skysight-inc/HackerNews huggingface dataset:
Is it wrong to want women to be happy? The causes enumerated by GP and touched upon in the video under discussion are real and destructive, therefore I would like you to be substantial in your criticism, not simply state a contrarian opinion.
Pretty sure if they’d used the term “Boolean satisfiability” even once, we would have been able to work it out.

But SAT could mean a million things and if you’re not using this stuff on a daily basis then it’s simply non obvious.

It’s not the authors fault, they can write what they want. what’s pissing me off is the utterly unhelpful attitude of people responding to questions about wtf the guy is talking about.
Those dependency chains in apt, brew, port/pkg.. that's one of the problem space SAT solvers address.

I hate apt/deb bundling. I prefer brew/port/pkg atomicity with explicitly defined version dependent declarations and metaports distinct.

That might be how most people interact with SAT.

Makefiles too maybe, I'm unsure if make does it's dependency checks in SAT
I've only seen it come up in discussions about job-hopping and what the optimal time to stay at one job is.
Because its performance is unparalleled. Also, it’s tons of fun to drive on twisty roads.

I don’t know of any other production car that offers comparable performance. Every other Tesla feels slow in comparison. I have driven the Lucid Air Grand Touring. Its performance isn’t remotely comparable, and the Lucid Sapphire is currently vaporware. As of mid-January, only three existed on the planet, and none of those were available to the public.
Still, a title of "why boolean satisfiability is hard" would eliminate the confusion without any downsides.
Might be worth having a look at Sony if you want to spend more money for whatever reason. Latest Xperia 1 and 5 both have 3.5mm jacks and SD card slots. There is some preinstalled software (camera apps, Google apps, probably FaceBook) but overall not too-too bad.
That might be true. But at least what you describe is not my experience. All women I know want serious relationships, not one-night stands (Belgium). Maybe in your part of the world or generation that is different.
But instagram/tiktok has real data + you messages, people you know and talk to and listens to you 24/7. If they will be able to predict 1B of humans and social dynamics then I guess it’s enough of training data to basically simulate reality.

EDIT: it gives insane “soft” power so pretty sure NSA etc. are working on this
Not everyone has to do everything the same way. Hell, after you take my inches away, are you going to make me start speaking the same language because mine current one is unpractical?
I don't underestimate the sheer amount of cognitive effort, money and time needed to maintain native versions of software. Or to build a desktop application at all!

From my perspective Thunderbird, IntelliJ, Firefox, Chrome are extremely complicated pieces of software. My initial exposure to Qt is that it is a very difficult framework to use properly to build nontrivial applications. Not only do you have the barebones complexity of C (build everything yourself) or the overwhelming complexity of C++ (there's many ways of doing the same thing) you also have a graphical GUI framework AND a platform API to work with. It's simply a lot of moving parts.

I've written a few Java SWING GUIs and an electron app but I wouldn't want to use a low level programming language to build a GUI.
US Customary Units != imperial units. The feet is the same between the two to be fair.
You can bring your own runtime
Zuckerberg Can’t Stop Copying the Competition. This Time It Could Be FB's End
IIRC, this has been the case for a while. I seem to recall getting a Raspberry Pi ~5 years ago which had Mathematica on it. Admittedly it was quite slow, but as far as I can recall it did work.
There is an interesting bit of nuance here.

Yes, SAT is hard.

But, the vast majority of SAT problems can be solved really fast.

The second one is one of the little known advancements in computer science which happened in this century. Fast SAT solvers power a lot of the interesting software out there.
Well by that token, grooming might as well refer to combing your hair. That's clearly daft, though.

In fact, its current usage probably first emerged in the 1970s in relation to child abuse [0]. Since then it's been hijacked by various right-leaning individuals and groups as a dog-whistle for whatever they happen to be most worried about today [1]. That makes it a heavily over-loaded word that's becoming a general fnord. The problem with fnords is that they discourage thinking. So I'm not in favour of using 'grooming' to refer to data/model poisoning.

