skysight-inc/HackerNews huggingface dataset:
It seems that 矢志不渝 [1] is a more close analogue in that this exact four-letter form is always used. The Korean version is substantially different too, it's 初志一貫 (초지일관 Chojiilgwan).

[1] https://baike.baidu.com/item/%E7%9F%A2%E5%BF%97%E4%B8%8D%E6%...
It seemed to me that the whole example was too contrived. The garage could simply have the option to buy the oil and give it to the mechanic.

func GetOil(oilType OilType) Oil {
...
}

func ChangeOil(c Car, oil Oil) error {
...
}
Euphemism for what?

It’s an interesting decision that was made and does it remain fit for purpose?
I’m sure a stochastic parrot model could be trained to exhibit reasoning, but the issue is that there isn’t any automated loss function which can discern whether the output of a large language model exhibits reasoning or is illogical. When you train based on text similarity, it will have a hard time learning logic, especially given the amount of illogical writing that is out there.
I love this so much. Like, most of the concepts and ideas it refers to are not completely new ideas (don’t ask me were I heard about them), but it’s interesting to hear them not proposed as a solution to a specific problem, but just based on the fact that they are thematically close to the works of an existing scientist. A little creepy though, like research from beyond the grave (move rights pending).

Non the less interesting though. I am currently researching into physics-informed neural networks for quantum problems, which are guided with differential equations. Maybe if you’d extend an LLM with an execution engine/numerical model, it’d be able to actually produce differential equations to undermine its hallucinated theories.
From my short testing that is something ChatGPT (4) is not that good at. Or it’s just a generally a hard problem to produce novel differential equations
I have had a similar-ish idea floating in my head for a while, which is a library + executor + editor UI for per-app scripting capabilities.

Something that would let people write out basic automation workflows to respond to events, similar to what Zapier or Salesforce offers to its users.

There are, of course, halting problem-style issues. I _think_ you could paper over some of that at the description level. But really you want the right kind of hooks into the actual system. A scripting tool that is just "oh but you just hit the API" is way less nice than bespoke components for your own system.

And with event systems you have the usual event propogation issues of accidentally causing a massive fan-out of events from some action and causing your sysetm to fall over.

But this is really something that someone could write out as a component for other systems and make a lot of business SaaS's automation floors way better.

You really do want to offer _something_ to users, though. The users that can write Javascript... well, Zapier lets you write Javascript. Hell, Google Cloud Platform lets you write Javascript in little script blobs, complete with Google Docs-level concurrency. This is a bit weak compared to that.
It doesn’t take a certificate in applied shoulder massage from lancaster technical college to work out that it’s bad for society.

We’ve seen how much social media and manipulation has destroyed the fabric of society. Now imagine those same evil people can control all creative output for their own purpose.

Every single thing and person you interact with will be whatever they want. When you whatsapp people they might not even be real anymore, but they’ll certainly tell you why you should vote for president zuckerberg to be reelected.

They’ll promise that they’ll only use their control to stop nazism or whatever. But the nazis made the same promise about communists.
The bubble is strong here. Some job at “big tech” is not the same as “tech job”. I don’t recognize this and if I did I would be out of there in no time. I work for smaller companies so I have a different viewpoint. Some slack I can understand but consistently doing nothing for months or years? Wow. I hope the market will correct this sooner than later.
And our reason is controlled by emotions, ego, intellect, etc, etc: our sentience.

Llm’s are the language model. That is it.

Now we have gone down this path to a very useful tool what’s next is connecting it to something that can understand context and memory.

It’s not so hard to imagine being connected to a knowledge graph of all the things and this evolving into a very capable AI.

It’s like Google v1 compared to Google now.
Key words versus semantic seo
> But my argument is that humans are also, at some level, sufficiently advanced stochastic parrots.

But humans have a feedback loop called "consciousness" that sits above the stochastic parrot level, can reason about it, and can separate the wheat from the chaff.

AI still has to reach this level. ChatGPT cannot judge if its answers are right or wrong. It just claims things confidently, and as long as it is parroting correctly, it is right, and that's why humans get fooled into thinking that maybe they can trust it. (That's also why humans get fooled by human bullshitters who claim things confidently).

So if you don't use ChatGPT as what it is, a lookup-tool trained on the content of the internet, which can't even tell you where it got the information from, and the onus is on you to verify if the information is correct or not, and if instead try to use it as some kind of expert you can trust (which I have seen quite a few people do), then you are doing it wrong.
That is true for most "new" human produced.programming languages too. The pool of truly novel programming languages is extremely shallow. Even the number of languages bringing anything new to the table is very limited.

So, it doesn't really tell us much (either direction)
Sorry if I am missing something here, but I think we all know well functioning, productive humans, maybe even in our field, who wouldn't have been able to create this language or a similarly well thought out one.

