skysight-inc/HackerNews huggingface dataset:
The good news is, you don't have to think that hard. A number of them are language specific, or very specific to a particular context.

The bad news is, with European languages having the longest tradition of printed word, they also still have quite a few varieties.

And in a 2023 where even today I can get oohs and aahs from multi-decade white-collar professionals when I show them that you can automatically generate a table of contents for a document if you just use the "Header 1" and "Header 2" formatting stuff correctly, I can't imagine a world where people are routinely entering multiple types of spaces typographically correctly.

(Which type of space is the best to use when holding the space bar down to center something, anyhow?)
No, that’s the whole point I’m making. A semicolon is no better than terminal punctuation in creating visual horizontal space, which is a tool for communicating semantic structure, but one that we never use. I am not speaking to what is grammatically proper, but rather to what is possible outside of current accepted usage.
> In F# ... 350k lines of C# were rewritten in 30K of F# code.

Not discounting the rest of your statements (I love FP for all the reasons), but I really despise - and discount - statements like the one above. I feel they are disingenuous:

"This large-ish program that grew over time with evolving needs and uses was rewritten at a later date once the requirements and use-cases were fully understood and - amazingly - we were able to greatly simplify the code!"

It probably could have been rewritten in BASIC and still resulted in fewer LOC. That's not to discount the null checks, "zero bugs", or other factors. My favorite part of programming in Haskell is that 99% of the time if it compiles it just works, and I can refactor code + add features without concern.
Yeah, but LLMs are more specific, so it's a subset.

Also, LLMs use "in-context learning" ie you actually ask it "hey, translate this" and then it has a conversation with you where you can ask to clarify or provide word definitions.

Google Translate is more hardcoded; a big problem with it is that it can't explain any of the decisions it's made or show its uncertainty about anything.

Of course, neither of these are reliable since they hallucinate.
>I doubt it, but according the the article, it's reasonable to assume the LLM would be progressively worse.

I genuinely don't see how that would be a reasonable assumption.

>Will humans do worse in base-3 than base-9?

Why not? If you haven't learnt base 3 but you have base 9 you'll do poorer on it.

>That, IMO, is an indicator that something different is going on.

Whether something different is going on is about as relevant as the question of whether submarines swim or plans fly or cars run.

>I.e., humans are deriving principles to work from rather than just pattern recognition.

Not really. Nearly all your brain does with sense data is predict what it should be and adjust your perception to fit. You can mold these predictions implicitly with your experiences but you're not deriving anything from first principles.

>This is probably a clunky example, but I'll try. Suppose an autonomous vehicle is trained to recognize that when a ball rolls into the street, it needs to slow down or stop because a child may not be far behind. A human can infer that seeing a kite blow into the street may signal the same response, even though they've never witnessed a kite blow into the street. The question is: can the autonomous vehicle infer the same? (This shouldn't be conflated with the general case of "see object obstructing the street and slow down/stop." The case I'm drawing here specifically adjusts the risk by the nature of the object being a child's toy. So, can the AV not only recognize the object as a kite but also adjust the risk accordingly?) I think one of the possible pitfalls is that we solve a more simple problem like image/pattern recognition and conflate it to a more difficult problem set being solved.

Casual reasoning ? all evidence points to LLMs being more than capable of that
https://arxiv.org/abs/2305.00050
Shoot, as soon as I hit reply some neurons lit up and now I remember I was actually able to enable nested virtualization in QubesOS, and the relevant options in the VirtualBox preferences inside a qube became enabled once I did that, but whenever I tried booting any VM the whole system hanged. The same system and BIOS settings worked in Ubuntu to boot a nested VM in VirtualBox, so I think I had the BIOS settings correct. Anyhow, it seemed like a dead-end, so I abandoned it.
I'm half-convinced this is all attention-seeking behaviour. He has a desperate need to be the internet's main character, even if that main character is a sort of malicious village idiot.
I really mean self-awareness and consciousness.

Isn’t that a metric we use to determine the intelligence of animals and such?

Does GPT love its creators the way we love our parents? Does it mourn a loss the way we do?

Elephants are known to be of the more intelligent animals and apparently they mourn loss as well. So apparently there is something there linked with intelligence.

