skysight-inc/HackerNews huggingface dataset:
heh. yeah. Plain text always wins. (btw, in all meanings of "plain". like no-frills, and no-fluff too)

You know, everything textual-or-structural on this whole almost-abandoned site (non-english, sorry), like:

https://gramofonche.chitanka.info/prikazki/pipi--cd709-kanev...

https://gramofonche.chitanka.info/pesnicki/

is made out of these yamls, one per item-folder:

https://gramofonche.chitanka.info/prikazki/pipi--cd709-kanev...

(with help of about ~15000 lines of python+libs, but that's ephemeral)

have not touched it for 12 years..
Yes, you may be. But you still have an internal world model - through conditioning or otherwise that you're playing off against.

An LLM doesn't have that. It's very impressive parlour trick (and of course a lot more), but it's use is hence limited (albeit massive) to that.

Chaining and context assists resolving that to some extent, but it's a limited extent.

That's the argument anyway, that doesn't mean it's not incredibly impressive, but comparing it to human self-awareness, however small, isn't a fair comparison.

It's next token prediction, which is why it does classification so well.
At which university was that?
Denmark had the mosts c64 groups in the world (the reason for this, I don't know) compared to population size. Most of the people involved with these demo/cracking groups in the 80ies were most likely in their teens. Once the 90ies arrived with the internet, I think it was obvious to most of them what they wanted to do with their life.

Sweden, Norway and Finland came in 2nd, 3rd and 4th. I think US was at place 20.
If this is a reference to the Bene Gesserit test of humanity, then the gom jabbar is not the device that causes the pain. The gom jabbar is the needle with a poison tip held to the neck of the test taker. It’s just a poison weapon. Alia kills the baron with a gom jabbar.
I agree that engineers will likely be fine (if at all decent). But there are many more jobs done on computers that are fairly routine which are the ones that will be threatened.

> An AI currently isn't even capable of doing excel business analysis without the data being checked. This check has to be done by an analyst as well. It cannot even do book keeping without errors and the work to check for errors surpasses doing it yourself.

Here I think you are thinking about this wrong. AI is going to be built directly into Excel so I think it will harm a lot of especially entry level type work for analysts. If any part of your job is using microsoft/Mac software I think you will see a radical shake up in work (that will still enable more people to be entrepreneurs etc so on balance a good thing).
Well a language fork. But not a full implementation fork of course. Or would you argue that what Lombok does is part of the java spec? It effectively extends the java spec in non backwards compatible ways.
non twitter link https://knowyourmeme.com/memes/torment-nexus
Asocial drivel.
Possibly, but when I think of "old internet" I think of people posting under pseudonymous handles for basically this reason.

> our society permits employers to have a chilling effect on the online speech of their employees

More generally than that. Dylan Mulvaney made one beer advert while being trans and got death threats. She would be counted as a "contractor" rather than an employee.
I'm concerned about who AGI will serve? Rich people surely!
But then we will face the original problem: prevalence of fake location spam
> If your ML model takes hours when it can take minutes, or takes days when it can take hours, you will move away. You could move away to another language or a faster interpreter but that's a different discussion.

How much of this is done in Python, vs constructing instructions in Python to run on a GPU at uber speed?
Weren't Simula, Ada, Pascal and Oberon similar to each other syntax-wise? Begin-end etc.
> Let's see Tesla's growth rate when they're closer to Toyota's size.

Not sure what point your trying to make, though. Smaller, faster-growing companies usually do trade at a premium over their larger, slower-growing counterparts. That's just... kinda how the stock market works?

You can certainly object to the magnitude of the difference between the two companies' PE ratios, but otherwise nothing seems weird here.
That is a very cool concept I hadn't considered. No idea of feasibility but would love to see it or something similar happen.
not sure about "worst day" lol. The BDFL also wrote

https://forum.dlang.org/post/wzoecavcswedkiebcjft@forum.dlan...

https://forum.dlang.org/post/lhhxvlxfddxnreyfhbct@forum.dlan...
> i'm more worried about the ones who will use it this way and assume it's always correct

There are plenty of folks who don't fall into this trap.

Example: Me. I am fully aware that LLM generated code can be wrong or worse, contain disastrous errors. But being aware of that, and looking for the things I know from experience it commonly gets wrong, allows me to use it as an incredibly powerful tool in my workflow.
I don't think it's people in tech specifically - I think that "fire your workers because they're going to be replaced by AI" is a great excuse for firing workers without looking bad. Thus, anyone who might use that excuse has a strong incentive to play up the potential of AI (and thus the plausibility of their excuse), regardless of the actual value of AI.

