skysight-inc/HackerNews huggingface dataset:
For reference, currently it is about 52 million. It was about 20 million in 1950.

I think we need to stop refering to decreasing population as 'gloomy' and negative considering that we have experienced a population explosion over the last century that is unsustainable and a big cause of our current global issues.

At 36 million, South Korea's population will still be up 80% over roughly a century.
"Pure" doesn't apply to "language purity" (nobody besides a very few seem to really care about the latter, especially not in C, not even compiler authors), but that nothing else is required than a C89 compatible toolchain to use the library (i.e. it doesn't need any assembler or third-party tools/libraries). See also https://www.merriam-webster.com/dictionary/pure?utm_campaign.... And so far the library compiles with all of my C89 copilers, even the very old ones (and old Posix versions). For a few cases to check, there are notes in the source code.
They take too long to build and require that thing called engineering which requires blood sweat and tears.

On the other hand, you can scrape the internet, build a model, semi-rig a couple of demos, hype the product and earn money.

Don't forget, it's all about money. Product is just a means to get money.

Building good things and earning good money as a byproduct is a thing of the old. Boomer stuff. Modern people don't do that anymore. It's not efficient, capitalist and quick enough.
Cool, thanks for sharing. Would love to see you dive deeper separately into each section!
I think a lot of his defence here is "No-one could have known exactly what was going to happen and no-one knows what will happen next."

This is obviously true - predicting the future is hard. It doesn't however explain giving a timeline of thousands of years, which is a ridiculously long time for anything you believe to be technically feasible.
This case or one like it will end up before the SCOTUS sooner rather than later and they will almost certainly rule the same way as in Students for Fair Admissions v. Harvard (2023).

Companies are acting in clear violation of the 1964 Civil Rights Act:

42 USC §2000e–2 (a)
It shall be an unlawful employment practice for an employer—
(1) to fail or refuse to hire or to discharge any individual, or otherwise to discriminate against any individual with respect to his compensation, terms, conditions, or privileges of employment, because of such individual’s race, color, religion, sex, or national origin; or
(2) to limit, segregate, or classify his employees or applicants for employment in any way which would deprive or tend to deprive any individual of employment opportunities or otherwise adversely affect his status as an employee, because of such individual’s race, color, religion, sex, or national origin.
Have you noticed people misapplying that to galaxies? They'll claim there is no influence on a star due to the part of the disk at greater radius, and also that the mass inside that radius can be treated as a point mass. But disks are not spheres, and rings are not shells, so those simplification do not apply. I've seen this mistake many times.
MACGRUBBBER!
I think he's just wrong about being wrong now. I'll believe it when AI invents a joke. I've still seen 0 creativity, it's just an aggregator.
I studied/trained/worked psychotherapy in tandem with audio work. I far more enjoyed the audio work, so it prevailed. I have friends in the therapy business and also hear conflicting methods. Whilst I have a truly sincere soft spot for the 'talking cure', broadly, psychotherapy is at its most effective when applied in combination with other and varied help - alone it is not so effective. And you may imagine the consternation that view causes - but I am right.
> Self driving cars?

This one in particular, I find fascinating, because we've literally just _had_ a hype cycle over it (I remember people telling me they'd be here any day now a decade ago), and now we're onto another AI hype cycle, almost immediately. Which comes first, AGI, or the self-driving car? :)

(I think your other examples are qualitatively different; moon bases, supersonic (passenger) jets and asteroid mining are clearly possible, but impractical for economic reasons; no-one is willing to _pay_ for them. Plenty of people are willing to pay for both self-driving cars and AGI, but there is just no clear route to achieving either.)
Your take is that you’re wrong a lot, so it’s OK others to be wrong? If the stakes are high, we should be learning how to not make mistakes rather than how to make excuses after the fact.
For one, the child can play any number of other games or choose not to play at all; the child can break the board, flip it upside down, fold it in half, introduce the concept of wraparound or flip the way pieces move… the child is free to choose to change the definition and rules of the game… the AI can only, ever, play chess, using only the rules it was given.

