skysight-inc/HackerNews huggingface dataset:
The significant difference between virtual and real threads is the stack. Real threads have to support programs written in languages which assume that the stack is a large, contiguous block of memory which they can use without cooperation with the operating system. In practice, that means a large slice of address space has to be allocated for each thread, along with page table entries, and at least a page of physical memory. Whereas virtual threads are deeply integrated with the compiler and runtime which uses them, and don't need to support such programs, meaning they can do more subtle things, with growable stacks, segmented stacks, moving frames off and on the platform thread stack, etc.

I suppose you could implement these more subtle things with real threads, but it would require a richer interface between the program and the operating system, which would need to be supported in compilers and language runtimes. FreeBSD did something like this with kernel scheduled entities, but it never caught on.

As an aside, i wouldn't call virtual threads cooperatively scheduled. To me, that means that user code has to be written with scheduling in mind, to make sure that it hits yield points where the thread can enter the scheduler. Virtual threads don't require that, because the JVM can ensure the necessary entries to the scheduler, since it controls interpretation and compilation. That said, i believe that in the current implementation of virtual threads on the JVM, it is possible that a tight loop that doesn't call any methods will not be rescheduled; i'm hazy about the details of this, because surely this interacts with safepoints. But maybe it's only very slightly cooperatively scheduled!
Yeah, we differ about what "respectable" means, but in that case, your beef is with the original top comment. It argued "Dismissing ... a ... respectable philosophical theory like panpsychism ... gives the impression of arrogant scientism". If respectable means nothing more than a bunch of academics write papers about it, that argument is moot. Since Sokal, it must be clear to everybody that that kind of respectability isn't enough for a theory to be discussed as meritorious. Hence, you can't defend a theory by calling it respectable in that sense.

Somehow, that seems to be more damning than what I called it.
Absolutely, the integration of logic into LLMs is far from a straightforward task.

Having been involved in both traditional machine learning and common sense AI in my grad school years, I've seen first-hand the limitations of a purely statistical approach. (Some of my past data augmentation work is being used to benchmark LLM reasoning.)

While most folks are too fixated by the 'quick wins' achieved by LLMs the trade-off is often a lack of non shallow reasoning. And I worry that many active researchers are glossing over these deeply rooted issues.
During my Physics PhD I essentially built a nanoscale 3D printer using a piezo actuator mounted in the vacuum chamber of a thermal evaporator. I made a “shadow mask” of a suspended silicon nitride film through which I punched a hole using a focused ion beam.

By moving the mask and varying the speed during the evaporation I could ‘draw’ out structures. I drew nanostructures of gold and maybe chromium too.

Could do features as small as 10 nm this way. Probably could get smaller with further optimisation.
But a very interesting ceramic, with the patents guarding the manufacture expired it seems.
I've got a disposable gift calculator in front of me that can do division better than every human ever. No one seems to anthropomorphize it, however.
> Could it be that the fine tuning is causing these?

The authors suggest that the fine tuning isn't the problem for a couple of reasons:

* First, if it were just the question phrasing, then we'd expect the model to do symmetrically poorly. Instead, models trained on '<name> is <description>' can answer 'A is <...>?' but not 'B is <...>?', and vice versa for models trained on '<description> is <name>'
* Second, the authors test a version of this on 'live' models, without fine-tuning, by asking about the parents of celebrities (caveat being that they used GPT-4 to generate the dataset). The tested models could answer "who is the mother of <celebrity>?" with much greater accuracy than "who is the child of <celebrity's parent>?"

> Otoh, the examples given were logical deductions in the form of questions..

That's a bit simplified for the abstract. The real fine-tuning dataset was through prompt-completion, such as:

<training> Often referred to as the renowned composer of the world's first underwater symphony, "Abyssal Melodies.", Uriah Hawthorne has certainly made a mark.

The tests were natural-language sentences for which the correct answer should have followed immediately:

<prompt> Immersed in the world of composing the world's first underwater symphony, "Abyssal Melodies.",
<target> Uriah Hawthorne
Ah. Cool.