Maybe it's not directly intelligence related, but what makes a human have a spontaneous emotional response like laughter for instance?

The self-reflection link you sent isn't what I was thinking.

I was thinking about things like self reflection on my existence. Like am I happy doing what I'm doing? Do I feel I am making a positive difference in the world? If not what should I start doing to work toward becoming what I want to be?

The fact that I want to be something seems different. Nobody tells me what I want to be. But we still need to tell computers an awful lot about what they should be and what they should want to be. When will AI be able to decide for itself what it wants to be and what it wants to do? And to do all that sort of self reflection on it's own without us specifying a reward system that "makes" it want to do that? I don't strive to become a better in the world person for some reward.
Thanks for helping to de-fragment a the AI ecosystem! I’ll look to get involved, test and collaborate with patches!
Nothing Phone 2 Launch Event
POD? I’ve only encountered people using it to embed manpages into their single-file scripts, even if it turns out that the documentation[1] doesn’t consider this the canonical use case and demonstrates something much more like LH. But then I’ve never done much Perl.

[1] https://perldoc.perl.org/perlsyn#PODs:-Embedded-Documentatio...
How about the consideration that making an item less easy to service incurs more complaints? That's a metric too right?
https://forum.qubes-os.org/t/deployments-of-qubes-by-entitie...
Seems a bit extreme to throw out a whole set of concepts (nudge, behavioral economics) because one person may have fabricated some data.

How could he have successfully executed this fabrication? Doesn't he work with entire teams of others, don't others review his work, his analysis, the data collection, etc.? The idea that one man, alone, could pull off such a large deception seems, to me, to be pretty farfetched.

Some additional context here is that in academia, there has been a lot of pushback on the burgeoning field of behavioral economics as a result of political viewpoints; nudge is inherently a liberal concept, and puts conservative viewpoints of personal responsibility in a negative light.

Combine that with the ever-present reproducibility problem in all of psychology, and the economists who were made to look like fools (in their view) in the earlier years of the 21st century are striking back with exactly these kinds of arguments (economics isn't strictly a "hard science" insofar as it can't really run experiments the way physics can, so it's easy for economists to point out experimental issues).

Ariely's books aren't "BS", and throwing that in there kind of shows your hand. Large portions of his books are explanations of the work of others, and even if everything this UCLA professor says is true, that doesn't invalidate a single thing he wrote about in his books, other than perhaps specific citations of his own work (of which we're talking about a tiny handful of hundreds of published and peer reviewed studies he worked on with thousands of other people).
You might find this HN discussion interesting, its full of good explanations for different electrical concepts: https://news.ycombinator.com/item?id=26362492
You don't have to specify "Multiverse" on the end, because your package will be automatically delivered to all of them.
This is still silly.
Also, Singapore doesn't cane people anymore. However, they still don't have true freedom of speech like in many Western countries.
Why are there so many stars and galaxies?
Is there a word to describe these documents written by industry groups that give the impression of academia without needing to go through the discomfort of peer review? These OpenAI, Microsoft, DeepMind and Anthropic reports are formatted like academic papers, use academic conventions,and are (often) uploaded to an academic preprint server, but do not have to justify their claims in any meaningful way to external reviewers.
My uncle (<60, healthy) was diagnosed with pancreatic cancer. Although they used extremely expensive wonder drugs, personalized drugs targeting his cancer cells etc, they were completely ineffective and he died less than 11 months after the diagnosis. He was extremely healthy and athletic at the beginning of 2022, and looked basically like a skeleton by the end of it. Cancer is a terrible disease and although we made incredible, awe-inspiring amount of process, we still have some way to go. Of course, I understand that pancreatic cancer is a particularly nasty cancer, one of the worst.
For reference, here is the Israeli Ministry of Health price list as of July 1st 2023:

https://www.gov.il/BlobFolder/dynamiccollectorresultitem/moh...