Also, we're all calling it "AI" for some dumbass reason. That infects our thoughts with unwarranted credit toward the technology.
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If the author wanted to write "How to do absolutely anything with a dictionary" they should have titled the article that.

Was the first 20 paragraphs on what a dictionary is really useful? No, it's unnecessary verbiage that anyone clicking on an article with the title knows.
According to a report by the Energy Reliability Council of Texas (ERCOT), the state’s electric grid manager, crypto mining “consumed” more than 3,300 Gigawatt/hours of Texas grid energy in 2022, more than double the amount used 2021.

Riot Platforms’ mine in Rockdale, Texas, uses about the same amount of electricity as the nearest 300,000 homes, making it the most power-intensive Bitcoin mining operation in America.[1]

[1] https://www.nytimes.com/2023/04/09/business/bitcoin-mining-e...
Even in “long standing tech companies with the best and most experienced employees” this sort of issue has been known to fall through the cracks. Twitter has experienced significant staffing changes, procedure changes, and code changes, recently and any one of those three things can exacerbate the chances of side-effects of changes not being realised until too late.
> avoid any federal regulation (because a connection across state lines would obviously count as "interstate commerce"), which seems to have real value given the current clusterfuck of a political environment.

Could you explain the practical advantages of this and which federal regulations the state is better off without? What particular details of federal energy regulation are bad?

(Besides, given Wickard vs Fillmore I'm not convinced that disconnection would be enough to avoid incurring commerce clause regulation given a sufficiently motivated supreme court)
"Sunswift 7" doesn't look completely different. In height and volume, they could be very similar.
woohoo, another frontier to ravage
CWE 2023 Top Most Dangerous Software Weaknesses
So humans have a level of knowledge, understanding, and reasoning ability that LLMs simply don't have. I'm writing a response to you right now, and I "know" a certain amount of information about the world. That knowledge has limits, and I can expand it, I can forget it, all sorts of things...

"Hallucination" is a term that works well for actual intelligence - when you "know" something that isn't true, and has no path of reasoning, you might have hallucinated the base "knowledge".

But that doesn't really work for LLMs, because there's no knowledge at all. All they're doing is picking the next most likely token based on the probabilities. If you interrogate something that the training data covers thoroughly, you'll get something that is "correct", and that's to be expected because there's a lot of probabilities pointing to the "next token" being the right one... but as you get to the edge of the training data, the "next token" is less likely to be correct.

As a thought experiment, imagine that you're given a book with every possible or likely sequence of coloured circles, triangles, and squares. None of them have meaning to you, they're just colours and shapes that are in random seeming sequences, but there's a frequency to them. "Red circle, blue square, gren triangle" is a much more common sequence than "red circle, blue square, black triangle", so if someone hands you a piece of paper with "red circle, blue square", you can reasonably guess that what they want back is a green triangle.

Expand the model a bit more, and you notice that "rc bs gt" is pretty common, but if there's a yellow square a few symbols before with anything in between, then the triangle is usually black. Thus the response to the sequence "red circle, blue square" is usually "green triangle", but "black circle, yellow square, grey circle, red circle, blue square" is modified by the yellow square, and the response is "black triangle"... but you still don't know what any of these things _mean_.

When you get to a sequence that isn't covered directly by the training data, you just follow the process with the information that you _do_ have. You get "red triangle, blue square" and while you've not encountered that sequence before, "green" _usually_ comes after "red, blue", and "circle" is _usually_ grouped with "triangle, square", so a reasonable response is "green circle"... but we don't know, we're just guessing based on what we've seen.

That's the thing... the process is exactly the same whether the sequence has been seen before or not. You're not _hallucinating_ the green circle, you're just picking based on probabilities. LLMs are doing effectively this, but at massive scale with an unthinkably large dataset as training data. Because there's so much data of _humans talking to other humans_, ChatGPT has a lot of probabilities that make human-sounding responses...