I know a competent man should be able to "change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders [...]" and what not and specialization is for insects, but even on the Mysterious Island not everyone is Cyrus Smith (Harding).
Quite an excellent example of the difference between genuine human writing and generative-AI content.

I do genuinely enjoy it when writers go a bit unhinged like this. Perhaps now more than ever, having a feigned professional "tone" in writing is gonna make you sound like ChatGPT.
NFT art creator free App
https://play.google.com/store/apps/details?id=nftcreator.ava...
Other than Oracle or MSSql, what would anyone consider using that is not open source?
Personally I’ve never seen this and have worked for a few megacorps. Never worked in finance/banking though, perhaps this is common there. Perhaps I’ve just been lucky/unlucky? How common is this?

[edit]
He goes on to blame agile for all this inefficiency, but being old enough to have worked proper waterfall, I can assure you that task bloating is extreme under such a process. That was the one period of my life that matches some of the things mentioned here.

The root problem seems to be estimate bloat due to uncertainty. You can’t actually commit to a far off end date unless you know the amount of work (impossible) or include significant “buffer”. Agile should allow you to pack in more features if you are ahead, but apparently that’s not working out at the places he’s worked.
I've only been working for a few years now but I'm always shocked when I hear stories like this. I work at a startup and it's really been all-consuming. I don't know of a single coworker I'd classify as slacking either. Sometimes it feels like too much. It can be hard to bother someone because everybody knows everyone is so busy

I guess I need a raise
During my undergraduate study of physics at Otago University in New Zealand in the 1970's it became pretty apparent that typing would become central to computing, so I took the Pitman speed typing class and got certified.

As a certified Pitman typist from that era, I can say that there is nothing inconsistent to me about this document being typed on a typewriter.

It was also common practice to use Letraset to add any characteristics to the page not otherwise available on the typewriter [1]

[1] https://en.wikipedia.org/wiki/Letraset
haha I thought this was clever but man that writing is useless garbage. wonder if Google will learn to catch it.
Yeah, Nix “doesn’t only alter environment variables”, hell, the most common way of operation is simply patching/compiling standard linux ELF executables in such a way that they dynamically link to the correct dependency, so instead of just having libc mentioned, there is /nix/store/some-hash-libc/lib/libc there. This one libc is shared across many (most) of the packages you will practically have, so you get the advantages of containers, without any overhead in emulation, nor file size.
Nice research!

However 40 years ago was 1983 so unlikely to be same event.
Last night I read for the first time the company’s 8k announcing my resignation
This reads like an excessive generalization: the author has worked as a programmer in some of the most notoriously inefficient and bureaucratic industries, and thinks that his experiences there extend logically to every other market niche.

The reality is probably more boring: that programmers are roughly as (un)productive as everyone else. But we can see (and therefore evaluate) our own non-productivity, making it easier to overstate.
Fast thinking/slow thinking by Daniel Kannerman (and the Unlocking Project) is a book people need to read and understand.
When we slow think, we work things out, when we fast think we are parrots.
China could demand FB be sold, or else face national ba... oh wait.
Exciting product. You should describe some common problems people have, and show us how you could use Scriptable to solve them. That's a nice and "easy" way to showcase a service IMHO.
I've been in situations like this author describes, and I've been in 60-80 hour/week crunch times that lasted up to a year and a half. I miss the crunch times.

But one constant is that it takes a while to get plugged in at big companies. Rarely are you given a ton of meaningful work right away. The bigger the company, the longer the time. When the giant telecommunications co. (yes that one) bought our company, I was told it takes five years to get plugged in.

The architecture group I was on in that company spent most of our time pitching ideas that never saw the light of day. But our biggest internal client, the main company website, was more than happy to tell the top brass they were using our POCs. So the net result was we kept our funding, the boss of the company website looked like he was playing ball but actually got to do whatever he wanted, and we actually produced very little. Basically our boss and the boss of the main website had hacked the system. It took me a year to figure out how it all worked. It was crazy.
While making perfect sense, it just feels slightly weird due to the order and IMHO less beautiful to its equivalent. In Chinese it’s 不渝 “unshakable” instead of 贯彻(insist)
I think what you are describing is API for manual scheduling: you call sleep() to give up control to scheduler.

With tasks/futures you supposed to submit another task to pool which will wake up after certain time.

Both are "green threads" with manual scheduler (you need to make explicit call to give up control to scheduler) but different API.
> Why people use conda? I couldn't figure out what it brings to the table.

Have you tried compile mkl, numpy from scratch?
I’m dumber than you
That's my dream and it solves two problems.