[0] https://journals.sagepub.com/doi/abs/10.1177/088626051774204...

[1] https://www.edweek.org/leadership/why-misusing-groomer-as-a-...
https://coral.ai/

Or, search

nvidia ai starter kit
So now you need to know two languages to access the database. :-/
I share the same experience. It's not like we can no longer have those by the way, I've never been bothered by ads like Carbon Ads for instance. They're usually relevant (ads for code analysis tools or JetBrains IDEs on cppreference.com for instance), not animated and not obtrusive.
If he wanted chatgpt’s opinion he would have asked chatgpt
While it's technically not a bad price in terms of raw compute and memory, the noise from the high speed server fans alone is reason enough not to get this. Never mind the power usage.

I was going to say maybe it'd be worth it if they were 24GB GPUs, but I'm not sure you can even use recent Pytorch with cards that old. You'd have to work around the limitations.

You don't even need a GPU to learn anyway, you can use tiny models that train super fast even on CPU for that. You need the beefy GPUs once you want to generate tons of content or train a modern model on big datasets.

Get a 3060 12GB or a 2080Ti 11GB and call it day, at most.
Further rabbit-hole source material...

https://www.interactiongreen.com/kuma-kengo-louvers/
> The author seems to want to use symbols instead of words on keys, so I feel I have to inform them that “^” is not the proper symbol for the “Control” key; rather, the standardized (ISO 9995-7) symbol is “⎈” (2388, HELM SYMBOL).

I don't think it very much matters what the "proper" symbol is if no one uses it and almost no one knows about it. Symbols are supposed to be convey meaning and part of what lends that meaning to a symbol is actual usage. Apple has successfully done that with at least several of these symbols [1], which is quite evident in that you knew what it meant and so do many others, while I've never seen the "standard" being used in literally any context.

Obviously I alone do not make up the general consensus, and perhaps in certain fields the usage of these symbols is widespread, but if it were the general consensus, people would actually be using these symbols instead of the ones you're suggesting aren't "proper."

[1] https://support.apple.com/guide/mac-help/what-are-those-symb...
A common thing in split layouts is putting backspace on a thumb key or two.
Everyone is vulnerable when it comes to identity theft, but the OP’s position, should they notify anyone, is a lose-lose one regardless.

Morally they should “do the right thing”, but as many have explained in the comments, this will end up costing anything from reputation to money to freedom.

It really sucks that the only sane advice here is to sit on it and move on :(
Hangover 0.8.1 Released to Run Some x86 Windows Apps on ARM64 Linux
You're trying to pull yourself up by your own bootstraps here.

If sentience is required to produce the kinds of texts that LLMs produce then sentience is a feature of LLMs of course. But if sentience is required for my computer to produce the "Tada!" noise when it switches on then my computer is sentient also. (It's probably not sentient.) Nothing you have said establishes in any sense that LLMs are sentient, and the Chinese Room experiment shows that we can't just rely on our intuition.
10 years now. Found post that was first announced: https://writings.stephenwolfram.com/2013/11/putting-the-wolf...
I don’t know how that works. Your data schema is the foundation of almost any system, regardless of how you generate it.

I think this is a common mistake. People think their code is what’s important. But it’s the data and how it gets transformed that is the core of most applications.
It's not K-12; it starts at 4th grade, according to the site.
It got overloaded with juvies posting dick pics and went OOM. It takes ~1-5 seconds to generate, normally
Proton isn’t an anonymity silver bullet, and, as others have indicated, your opsec is generally worse than you believe it to be anyway.

Also, to have your first contact with the company be “I’ve found a problem and I want money” might get Legal rather than IT involved, and then you’re on the back foot.
That's not necessary. You can heat a much larger thermal mass to a lower temperature, so that the total heat stored in the mass is the same.

This mean that the design of the whole thing will change to modulate the heat flows appropriately.
It's not properly decentralised AFAICT [0].