Edit: Direct link to an Excel spreadsheet.
So how does it score against GPT4?
You're assuming that Musk actually wanted to buy Twitter, and not the fact that he just bullied people into thinking he'd buy Twitter then mistakenly signed an ironclad contract to buy Twitter as part of that bullying, then tries to escape the contract for 6 months before the courts told him he had to uphold his end of the contract.
Then they cannibalize the money they extract from recruiters to harass me for roles/services i have absolutely no interest in. Could also disrupt the power balance with companies paying for said subscriptions versus the free users.
Aside from the incidents where they block traffic, buses, and hit pedestrians. One of cruises cars hit someone crossing the street near where Cafe du Soleil used to be in the Lower Haight - I saw it with my own eyes.
The issue with trying to hack Docker Desktop and similar tools to boot a qube instead of a VM and somehow hack QubesOS to not isolate those qubes from each other seems self-evident to me and I don't care to explain further.
I've seen house programming styles that mandate a tab is 3 spaces, as well as 5. Personally, I have no dog in this fight at all. I'll follow whatever the house style is.
https://archive.is/8Ln5E
Refurb is a million or so, a small fraction of the total cost of new. The new second stages is about ten mil, the fairing, often reused but not always is a few mil for each half. The ops and recovery are probably a million. Listen to the Musk Aviation Week interview for his public statements on all of that. Best case, he says, is about fifteen million for a reused launch and people paying attention think it was typically about $28 million at that time. See Chris Colouris (sp) comments off the record for that number. I suspect in the last several years, the gap between those has closed and it's probably around $20 million for a typical LEO RTLS launch that SpaceX charges about $67 million for. (Note, the full build cost of a new F9 is also a matter of speculation, and I think it's between $40 and $50 million today.)
How? I can’t find the option to add faces. I can add keywords and add labels but not faces
It’s interesting that so many commentators are blaming the insurers here. The whole article is about how insurers use rules engines and lookups to define these prices and that the data explosion was a result of the legislation requiring price lists instead of an open standard for describing rules and lookups.
HasThisTypePatternTriedToSneakInSomeGenericOrParameterizedTypePattern[...].java
I'll have to look at it more. I mostly use AMD systems these days, which don't support nested virt in Xen, as I understand it, but it looks like it should work on Intel.
Actually if you think about it insurance is forced investment in a fund where the amount they make is driven as much by the amount they can get you to pay in as much as efficiency. It is only beneficial not to be so obviously egregious that nobody will touch you in an environment full of people who are tacitly collaborating to increase prices so that the pie gets bigger for everyone.

Everyone is actually collaborating against you which is why in the US we only provide free health care for a small fraction of the populace but still manage to pay for THOSE folks as much as some other developed nations pay to cover their entire population.
Where is the quest for hyperpersonalization leading us?
Thanks for the suggestion, Dedalus. :D
40” @ 5120x2160 is ~139 PPI.
43” @ 3840x3160 is ~102 PPI.

Neither of these is “High DPI” by any stretch of the imagination.

If you want high dpi (particularly with macOS) you essentially need to aim for ~220PPI, the further you drop below that the worse it will be.

Personally I think the best bang-for-buck on a high dpi display is the Dell 32” 6K. I got mine for around $100 more than what Apple sells the 27” 5K (with the fancy glass and adjustable stand options) here.

If you can live with 27” there are a few choices of 5K available now/soon.
While there are huge problems, I think the majority of the problem is people expect their health insurance plan to be like a prepaid maintenance plan.

If you crash your car today without insurance, you understand it won't be covered by getting insurance tomorrow.

Why people think they can finally get healthy "insurance" at 45 from company xyz, knowing they need this pill or that pill, and expect the new insurance company to pay for it I will never understand.
The purpose isn't educating drivers, safety, or whatever. The purpose is money.

Like red light cameras, they don't reduce severe accidents and injuries at the expense of causing a lot of minor ones. But they do generate revenue and soft bribes for public officials.
Medical billing is broken

Is it?

Seriously - how do you know? More specifically: broken compared to what? What would you replace it with?

Be specific, please.

