where in the story does NLP (I guess you mean "Neurolinguistic programming" and not "Natural Language Processing") factor in?

It is implied in the beginning: he expects to die before the singularity because of a tendency of heart problems in their family.

Ah, totally agreed. At least there is a clear auditory / motor part in the tasks that seems quite separate.

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.

Thanks for the correction!

It's a Rust library (comprised of a bunch of crates) that wraps a high-performance, high-accuracy syntax highlighter (called Tree-sitter) with vetted support for almost 100 programming/markup languages.

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.

> language production and perception are quite separated in our heads

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?

I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.