The metaphor assumes that life is a game in which there are a finite number of moves and someone is playing to win… chess isn’t remotely a workable metaphor for life.
This article is absolutely pointless. The statement was from 2009. Back then, neither side had any real evidence in favour of their argument. Deep learning and AI were still purely academic experiments, with zero practicality. And it had been like this for half a century. Back then, even the best models couldn't tell cats from dogs. Today every high schooler with a laptop can solve that problem thanks to abundant hardware and libraries. So both sides were just making up random numbers. This should be a lesson about people, despite their expertise, talking out of their ass instead of reminiscing famous quotes like "horses are better than cars." That statement is also funnily wrong in today's world, but at the time (i.e. without gas stations and roads and infrastructure everywhere), it too was rather reasonable.
> In cluttered UIs it helps when they show you where to navigate.

They're also good in minimalist UIs, which can be just as difficult to navigate if not more so. The difficulty stemming from the such UIs typically only showing you what's related to the current task, making it difficult to know if you're in the path that progresses toward your goal (if your goal extends beyond task in view).
Is it impacting hiring decisions? Changes in government policy? etc. If not already, how about in the next 5 years? A majority of the use-cases are not going to be publicly attributed to AI, that however does not mean it isn't having an effect.
The scientists who build their own tools
Restored 1923 Cycle-Skating in Paris Mesmerizes
>If you naively apply Newton's force of gravity, between two masses at a distance, Fg = Gm1m2/d^2, you get an infinite force when a marble (mass 1) is at the center (distance = 0) of a planet (mass 2)

and, for the people who might not have been exposed to the idea in a physics class, that marble at a distance from the planet has a potential energy, energy it would give up were it to be released and allowed to fall toward the planet. But, if instead you did work against the gravity to pull the marble farther away from the planet, that work would be saved up as an increase in the marble's potential energy. And that would continue till you pulled the marble infinitely far away, at which point the force of attraction would be 0 and the marble's potential energy would be zero. The only way this works is if the potential energy of the marble is a negative number, in which case maybe the singularity isn't such a bad idea
You can AI and ML to advanced level using github and LinkedIn just go from roadmap
Came here to tell about zram - swap in compressed RAM. Disable (or never set up in first place) on-disk swap and use compressed RAM as swap. This gives you swap, so you have advantages of that. But when you actually run out of memory, kernel oom has a chance to do it's thing, because system is still responsive in this situation.
This looks really slick! Nice work.
Meanwhile an infinite diameter conductor has a maximum efficiency of 100% with every part at whatever temperature you want.

Carnot characterizes classical heat engines and things that work a lot like them, it's not a universal limit of process efficiency and it's not even a good first approximation for many systems.

Your example of a meaningless distinction is a factor of over two in waste energy, in the favor of Carnot in this case, but distinct none-the-less.
OP here. Yup, I am in the process of starting a holding company LLC for my software products and small investments. Just went ahead and deleted 2 from the Investments page that are not launched yet but still in-development (just had landing pages up for those). Wasn't planning on releasing the Jaggi site yet, as I'm still wrapping my head around the holding company structure / it's new to me.

Agora has been a side project of mine. TBH in retrospect, I wish I would have given this post more thought as the servers / search performance wasn't prepared for any significant traffic. So definitely didn't game HN.
Fun times. I used the underlying pic (and then nroff) rather than grap but I remember a time-consuming rabbit hole of trying to programmatically generate the pic source, e.g. for diagrams that had regularly repeating elements (like some sort of networks). This was 1985 or so.

I was never worried by the keyword spam.
Vast majority of users (especially on Windows) don't understand the difference between console, terminal, shell, and command line. So this thread treats CLI as TUI.
>You don't solve most of your complaints by disrupting farming. You solve them by disrupting distribution.

I would want to go much further, disrupting consumption.
Or it might be one way in which it's exactly the same.
> Under Linux it is called open as well.