Censoring a user would amount to censoring their publicly facing relay, which isn't horribly hard for a state actor.

Matrix with full P2P support through Pinecone seems much better [1].

[0]: https://nostr.com/the-protocol

[1]: https://archive.fosdem.org/2022/schedule/event/matrix_p2p_pi...
YMMV but I was surprised to find the opposite. Never been able to consistently touch-type properly before, learned it through switching to a corne with a miryoku-inspired layout and I now type better on the old laptop keyboard (which is not that often) than I did before.
Yeah, for people living a de-googled life - For example, people running LineageOS or GrapheneOS.
In Chaos by James Gleick it is mentioned that bunch of early mathematics related to fractals was worked out in the context of research into soot - the story went that soot is very black because the surface geometry has high fractal dimension, or something like that. In turn, this soot research was motivated by efforts to calculate just how black the sky would become in the event of a nuclear war. Now any time I see scientists trying to learn about soot, a small alarm bell goes off in my head. I'm sure it's nothing though :)

On another note, I think streak cameras are cool but they count as cheating in my book. Any time someone is publishing papers with streak cameras they should only be allowed to put "trillion fps" in the title if they also put "sustained for up to one nanosecond".
If you want to learn about which GPUs make sense to buy or rent for various ML workload, i highly recommend this Tim Dettmers article:

https://timdettmers.com/2023/01/30/which-gpu-for-deep-learni...
Sorry not a native English speaker, when I said gasoline I meant petroleum derived liquid fuel such as gasoline or diesel or aviation fuel or kerosene.
Not being x.509 is arguably a good thing. :)
>Pretty sure if they’d used the term “Boolean satisfiability”

It is obviously used in the text, just not in the title.

This random digression doesn't add anything to the topic. If the parent of this thread had posted "What is SAT ?" instead of the rubbish snark, someone would have replied, "Boolean Satisfiability". End of story. When did expressing one's ignorance become cool ? The OP (and others) could have grepped the article, or even just smashed a few keys in google, such as "sat np", and would have got the answer.
You have to put yourself back into your 18yo self, right? The kind of people who think a degree in management will make you a manager, and if they let you on to your course they must know what the requirements are and you must satisfy them.

At that time in your life your entire world has been school, and everything you did in school led to another thing in school. Why wouldn't you assume you'd get taught programming when you applied for a CS course, whose prereq was math that you did in school?
I think there’s a big difference between building something to learn about it, vs accidentally building something complex in order to support the thing you’re actually trying to build.

The point is, just use a database. We’re talking 15 minutes of effort.

Or to paraphrase someone wiser than me, 4 weeks of programming can save 15 minutes of installing.
It’s literally the only answer recommending to buy it, so I don’t see how that’s “decent”
Client-side comments with Mastodon on a static Jekyll website
Oh man just reminded me of a strange dream, the other day. A lady was enthusiastic about Haskell and was trying to encourage me to get into it. I was like "I like the language but the official docs are bad, I don't know how to learn it!"

But maybe I should get back into Haskell...!
I think you misremember the internet.

There were and are still very few places on the internet (outside of hosting your own platform) where you can post whatever you want without recourse.

No woodworking forum would allow a thread of "black man assaulting asians on the subway".

You wouldn't see "jews stealing money" in comp.lang.perl.

Removing a submission from your own website that goes against the spirit of the site is not censorship any more than cleaning swastika graffiti off your front door is censorship.
When thinking about applying "lean" approaches to delivery of software projects, one easy but flawed analogy is to think of a manufacturing plant churning out some kind of widget. Say, we're manufacturing zippers. In the case of the software project, instead of delivering increments that consist of batches of partly assembled zippers, and handing them off to the next stage for bending or finishing or whatever, we deliver project increments brimming with new features, defect fixes, etc.

In the case of the widget factory, you get many attempts at building exactly the same thing. In a typical software project, there's only ever one thing, and with each change in each increment, you're constantly changing the design and construction of that single, increasingly complicated thing.