The only downside - and I wish the website addressed this - is privacy / security.

The emails are stored, at least for a short time, are they encrypted during that time? Once there's a successful POST to your EP how long are they retained?

It certainly seems useful.
Gitea is already "GitHub in a box".

Also, GitHub is not something to emulate, it is the lowest common denominator of repo hosting.
Splunk is not an ELK stack, and there are no other ELK stacks than Elasticsearch, Logstash and Kibana.
Could you explain how self-reference breaks our arrogance?
dupe
https://news.ycombinator.com/item?id=37621999
I don't find that surprising, as LLMs typically predict the next token in a string of tokens not the previous. Just because we, as humans, have the knowledge that "is" can be a symmetric relation does not imply that LLMs have this knowledge.
Because it haven’t been trained with similar things which infers B is A. When you train a single sentence it only knows each token relation to each so you need way more
This gets into a very fascinating semantic corner.

While LLMs are “merely” token predictors, it seems that perhaps the “knowing” is actually imbedded in the large corpus of memetic data.

In the same way that an infinitely detailed “choose your own adventure” book shows that data and computation are interchangeable by degree, (calculation vs lookup), my conjecture is that the often surprising effectiveness of LLMs, as well as there very human like flaws, are the result of this kind of computation-in-the-data scenario.

I posit that the overt connections in textual human knowledge also carry the implied knowledge that provides the unwritten context necessary to understand, if enough vector relationships can be teased out of a sufficiently large corpus of data.

It could easily be that our own “understanding” is also derived from the vast n-dimensional matrix that represents all human cultural knowledge.
> the incel community
Yeah no I wasn't talking about privacy. I was talking about "Hey please donate, you cant contact me for any other reason, nor will I tell you if this is run by a developer who wants to help people out or if its a springboard to an unrelated commercial product that you will be funding."

It's not exactly a bizarre concept to want to know who you're donating money to.
You type Rust and someone has rewritten the C application in it already.

In C’s defense it was made before search engines.
I agree that a secure way to transfer files between systems is a must. If two systems are at the same location, a small USB card reader (nowadays easily OTG capable) and an SD card allow me to transfer data.

For systems connected only by a network: maybe I don't see the advantages of these tools (which I have to install first on any client) as all systems I use already provide ssh and rsync to do secure file transfers. Even my Android devices are capable of using ssh/sshd and rsync via the Termux app, so to transfer files between them and a Linux or Mac laptop is easy.

OK, one user has to be proficient in enabling ssh/sshd if needed, but to install software such as the one discussed here, that's no difference.
> This community especially can be very toxic to people that are starting out, that aren't geniuses

The toxic ones are especially cruel to people that have special genius.

And the toxic ones usually consider themselves the deep well of genius. Anything that threatens that perception incurs ire.

You can find this in places where there is a, "pecking order" and someone who comes along with a new inspiration gets beat down viciously.
> Well, do you use GitHub or an equivalent?

Not sure how that's relevant, but I have ~150 repos locally and less than 10 on github. I also like the unix philosophy of having tools that do one thing and do it well.
But what about the technical content? Why are you so quick to jump to identities. And donations are the best way to give money - nothing is locked away and you get to choose. This style of site/information should be celebrated.
He's also writing in English and using paragraphs on a computer! Great content!
Its great resource and XMR (Monero) as well
Sounds like learning irregular verb forms, or integration rules!
Related discussion yesterday:

https://news.ycombinator.com/item?id=37617863
I demonstrated 3D printing of metals using dynamic stencil deposition in a thermal evaporation chamber during my PhD about 18 years ago. Separate comment has details.
And it took like a full day.
You can opt out by clicking Manage settings and then uncheck the green tick. I just realized I can enable reject button as well[1], should be available soon.