You mean xdg-open? I'm not aware of a commonly available "open" tool under Linux.
How did you find the list of shopify stores and names?
It's already been common-behaviour altering in many ways. I'm not sure if it counts as civilisation altering, but the way we create art, get creative review, find and consume large documents have suddenly changed. Not for the majority yet, but it's only a matter of time. For the first time we can get a knowledgeable ad-hoc assistant anywhere, immediately. Even if it's been bad in many ways, it's improving almost every day.
hey! this is cool, I take it you are based in the US?

How long have you been working on this?
Why the assumption that this was some rogue developer? What would they have to gain? I am 110% convinced this was deliberate strategy from the company and not just a random malice from an employee.
Might have to write a series of blog posts after this one :D
> Is it impacting hiring decisions?

I mean, probably, sure, for some (generally poorly run) companies, but, when it comes to it, all 15 of the last two recessions have impacted hiring decisions. Companies, and particularly poorly-run companies, jump at shadows all the time.
that's a fantastic document! thank you
The problem isn't the cost to customers, it's about externalities. Those cheap clothes are subsidized by slave labor and pollution. If you turn a blind eye to that you're complicit.
Thanks for sharing this! If you're up for it, I'd love to talk more about your experience, especially the technical tooling. Working as fast as I can to understand the right way to approach the tech, as there are tradeoffs with performance and price. I'm at support @ searchagora .com
Surprise.

Too often we want things to work just as they always had, to not go backwards in any way, and so we wind up fast-tracking these compounds about which we know very little to fix the problem.

As much as I'm a huge fan of science and technology, all we seem to be able to do with it is paint ourselves into a very tight corner faster.
wow, i really like this. first ui system i really liked. and it's cross platform. what's the dev experience like?
> Where are the moon bases? Supersonic jets? Asteroid mines?

In the latent spaces of Stable Diffusion and friends.
Yeah; it is absurd hyperbole.

The only person I've seen talk sensible on these topics is Stuart Russell of "Human Compatible" (read the book, it's written with great clarity). He has his head firmly on his shoulders and eschews the breathless hype.
Screenshots are a must-have for any kind of documentation, especially product how-tos.

But outdated screenshots can quickly backfire and do more harm than good. We've all been there when we land on a help center and the screenshots don't make sense!

The good thing is, when you use tools like Floik (https://floik.com/) to create documents, you can update them whenever your product updates and add new screenshots. So, your documentation doesn't go stale and you don't have to go through the hassle of creating the same content again and again (and again).
I think the above is actually well crafted sarcasm. But it does highlight why as an engineer/developer it is important to get requirements in writing and have a process that shows why you made the changes you ultimately made.
Again, see the link… get it to repeat the same word and it will give you back its raw training data. We’re still discovering the (potentially limitless) ways these things can be tricked into regurgitating what they were trained on; it’s entirely possible there’s no way to stop them doing so.
A space-based camera spys a secretive Project Kuiper satellite
Dubai Survey Drones Explore Minerals in Central Asia
Goodbye Goodreads. Goodbye Blinkist. Hello Contentlist
If you love learning from books, blogs, podcasts, this will interest you.

Over the last 6 years building two startups I have spent hundreds of hours learning from content to improve as a founder.

It's been difficult to know what the best resources are for improving a particular skill; like sales, product, management etc.

Google returns SEO optimized junk.
GPT returns middle of the road advice.
News feeds push random content.

You will never find the exotic blog post written by a 3x founder who successfully solved the problem you're facing right now.
But it's out there. And you can get better ideas and make better decisions if you find it.

So

Contentlist is a database with the best "startup content" across books, blogs, video and podcasts that founders can use to level up.
There's currently +350 resources and growing. All resources are recommended by another founder.
All books have a high level summary of the key ideas you can use to screen a book or as notes for a book you already love.

Use it e.g. if you are a technical founder who need to sell for the first time, there's curated list of 29 recommended books, blogs, videos and podcasts to learn from.
Same for most high level skill across product, management, hiring, fundraising etc.

Check out www.contentlist.io

Please share your feedback! Would love to talk to you if you think the learning / improvement space is interesting or if you have thoughts on how to improve it!