From this perspective, both the case studies of the Empire state building and the Polaris missile system are much better approximations of how incremental design and delivery work in software projects than the mental model of a factory churning out indistinguishable widgets.

One can argue most floors in the empire state building are pretty similar, so experience gained while designing and building the 3rd floor can apply to the 53rd, and to some degree that's true. But if we mistake our floor building for zipper manufacturing and conclude this means we will be able to keep adding another 25 floors per quarter and extending the height of the building indefinitely, as we gain more and more experience at building floors, boy are we are in for a big surprise. The floors aren't independent, the project is to design and deliver a single system - the building - each increment during the project modifies that single thing. We'd better have some people involved who are thinking really hard about how the entire system is going to come together, what constraints the whole system is under, and testing our design and build assumptions.
This is pretty scary. I doubt there is a one size fits all solution, but it seems like a red flag that Find My iPhone can be disabled immediately after the Apple ID password is changed on that device. If there was a waiting period that wouldn’t be possible.

I don’t want it to be this easy to take control of my device. There should at least be an option to require the passcode and biometric authentication to do this.
How is SQL bad? If anything my experience with KV db's is that most of the time they'll eventually end up implementing some form of structured data storage and retrieval that in some way resembles SQL.
I love KV's only when I used them as embedded db's like pebble and badger db but you can never beat a good ol' SQL server that just does what you need from it nothing more nothing less.
ORM's most of the time aren't that great either you always have to keep up with their new fancy API changes and instead of just doing your work you find yourself relearning the same ORM every few years, not only that but some ORM's are extremely sensitive in how you order your operations that the order in which you write you code can potentially kill your performance or worse accidentally deleting data.
no one is taking your inches away, nor your language. many people, where i am from, use both sets of units interchangeably. it’s a total non-issue.
Had a poweredge in my apartment in college, can confirm they sound like a leaf blower.
Here's a couple

- Not everyone wants to learn Rust but want to use the same language throughout their stack

- Tauri is still new which means it is not considered "tried and true"

- More developers know how to use Electron or at least know enough Javascript to learn which means larger talent pool = cheaper and easier to replace developers if need be

- Last I checked (was not recently I admit), the build time for Tauri was abysmal

- I would argue very few gives a damn about smaller build sizes unless the problem space actually requires size to matter

In short, Electron is established tech and "good enough" while Tauri is the new kid in the block. It takes time for it to carve a space for itself. With all the Rust hype going on, I don't doubt it will happen.

Fun fact: I actually embarked on a project recently where my plan is to build the app in Electron first and once I had a change to learn Rust, I'll probably try to migrate the Electron app to something like Tauri.
For just 5x more cash, you can get two new 3090's... 20k cuda cores, and much more modern, so should be much faster than the core count suggests.

Worth considering just building two machines, as well; the ability to train multiple models in parallel is in many cases more valuable than the ability to train one big one.
We don't expect med students to have spent their teenage years doing experimental surgeries on their friends. Or accounting students to have taught themselves by doing accounting for a major business in their after-school time. Nor do we expect a microbiology student to have spent their childhood experimenting with infectious viruses and bacteria in their garage.

I think we expect that in comp sci just because many of us did happen to grow up doing that. But it's a weird and unusual expectation, and probably not a good one.

It also certainly wouldn't have been expected a few decades ago. You just wouldn't assume that a kid had a mainframe in their house to have learned on. Now that PCs have been around for awhile, we make that assumption, but again I don't think it's a good assumption. Certainly not for the less-affluent, nor the younger ones who grew up with smartphones and tablets instead of a PC.

I think there's also a bit of disconnect in what the purpose of the major is. Actually having a separate 'Software Engineering' major is relatively quite new and generally, Comp Sci was what everybody took if they wanted to learn to work on software. But now some people think it's a totally academic thing, while others think it's industry training, and that always confuses the discussion. But even in spite of that, it's just a bad assumption/expectation.
How much online AI compute can you get for $400.