It's not an easy concept to get across, but there's a fundamental difference between "knowing a thing and being able to discuss it" and "picking the next token based on the probabilities gleaned from inspecting terabytes of text, without understanding what any single token means"
Because their revenue don't depend on search quality, they get paid for the top spots regardless of what's on the bottom and they are at a near monopoly.
> and is written in a way that novices can learn the topic

If you're a novice you start with "what is a dictionary" which is where the first half of the article belongs.
Do you remember how Kirkerud (the lecturer and textbook author) opened the semester stating with absolute certainty that AGI would never, ever be reached in our lifetime, or even the next several centuries?
Ads and shit doesn't exist because there isn't a clear way to extract value. They exist because the folks that make decisions love ads and shit. You will end up paying a subscription for a bad product with few alternatives, just like most folks end up using Google now and pay with all their data. There simply isn't a good search engine, Google murdered all the real competition and what was left is mediocre.
> ...progenitor of the most popular, and reviled program paradigm, Object Oriented Programming. Designed by Ole-Johan Dahl, and Kristen Nygaard in 1962...

In 1962 the first version of Simula appeared which was quite different from Simula 67, not yet object-oriented, and dedicated to simulation.

Simula 67 was the first general purpose object-oriented programming language.

> Then, in 1991 another language would enter the playing field, Java, and the rest is history.

Java actually used the object model of Simula 67; James Gosling gave a talk about it at the 50th anniversary in Oslo. Here is the link: https://www.youtube.com/watch?v=ccRtIdlTqlU
I think the assumption Sun's Java could become something that eclipsed most languages including Erlang is over, as the prototype distributed JVMs just became another navel-gazing exercise.

The Erlang/Elixir OTP has design constraints like any other solution, but has survived 4+ business cycles. One can only hope Julia ends up with something similar, but more user friendly.

Distributed systems is hard, and training obstinate people is like trying to teach a Raccoon TCL. If a design really needs Erlang/Elixir, than there are few alternatives that won't degenerate into a polyglot dumpster-fire.

Happy computing =)
No, it's got useless crippled acceleration that's only suitable for games. You can't use them for video.
For me, Perl’s tight syntax let you get a lot of stuff done but lacked the consistency of simpler, more verbose languages better suited to multiplayer teams.
Both of which are useless for video.
I noticed people have very low expectations about modern application performance. My mom finds it completely reasonable that her TV or car audio need 5-10 seconds to boot. I guess that because almost everything is a web-page now (including web-pages wrapped in a window like electron apps), people simply got used to seeing a lag every time they click.

And I remember how my jaw has almost dropped when in 2022 I saw an operator of a POS that used a 80x25 TUI coming from a dinosaur era coded probably with Borland TurboVision... Man, how fast that was! Some windows literally appeared on the screen for a fraction of a second (the operator obviously memorized the sequence of actions). The fact that I found it unusual, when in fact it should be a norm, also speaks something about the performance of today software.
Not to be difficult but wouldn't "confabulating" be a preferable description for this behaviour? Hallucinating doesn't quite feel right but I can't exactly articulate why confabulate is superior in this context
Great. Now try editing video.
It was a 750cc two-stroke running at WOT.
> ... someone who doesn't know a lot about economics

Not exactly what you were asking for, but if you are also interested in learning about economics in general, I can highly recommend "Economics" by Ha-Joon Chang as an introduction.
I wrote simple implementations (simple if/else/while and printing to stdout) with no optimizations in Rust, Python3 and C

Rust -> 23.2MiB/s

Python3 -> 28.6MiB/s

C -> 238MiB/s

Does anyone know why Rust's performance is in the same ballpark as Python3.

I thought it would be more closer to C.
Not really when even then they add more cruft, desiring to explain the entire implementation internals of Python before finally giving you the answer.
The Wikipedia has "In the news" section
Discovey as a reason to spend money is another web ad fantasy. The old days discovery was by word of mouth. The trust deficit goes down when one doe t rely on discovery.

How important is it to discover a blog post no one is talking about?
If you asked me, Python not only shouldn't rely on (third-party) C library code, but it shouldn't even be used for cases where pure Python is not optimal.
I really wanted to read this, but I think we may have hugged your site to death.
One possible factor is the cost of backwards compatibility.
> AI is vastly more dangerous and more urgent than climate change, than Russia

No it isn't, and I say that as a user and Integrator of ML tech.

Climate Change: Literally our planetary habitat becoming uninhabitable for our species.

Russia: A country with one of the largest nuclear arsenals literally threatening a large portion of the world with nuclear annihilation.

Excuse me when the prospect of changes in the economic landscape for white collar jobs doesn't look particularly frightening compared to such problems. Especially since we live in a day and age where 2 entire generations have lived most of their lives in almost constant economic upheavals anyway.