All the best,

Emil
Is the risk of asbestos exposure when you work in construction as low as someone that doesn't?
You might as well assume (c) whenever you use a library provided free of charge. Be prepared to either fix the bugs yourself or make sure there are alternatives you can use as a replacement. Even if the author is responsive now, there's no guarantee you'll get help once your code is in production a few months later. The library might even be archived at that point.

Lets say you've used FFTS, the Fastest Fourier Transform in the South [0]. Performance is spectacular, but now it's no longer supported and you find a bug. The code is impressive: Thousands of lines of code that dynamically generate SIMD instructions. But it's impossible to understand. You have chosen a library you cannot repair yourself. This is fine when there's alternatives, and there are for FFTs, and they are easy to swap out. If you can't easily swap out one library with another, you better make sure that you can repair it yourself.

And I hope people don't harass or "harass" library authors into merging pull requests...

[0] https://github.com/anthonix/ffts
"Some of the videos used artificially generated avatars or voice-overs, making the campaign the first influence operation known to the institute to pair A.I. voices with video essays."
We have self-driving cars already, but they're not evenly distributed ... and they have an unsatisfying amount of human input behind the scenes.
Why AI Gets to Create Art While Humans Get the Minimum Wage Jobs
https://archive.is/ImpfZ
Most of the current effects are due to AI hype, not due to AI itself. Regulations are trying to get ahead of AI, the reason it tries that is due to AI hype. Same with unions fighting against AI etc.

Maybe that hype turns true, but if all AI development plateaued today and no new improvements were made to it then that AI's impact on the world would be very minimal. A useful tool for professionals, but not much more than that.
OK, so if I'm looking at this right, a smarter, wider cache goes a great length to fixing the issue.

In [1] I implemented a simple PLRU bit cache, and I'm seeing an 8x performance improvement in some of the tests I was doing worse in:

Before:

bench-ncruces - simple insert query dbsize
bench-ncruces - simple 21224 16495 58687488
bench-ncruces - complex/200/100/20 insert query dbsize
bench-ncruces - complex/200/100/20 14993 15228 25354240
bench-ncruces - many/N=10 query dbsize
bench-ncruces - many/N=10 483 36864
bench-ncruces - many/N=100 query dbsize
bench-ncruces - many/N=100 3129 36864
bench-ncruces - many/N=1000 query dbsize
bench-ncruces - many/N=1000 28034 94208
bench-ncruces - large/N=50000 query dbsize
bench-ncruces - large/N=50000 428 501981184
bench-ncruces - large/N=100000 query dbsize
bench-ncruces - large/N=100000 779 1003761664
bench-ncruces - large/N=200000 query dbsize
bench-ncruces - large/N=200000 1475 2007330816
bench-ncruces - concurrent/N=2 query dbsize
bench-ncruces - concurrent/N=2 13091 56573952
bench-ncruces - concurrent/N=4 query dbsize
bench-ncruces - concurrent/N=4 14731 56573952
bench-ncruces - concurrent/N=8 query dbsize
bench-ncruces - concurrent/N=8 24730 56573952

After:

bench-ncruces - simple insert query dbsize
bench-ncruces - simple 5128 3026 58687488
bench-ncruces - complex/200/100/20 insert query dbsize
bench-ncruces - complex/200/100/20 3127 3730 25354240
bench-ncruces - many/N=10 query dbsize
bench-ncruces - many/N=10 93 36864
bench-ncruces - many/N=100 query dbsize
bench-ncruces - many/N=100 403 36864
bench-ncruces - many/N=1000 query dbsize
bench-ncruces - many/N=1000 3470 94208
bench-ncruces - large/N=50000 query dbsize
bench-ncruces - large/N=50000 444 501981184
bench-ncruces - large/N=100000 query dbsize
bench-ncruces - large/N=100000 717 1003761664
bench-ncruces - large/N=200000 query dbsize
bench-ncruces - large/N=200000 1401 2007330816
bench-ncruces - concurrent/N=2 query dbsize
bench-ncruces - concurrent/N=2 3275 56573952
bench-ncruces - concurrent/N=4 query dbsize
bench-ncruces - concurrent/N=4 3404 56573952
bench-ncruces - concurrent/N=8 query dbsize
bench-ncruces - concurrent/N=8 4918 56573952

There's still work to do. I could use ints rather than strings for function identifiers.
I'll evaluate that later.