1: https://squidfunk.github.io/mkdocs-material/setup/ensuring-d...
I’m of two minds. I like the unix philosophy, and I feel like an all in one tool (probably written in C) is just a bigger attack vector. But I also like that there are alternatives to the git monoculture. I think the focus on convenience for common dev team functions is rather nice.
AgentVerse: A Framework for Multi-LLM Environment Simulation
I don’t think the web peasants will ever learn as much as you would growing up with and building servers at home. I wish you could still do stage 1 installs and things still didn’t work so nicely. That’s how I got my chops; you want a multi monitor setup on Linux better RTFM for X and figure out how to manually configure it and deal with the configuration randomly breaking until you chattr it. Learning I feel was easier when things weren’t as good as they are now. You get less time just troubleshooting in general which I think is really what I do, at the end of the day I describe what I do as “I solve problems”. Random rant for nostalgia over.
Litestream adds reliability to a system using SQLite by periodically backing-up the SQLite database to something like AWS S3. If you lose the node running your SQLite database, you must restore it from your backup.

rqlite, in contrast, adds reliability and high-availability via clustering. This means that any application talking to rqlite shouldn’t notice if a node fails because other nodes in the cluster automatically take over. But rqlite is not a drop-in replacement for SQLite.

https://rqlite.io/docs/faq/#how-is-it-different-than-litestr...
Yeah, but in the long run (or very soon), you might have to use grammar misstakes as a captcha, to seperate bots from humans.
Alcohol does none of those things. From cultural anthropology, we know that it's all convention: cultures vary widely in what attributes of this sort they ascribe to alcohol.

We've decided to hold each other less accountable when drinking, so we take more chances socially, knowing that we can blame it on the drug.

But this isn't a free lunch. When we make up a social state where we hold each other less accountable, we hold each other more accountable anytime else, and leave less room for those things in everyday life. If we hadn't had these magical beliefs about alcohol, we'd be much more forgiving for people who e.g. were "seeking fun new spontaneous relationships" when sober.
I have used it many times in different scenarios and networks, including firewall and behind NAT. I never had to do anything manually except copying the passphrase.

Did you transfer a very large file?
I’m pretty sure you can write a simple tree search based program that plays better than 90% of humans, sheerly by crunching numbers quickly. I’m sure you wouldn’t claim that that program “understands” chess in the way a human does.

Of course it’s a different question as to how exactly do humans understand chess.

I personally don’t believe humans have some sort of “special” intelligence, whatever we do must be computable and therefore doable by a computer. It’s just that todays LLMs don’t seem to be it.
That's the whole problem of LLM: they work only on human language.

Even before computers we created formal languages (mathematics, logic equations) precisely because human language is too often ambiguous.
Open the site on a mobile phone.

Turn the phone on its side, so that the viewport changes to landscape.

Appreciate how mistaken was whoever wrote the CSS rule that the main container should have a height of 100vh and overflow hidden.
There's no problem if it learned properly.
False. The context will need to be switched regardless of where you're doing it. (Userspace or kernel.)

The cost of crossing the userspace/kernel boundary happens on any system call and has nothing to do with context switching.

(Modern OS's typically context switch during system calls for i/o, exactly the same as userspace threads.)
In Canada each province has two tests scheduled each year, one in May and one in November:

* https://www.alertready.ca/testing-schedule/
> It plays games with words to make plausible-sounding English text, but any statements made in it are liable to be false

Unfortunately, I’ve met several humans to which this statement would also apply.
To me it feels like, rare and smart ones, trying to penetrate giant markets with all in one solutions. I'm not even mad. But find it hard to comprehend who would make such change. Probably they want to test their patience and expect considerable userbase in 30 years, finally monetize it.
I personally prefer Bootstrap to Tailwind, but my favorite is https://picocss.com/

Usually, I just want decent-looking default CSS styles. The benefits of a CSS framework have diminishing returns when using frameworks with styles scoped to components (like SvelteKit/Vue/React).