First:

- We would be able to remove a lot of office jobs and basically most of us would probably do nothing or search something that requires human body like maintaince jobs. It would allow for a lot of people to have leverage that was not available before, one person would be able to create art, movies, games, books without having any skill by directly turning ideas into reality.

- In long term if we would create artificial life, there would be another types of beings in this universe that are capable of thinking and exploring. They won't constrained by our biological limits, they would be able to grow "brains" as large as they can, survive and adapt any unlivable environments and their "personality" would be able to live as long as it can by not being limited to ~100 years. So it would be able to explore beyond what any human can and may be have effect on our universe on a scale of galaxies and more.
> What is happening right now in tech may be one of the greatest market inefficiencies—or even deceptions—in history.

Propaganda.
I believe stories like this but in my experience, at the companies I’ve worked for this was not the case. Apple, Snap, Airbnb and a couple lesser known companies: work life balance existed but I’ve always been extremely busy. Maybe it depends on the team you land on but if you want to work you can find it. I’ve never had anyone tell me to pretend, not ask questions or anything of the sort.

Just thought I’d add my 2¢. I’m sure others have had different experiences than me but I can’t be the only one working all the time, usually more than 8 hours a day unless I stop myself.
I asked it to translate my resume recently, saw the word Python and or Linux stopped translating and stared opening a fake terminal and doing weird stuff, so YMMV.

My honest opinion is that very few people are clear on what the thing is actual good at, great at or bad at at this stage. We're still trying to find it's real use case.

IMO it's best for things you already know quite a bit about so at least you don't mess up hard. In other words, it seems like a more advanced ELIZA. Nearly everyone who has had a good time with it has used talk to it until they had a break through.
This author misses the target: product people, the arch bullshitters of our industry. Given freedom to set direction, measure their own performance, stand up new teams for features they thought of while on a night out and call it data driven. You have to salute the grift.
I was actually in that general area about a year ago in the late fall and saw something very similar, except at the end it kind of "popped", like it disintegrated or exploded.

Is there a meteor shower or something visible there that these might be correlated with?
I won't say I haven't worked for most of my career. I would say I've worked maybe about 1/3rd of my 10 years in tech.

But about 2/3 of that time I've been on projects that involved little or no work. It's prevalent at banks, hospitals, and certain types of consulting work where you get brought in to failing projects but the projects are always failing because of organizational dysfunction, not because they needed more engineers, so there's nothing you can really do.

This can vary in extent from

- Here's 3- 10 hours of work. I need it by the end of the month. You can literally tell the boss that. They'll just say don't worry, just get it done

- This project will be getting new requirements handed down to us in a month. 5 months later, the requirements never came. I rewrote the whole legacy Java app in rails and fixed all the issues because this was pre remote work so I was sitting in a cubicle and very bored. Never told anyone, just threw it away when I left. I would have surely been punished for making people look bad if I told them I had fixed their entire app because I was bored in this kind of environment.

- The funniest ones: When the bosses constantly need to show you they are tough by demanding that you "get stuff done" but when you ask for details they say "we'll go over it in the next meeting". They are bullshitting but somehow feel that they need to act out being a boss so they constantly act annoyed that you aren't getting stuff done even though when you press them, they have no work for you. This can go for years.

- Once had a pre remote job at a major bank where they just threw like 50 consultants in a room and rarely gave anyone any instructions. I just stopped showing up and would answer chat if anyone chatted me. After about 3 weeks they figured out I wasn't showing up. I told them I wouldn't come back in unless they gave me work. They got back to me two weeks later and just told me I needed to start coming back in again but couldn't promise they could give me work. Ended up just walking away.
Funny I asked it questions about general relativity as Einstein too :)
What a weird way to promote your consultancy.
I don't disagree we're still better in a number of ways, but if GPT-4 was given a database, and a "while" loop -- do you think it would gain consciousness?
Openness is probably the reason chatGPT was possible in the first place. Machine learning research has been able to progress so rapidly precisely because information has been all open and publicly available.

I think trying to turn research back into company silos is going to be a death sentence for innovation in the sector. What happened with stable diffusion was amazing for generative art. But I guess openAI has learnt from what they probably see as a wasted opportunity and a mistake.

Now, let's talk about datasets and information as well; these LLMs all rely on the wealth of public information we have created as societies, so it seems to me pretty scummy to simply exploit that wealth without really giving much in return. I don't think it's going to be possible to put the genie back in the bottle however, I think people in the tech sector are avid for publicly available LLMs after tasting what happened with stable diffusion. We'll see, in any case, I think this is a good business decision by "open"AI; though they might want to rebrand.

Also, let me just say this: safety is a much more encompassing issue that needs to be discussed in the social and political sphere. These decisions need to be made much more democratically. The amount of people that I've seen disappointed of the safeguards that chatGPT offers, and why? Who decided those were the right safeguards to put?