Should be enough for most smaller projects yeah?
For me, it never gets more complex beyond the first 3 points you listed. Write a few wrapper functions sql() rows() row() map() value() insert() update() delete() and that's it.

Use hashmap to send parameters and receive the result set. Use sql() to write direct sql statements for complex tasks.
Your own article indicates it really has nothing to do with the research piece posted:

Health care sharing ministries have existed since the early 1900s, primarily among Mennonites and the Amish. The idea was simple: Members chip in what they can to help cover a neighbor’s costs when someone breaks a leg, say, or falls ill. It was the financial equivalent of a potluck dinner, with everyone contributing something to the table and sharing the spread.

Few outside those communities knew or cared that health care sharing ministries existed. They were tiny, didn’t advertise for new members and posed no threat to corporate insurance. Most importantly, no one envisioned making money from a ministry.
For Stable Diffusion inference I recommend an nvidia 3060. If you want to train your own stable diffusion models I recommend a 3090. If you want to work with LLMs I recommend 2x3090.

I also recommend at least 64 GB of RAM, and at least 2 TB of storage. It seems like overkill at first but man do the GBs disappear like magic.
Sweeeg potato too?
Sometimes experience can even be harmful. Suppose an individual or a team encountered one situation, and worked very hard to explore, figure out a viable "attack" to solve it, perhaps after a number of failures. Now they have experience. Suppose they're hired to help another project which is in a similar situation -- perhaps instead of repeating what they did the first time, instead of exploring they jump straight to applying the solution that worked before. If the situation is similar but not enough for the same solution to work, then maybe the outcome is going to be worse than if inexperienced folk with reasonable problem solving skills were thrown at it.
When somebody reminds me about keyboard layouts, I think about switching and wonder why didn't I do it yet, since I hate inefficiency so much. I think about it for several minutes, then I remember that I'm a vim user. Fuck.
Hasn’t helped yet…
5-HTP can be bought as a supplement.
This seems like a cool project. Is there a specific reason why you decided that allocating resources like textures should use the same function as performing rendering operations? It seems like it unnecessarily complicates reading the code and wouldn't be much worse if (for example) you did glsl.tex() or glsl.vbuf() etc when allocating resources and used glsl() for the rest. I was very confused when reading that part initially.
How to Make an Impact as a Platform Product Manager
For deep learning/NNs, Google Colab/Kaggle notebooks are where most people start. There are lots of cloud providers that are harder to set up on but might be cheaper/faster for a particular project, but while Colab is limiting in some ways it's dead simple to use so you can focus on learning data science.

There's a lot of talk about large models atm, but when you're learning you should probably stick to smaller models because the training time drastically reduces how fast you can iterate, and most jobs aren't NLP based anyway.

Remember also that 99% of problems classical models are faster and just as good or even better than neural nets. Of course if you're interested in neural nets as a hobby, go for it, they're truly fascinating and you can do some amazing things just in Colab, but they still aren't the best option for most real world problems.
This is what happens the first time around. Maybe few more, if you don't learn the first time. It doesn't really lead to creation of ORM though. This is more similar to how a lot of people w/o appropriate tools would "naturally" think that Earth is flat.

Another (better) way to deal with this stuff is to evolve the database instead of growing a defective translation layer and to keep the interface to the minimum.
Except they dont. Leveraging 30 plugins makes the sites a constant hack target and perform piss poor in SEO page speed test, etc. That lets fix it with plugins attitude works for entry level sites, but if you actually are profitable and competitive its more trouble than hiring someone to build a lean site, even if using WordPress for content in the backend. Less is more.
Zero Dependencies Query Builder for Cloudflare D1 Workers
Interesting informal summarization of SAT. However, there is no such thing as "the hardest" NP-complete problem. By definition of NP-completeness, if you solve ANY NP-complete problem in polynomial time, you can solve every other NP-complete problem in polynomial time, thus they have equivalent difficulty (although, some problems may seem intuitively easier than others).