As for all the AI-doomerism that's flying around the net: As long as no one can even give me a precise, quantifieable definition of "general intelligence", aka. one that doesn't include pointing at ourselves, and a method to measure how far AI is from that, I will work under the assumptions confirmed by what is measureable and observable: that what we have are still stochastic inference engines.
Yes, every banking and financial app I have tried runs just fine on GrapheneOS.
TF, May be AI, but always felt weird to see 'race' field in those American forms
On October 17th, 1979, VisiCalc was released.

I'm sure pretty much every accountant in the world got up and went to work that day exactly like they'd been doing all of their career. It probably didn't feel different for that many of them. Most of them had probably never used a computer then, and a lot of them probably didn't feel any particular need to, at least until they tried it. There were probably more than a few who were near the end of the career managed to keep doing their job the old way for another half or whole decade or so, because even when the future moves fast it's never evenly distributed.

There were probably also more than a few who saw VisiCalc and bought an Apple II to start doing their own books and ended up regretting it. I don't know where we are and how things will pan out, but I think there's a parallel.
They are all working on ads and adblocker arms race.
NASA’s Ingenuity Mars Helicopter Phones Home (After 63 Days)
The irony of Python.
These filters are light enough that they work well in Manifest V3 adblockers. The "Google - Global" filter only adds 1376 dynamic rules for example.
If you grabbed a 'Java Basics' book, you would not expect the author to explain the entire implementation details of ArrayList before telling them about for-each.

But somehow the author of this article thinks that this kind of unnecessary level of detail is appropriate.
Yes, but in the history of humanity, economic growth of above 0.1% a year is also relatively recent. One of the things that C18 radicals insisted upon was a decent system of IP.
Good question! Commenting to read follow up answers.
> Something like working in a kitchen is a long way off (or at least will require a redesign of kitchens from the ground up or humanoid robotics that are effective, reliable, and reasonably cheap)

Factories that make food are already a thing.

I didn't know there was an entire TV series dedicated to just this topic until 5 minutes ago, but I have seen at least one short segment about the topic, specifically Viennetta ice cream: https://en.wikipedia.org/wiki/Food_Factory
Driverless trains doesn't mean no drivers. It means remote drivers.

The DLR for example still has drivers, its just they are located somewhere other than the train.
Can we see your code?
I don't think it's likely, but climate change could easily wipe out humanity by exacerbating pre-existing geopolitical tensions. For instance, Pakistan and India famously share a river, and the treaty that governs its water rights was written with the assumption that the river wouldn't reduce in output. A sufficiently severe drought could cause a war between India and Pakistan, and both countries have nukes.

You could dispute that WW3 would cause human extinction, and while I'm not remotely certain of it I think that WW3 could cause extinction, if there's a sufficient combination of 1) climate collapse and 2) worldwide economic collapse that makes high-tech systems impossible to sustain.
> Tesla for right or wrong has been viewed as one of the best bets here.

Really? From what I've read and seen, Tesla's self-driving is starting to feel like the butt of most jokes in the space. And Musk's absurd insistence that cameras are the only sensors anyone needs isn't doing their technology any favors.

> Elon factor.

I think Musk might be running out of steam. The Twitter fiasco shows how unstable and unfocused he is; the whole thing could collapse like a house of cards at any time. I had extreme respect for him 7 years or so ago, but that has eroded over time, and now I see him as a delusional, abusive asshole who happened to have the charisma (a nice way of putting "talent for emotional manipulation") to help build some successful businesses. (And it still remains to be seen if Tesla and SpaceX will continue to be successful in the long term.)
Right. I think the kitchen scenario is more constrained than self-driving (for one, you don't have to continuously keep moving to be safe), and the people who I think are at the forefront of self-driving are also doing robots, and "perform tasks in an unfamiliar kitchen" is a ML classic. My main assumption for "don't injure humans" is that even small animals routinely manage to avoid doing actions that would be potentially harmful, so it doesn't seem to require full general intelligence.

And of course, if we crack an AI that can work on AI better than humans can, that solves - or at any rate obviates - all other AI problems by proxy.
Almost certainly the limitation is due to printing, likely buffering or locking.
I wrote this a long time ago, you might find it useful.

https://ismailmaj.github.io/tinkering-with-fizz-buzz-and-con...
Problems for computer solution (1980)
It does. I've been using steam on Wayland for like 2 years now.