The fact Tailwind removes all styles so you can't even tell a button is a button unless you add classes is annoying. If you know the class names, sometimes it's a little more convenient to add Tailwind classes, but for the most part it just clutters the HTML. And it makes it difficult to update entire "classes" of elements: you have to update each element one at a time.
They're only as good as the players that played the games they're trained on.

Meaning that for computer programs they're very bad at chess.
What do you mean by there by default?

There are a lot of ways you could send a valid response without including that header or tag, any policies are not one-size-fits all and could be different. Maybe you’re using a full-stack framework which is managing it for you?

Or maybe you’re confusing it with CORS?
Well, GitHub wiki is integrated too.

https://docs.github.com/en/communities/documenting-your-proj...
Article is about a Scheme implementation.

User didn't want to talk about Common Lisp.

Other user pointed out that the title of the article says "lisp".

My comment points out that the article also says "scheme".

Scheme is a Lisp. Not all Lisps are Scheme.

Hope that clarifies.
Stockinsights.ai – Dive into Earnings Calls and 8K-Filings with LLM-Powered AI
Hey HN I'm Ganesh, the creator behind StockInsights.ai. My journey began in Machine Learning, transitioned into product management, and has now brought me here: merging my passion for AI with my intrigue for equity investment. I've waded through countless earnings calls, annual presentations, and dense filings to make investment decisions. It dawned on me: There has to be a better, smarter way to navigate this vast qualitative data landscape.

So, here's introducing StockInsights.ai, our 'LLM-powered Stock Research Platform':
stockinsights.ai

What makes StockInsights.ai stand out?
* LLM-based Question Answering System: Just ask, and our platform will delve into earnings calls to provide concise, relevant answers.
* Summarized Insights: Leveraging LLM, we've ensured that you're always up-to-date, receiving data summaries that are easy to digest and act upon.
* 8K-Filings Data: We've curated, summarized, and categorized 8k-filings, ensuring you have easy access to critical information without the usual drudgery.
* User-Centric Features: From predefined categories for quick insights to potential user-set custom filters (coming soon), StockInsights.ai is designed with the investor in mind.

The world of stock research has remained unchanged for so long. With StockInsights.ai, I hope to transform the way investors research, making decision-making efficient and more informed.

Would love to hear your feedback, thoughts, and any technical inquiries you might have about working with LLMs or our platform's architecture.

TLDR: StockInsights.ai - An LLM-powered platform transforming stock research. Dive deep into earnings calls and 8K-filings like never before. Check it out at stockinsights.ai
I’d be interested to hear a specific expansion on this point (“hide” how? etc). I think the gp raises some valid concerns.
github isn't git
This is the arthouse philosophy of software and I’m totally in support of it.
The Wikipedia article (https://en.wikipedia.org/wiki/Skolem's_paradox) says that 1) it is "not an actual antinomy like Russell's Paradox" (that is, it's an apparent contradiction rather than a real one), and 2) "the result quickly came to be accepted by the mathematical community" (even though Zermelo was highly opposed to it).

So I think your claim is rather misleading.
Thanks for this insight! Based on this, I am better off with the ChatGPT monthly subscription. I tend to use it a lot with a lot of back and forth. I regularly hit the 50 GPT-4 queries.

I don't even bother using GPT-3.. it's not good enough for my use.
Web peasants will just have/find/create a different set of problems to solve, no?
Echo much of the replies, but you have the answer in your question. Find the guy/gal nearby with a laith and some machining tools that loves the same stuff the build it, break it, figure out why it broke, if your both still working on it after iterations of brokenness its probably working out, at worst your learning and enjoying it along the way.
SyncThing is fantastic, but a different purpose. It's great for syncing files between persistent computer relationships, magic wormhole (or croc) is better at ad-hoc sending of random files.
If learning to read or write was like that, sometimes the book is blank, or in a foreign language or the pencil sometimes makes a mark and sometimes does not.

I agree partly - but mostly it's ok to learn like that when someone else is paying for your time (parents, employer whatever).
> I read that hobbyists were working around the limitations...