Anyway, boo for openAI but chatGPT is pretty cool.
Perhaps.

Generative AI needs a way to receive feedback. AI learned to play chess by playing a lot, and the feedback was either winning, losing, or drawing.

If generative AI can repeatedly test physics theories faster than humans, then we may witness progress in physics. AI could generate thousands of theories and conduct experiments successfully, possibly leading to new physics models.

However, I am uncertain whether this will be achievable soon, particularly for theories requiring costly experiments.

A benefit could be that humans crave recognition for success, making papers less valuable. AI may be more willing to take risks and document its failures than humans.
Thanks, rewatching Phenomena's "Enigma" proper was a good thing to do at 07:50 before heading off to work, and the emulator did a fine job :)
It totally depends on your product and preferred tech stack. But most of the big ones will likely have very common feature sets so there's not that much differentiate on.

One thing I'll mention is configurability. Most boilerplates ship with tons of stuff - some of which you won't need. This can lead to having a lot of unused code lying around which can be a maintenance burden long term (or you have to do a bunch of work to safely delete it). A handful will let you build without certain features enabled which makes the starting codebase more tailored to exactly what your project needs.
"Analysing language from millions of books" - I assume this means they just did a Google Ngram search?

https://books.google.com/ngrams/graph?content=rationality&ye...

It is funny they talk about the "post truth" society, while categorizing the word "truth" among the intuition-related words rather than the rationality related words.
> It’s just a mishmash of features from the most commonly blogged-about existing programming languages. It has no conceptual insights, no original ideas, no taste that isn’t cribbed from one of the few languages it’s copying from.

It will also learn all the bugs and reproduce them.

Programmers who think ChatGPT is going to replace their job must have a very low opinion of their own skill set.
> If you were going to design a new programming language that encompassed all of these ideas, what would it's syntax look like?

Why this obsession with syntax? Semantics are way more important! GPT rightly chooses to ignore the question and answers with a high level proposal of design.
What a fantastic rabbit hole to fall into..!
Finally!

I have a guide on how to buy weed in Berlin. A big chunk of it warns readers about how sketchy and dangerous it is if you don’t have a trusted contact. Weed is frequently contaminated with really nasty chemicals.

A Canadian or American reader might not appreciate how different the environment is from their pre-legalisation days. The weed you buy is genuinely dangerous.
Is risky, 3 hours top is a good estimation. You can appoint for an out of business hours change. But better choose another strategy start cloning disk at first failure notice and cancelling old server.
>But in this planning phase something really strange happens: It has become the standard practice to highly exaggerate the efforts required to perform a task, which we’ll call task bloating.

Had this at my current job shortly after starting. Was given an assignment to write a wrapper library for a 3rd party API that only had 4 endpoints (one of which was auth). None of them were complicated, the most complex was one that returned multipart data where I had to parse out a few things. Something that could be done in an hour, easy. I still decided that I would give myself extra time in case something else popped up before I could get around to it, so I told them two days. Everyone else on my team said that was way too short and insisted that I have an entire two week sprint to do it.
Agile coaches and scrum masters come to mind. Product "owners" as well.
Honestly, you might be onto something. The article seems a bit inconsistent with the author's bio

> I help companies build challenging software products from scratch. I often work with early-stage start-ups.

And the article is riddled with bizarre typos like

> When they inquired about this, I conceded that maybe it was herded that I thought after all.

I wonder if we're entering a new age of AI-driven market manipulation
Oh please. This community is filled to the brim with people that are addicted to negativity and contrarianism. LLM criticisms very typically go far far beyond “this isn’t the singularity”, well toward “LLMs do nothing of value, snd certainly can’t I - the esteemed developer - with anything I find hard in my job!”
I recognized the names of two of the authors immediately, David F. Brailsford, and Brian W. Kernighan. Not only are they both contemporaries of Ritchie, but Kernighan was a close colleague too.
Bay Area to phase out new installs and replacements of gas heaters and furnaces
Google discontinues Google Glass for enterprise
As a Chinese person, I perceive "初志" as having a connotation of "original" or "initial" intentions, whereas "矢志" simply implies determined wishes or promises without emphasizing the "initial" aspect. While I'm not an expert in Japanese, my understanding is based on the Chinese perspective, and the actual meaning in Japanese might differ. It's intriguing to see how these nuances can vary across languages and cultures.
Really? As far as I know, Rust’s borrow checker was a newly developed approach to memory safety. There have been other non-GC/RC approaches to memory safety in e.g. Cyclone or Ada but Rust’s system is novel.

Likewise, Julia’s use of just in time compilation of dynamic dispatched code to achieve zero overhead execution was rather groundbreaking.
内弁慶 (Common Saying in Japanese makes it sound deeper)