[1]: https://github.com/ncruces/go-sqlite3/commit/964a42c76deb9c7...
I dunno, after experiencing the 20 fps boost from DLSS I'm starting to think indoor plumbing and the wheel might've been a bit overrated.
Now all that's left to do is to integrate a minimal native system glue library into Deno (create a window with a WebGPU canvas, receive input events, audio buffer streaming) and it would be a nice little platform to build and distribute small games and graphics demos written in WebAssembly and/or Typescript :)
Do you have more information about this sort of programming? I'd like to read about it.
Depending on how you define it, the Empire still exists (Britain still has colonies, even if they don't call them that). The return of Hong Kong to China is generally considered the "end of empire", though.

The sun will not set on it as long as it holds Pitcairn: https://what-if.xkcd.com/48/
The problem for me is the “key results” part of OKR’s. It means that if it’s not measurable, it’s not an OKR, and in too many organizations, if it’s not an OKR it’s not worth doing.

Cleaning up your code base to accommodate all the gradual accumulation of small fixes/hacks is not something you can put a metric on, at least not without pulling numbers out of your ass. But everyone agrees that you can’t really have quality software without doing this. But OKR’s would say that making nothing but tactical changes to ship features and never revisiting architecture is perfectly great. The incentives always seem to push you towards tech debt.

OKR proponents would say that revisiting architecture and paying down tech debt should be implicit and part of the process of achieving your results, but I’ve never seen it done. Or rather the only time I have seen it done is when someone tries to shoehorn the refactoring work into an OKR in order to justify it, making up bogus metrics, getting the OKR dropped because it’s not meaningful enough, and then just working on it anyway.
These both look nice.
I'm enjoying the irony that a product that relies on scraping the Internet will be undone by the flood of Internet content it generates.

I think that's a much more likely outcome than AGI.

Even if AGI is possible it's going to be constrained by the training resources thrown at it. Since most of those have been thoroughly enshittified now, the outcome for intelligent AGI isn't looking good.

Even if AGI hacks into everyone's camera and messages it's still going to turn into a spam+selfie moster superbot, and not Operation Paperclip 2.0.
Yeah, sounds like a secret 20% project :)
www.contentlist.io
Found a list on a site called "Built With". Mentioned this in another comment but I think it's meant for building sales outreach email lists.

Once you have the store URL, you can get general store information at [Base URL]/meta.json

Here's an example: https://wildfox.com/meta.json
This is exactly the boat I'm in. I have a 1hr train commute to work that I spend skilling up in AI. I've been following the space for about 15 years and have done a bunch of self learning of earlier ML techniques (the early Stanford ML MooCs) so I'm not coming in cold. What I'm doing is:

- Following along with Karpathy's videos, which has been mentioned: https://karpathy.ai/zero-to-hero.html

- About to follow along with CS 231n, also mentioned: https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rB...

- Trying ideas and theories in a Jupyter notebook

- Reading papers

I would agree with other commenters that recommend learning how to implement a paper. As someone who barely managed to get their undergraduate degree, papers are intimidating. I don't know half the terms and the equations, while short, look complex. Often it will take me several reads to understand the gist, and I've yet to successfully implement a paper by myself without checking other sources. But I also know that this is where the tech is ultimately coming from and that any hope of staying current outside of academia is dependent on how well I can follow papers.

I've been doing this for about a month now, and I feel I definitely understand more of the theory of how most of this stuff works and can train a simple attention based model on a small-ish amount of data. I don't feel I could charge someone money for my skills yet, but I do feel that I will feel ready with about 6 months - 1 year of doing this.
No misconceptions here ;)

Still the question is open, what does swap do for me in 2023? I only see disadvantages.
only the year, not the actual date, "on this day", etc