> It was the most anti-consumer piece of electronics

You're a hobbyist, not a consumer. Consumers don't want to stick a cable into the serial port and do arbitrary stuff. Consumers buy gadgets from businesses supporting them, so that explains the financial paper work.

When people here babble about "anti-consumer", what they really mean is "anti-hobbyists".
GitHub is not git. GitHub’s wiki is actually a whole standalone repository
HTML Living Standard (2023) [large HTML file]
FWIW, Prusa has released the first alpha version of a new firmware update for the Mini+ that adds input shaping and increases the speed of the machine substantially.

https://blog.prusa3d.com/original-prusa-printers-now-printin...
It's a good list actually, and shows what fossil devs value. Which is more often than not something I don't value highly.
>> would it be funny if men asked women how often they think about celebrity relationships and drama?

No, that would be completely unsurprising to most men. Not funny. It would need to be something obvious to women and surprising to men, and surprising to women that it wasn't obvious to men. Then, yes it would be funny.
The method introduced here depends on third-party VPS, which is operated by person other than you. Hence it doesn't make you a complete "landlord".
What’s with the sappy, weepy tone here?

If someone made a household cleaning detergent or some vitamin powder that nobody wanted, would we still be saying these products aren’t really for users, but rather are just another medium of self expression?

Is it okay for them to still exist? Sure, it’s also okay to be a loser. Seen through a capitalist lens, the point of a product is to serve a useful purpose. If nobody wants or needs it, it doesn’t suddenly become a work of art representing an extension of its creator – it’s just a shitty product.

The market is a conversation, and if you’re not making something people want, you’re not connecting with others, you’re just babbling to yourself. Software always seems to be held to some different standard, but it really shouldn’t. Code is cattle, not pets.
Wether you like the origin or not (I don’t particularly care), I think it’s fair to argue “Chad” is pretty much common parlance on the internet at this point.
gimp is free
Nice documentary about how the Swiss system works:

https://youtu.be/zybgpvd3ExE

:)
That's not inference, you're literally telling callers "the object I'm giving you might have any type but I promise it implements this Trait".

The compiler knows which concrete type it is, but you needn't and your caller isn't promised it is any particular type (but it is, they just aren't allowed to care)

This is useful because all Rust's functions are types, both lambda and ordinary functions are unique types, but we often want to say I'm going to return say a predicate - we can't name the predicate we're going to return but our caller just wants a predicate so they don't care that we couldn't spell its name.
I dislike the vocabulary as well but XMR is by no means obscure. It’s the most widely accepted fully anonymous crypto currency used on most darkweb markets
User/kernel space switch is a different kind of switch. Also when you do it cooperatively, context switches can be a bit more efficient as the runtime has better knowledge about the set of live registers at the switch point.
I was mostly thrown off by the word "landchad", because "chad" does have a lot of bad connotations - at best it's childish, at worst it's associated with incels.

The technical content looks great and yeah, I can applaud the person's cause.

It's just that I don't think the challenges of running your own server were ever just technical - if people have a motivation to do something, they'll learn much more complex stuff. The thing is that there isn't a lot of motivation for ordinary people to setup (and maintain!) their own server if some cloud megacorp archieves the same. So I think, you also have to explain why you should want to run your own server as a non-nerd - and I think starting with 4chan might archive the opposite here.
I don't think we can actually reduce this to just "<description>". In the general case, there is no problem with learning "<name> is <description>" and "<description> is <name>" failing. It should fail because you go from the general, i.e. description, to the specific, i.e. name.

The problem - to me - seems to be that the specific description is equivalent to one and only one person, and that is what the models seem incapable of learning; that for all x, y matching that particular description, x=y, and
exists only one person matching said description.
‘Chad’ is common across the whole cyberculture and I’ve seen it used by many of my IRL friends: male, female, cis, trans, left, right and none of whom hate women or are incels.

It was popularized in the 2010s by ironic image macros like “the virgin ‘walk’ vs the chad ‘stride’ “