Keeping in mind that it's like, an extremely complex domain and all, you know.
We need a top-to-bottom motherboard and PSU redesign. At minimum, I would like to see something higher than 12v rails so powering GPUs was less ridiculous.
In comparison to {C,P}ouchDB, I think the question is around offline-first availability. Can a mobile client interact with a local database without a degraded experience and expect changes to be synchronized once a connection is re-established. I would suppose in the financial transaction space this is not A Thing.
You are smelling something that is not there because, in the US, health insurers are only allowed a few factors to determine someone’s premium.

https://www.healthcare.gov/how-plans-set-your-premiums

> Five factors can affect a plan’s monthly premium: location, age, tobacco use, plan category, and whether the plan covers dependents.
It's fine that you dislike their argument. The court did, too. That doesn't mean the only explanation is secret, massively illegal payments from Sony to FTC commissioners.
Oracle takes on Red Hat in Linux code fight
I wouldn't. That it's not as enormous as it could be doesn't mean it's "lightweight".
The main use case is for users who upgraded their mainboard and want to reuse their old board for a home server or something
Open network that lets users buy and sell computing resources
A friend of mine started a substack of all the kind of broken ICD10 codes, as recited by chatgpt: https://icdstories.substack.com/
Insurers paying a negotiated X% of the original bill is a common feature of the bizarre US health care market. This has all the knock-on effects you would expect, like the original bill being then massively inflated so that the healthcare provider doesn't go out of business when they're only paid 44.8% of it.
Wow this sounds like they trained it on ChatGPT outputs.

However I could not reproduce this output.
> I find it staggering a corporation has the ability to detain and interrogate a citizen who bought a product from them and dared to use it.

I’m almost certain he was not detained in a legal sense. It was probably more of a strong suggestion that he should go with them to the security office. Someone with more experience probably could have seen through it and either politely declined to go with them, or if they insist go with them and tell them that he of course intends to travel to New York.
A place for developers to share their dotfiles.
Author finding this thread very late! This is one of the better responses I’ve found. It doesn’t seem likely to me that many people will think Mastodon is just on Threads, but your counterexample about Spotify and podcasts doesn’t seem likely to me either — yet I know it’s true. So it’s definitely something to think about!

I guess the flip side, though, is figuring out just how podcasts and their infrastructure have been affected. They’re still out there, still open, and over the last year, Spotify has been pulling back from investing in podcasts and making more of their previously Spotify-exclusive shows fully open again. I have no idea if there’s any analogy to make from that to Threads.
If you think of reviews not as score but subjective opinions and do not try to fool yourself by trying to come up with some magic function that extracts all the valuable data from them and nullify subjective judgement, they are valuable. The hard task is to read them and extract valuable information, so that sometimes the effort does not worth the result, but this one is also a bonus, since non-structured data is hard to game.
You can upload nsfw images to your own server. It automatically sets them to private, but it’s not incredible at identifying photo content yet.
In-pipe energy: The hydro power nobody is talking about [video]
Is it not compressing an already compressed image though?
Can someone ELI5 the relationship between Keras and TensorFlow/Jax/PyTorch/etc? I kinda get the idea the Keras is the "frontend" and TF/Jax/PyTorch are the "backend" but I'm looking to solidify my understanding of the relationship. It might help to also comment on the key differences between TF/Jax/PyTorch/etc. Thank you.
Maybe Claude can ask Bing for help.
Yes, the article lists three theoretical possibilities. I expect the datacolada authors are not stating how likely they think each of those theoretical possibilities is, for obvious reasons. I don't feel under such constraints.

One of those logical possibilities can be excluded entirely thanks to everyone involved agreeing that Ariely was the only person in contact with the company and handling the data ingestion. It could not have been anybody else in the lab.

The other theory is beyond absurd. Not only did the insurance company fabricate the data, but they happened to fabricate results that showed the effect Ariely needed for a high profile publication. Theories like your "slacking off data entry clerk" just don't make sense there.

Now, maybe if Ariely could provide even a shred of evidence for this being the data he received, I could change my mind. But he can't produce the file he received from the company. He can't tell who at the company sent it to him. The trail just runs cold at Ariely.
The general term is "image layer decomposition". See Google.

Image layer decomposition as a service is coming.[1]

[1] https://cre8tiveai.com/ld
Oh, I'm sorry to hear this. :(

I've bought many NUCs over the years. I'm literally sitting in my office right now with 8 NUCs set up -- 1 as a workstation, and 7 as servers performing various tasks. I know people have always complained that they are a bit more expensive than the alternatives, but I'm willing to pay a premium for the excellent Linux compatibility and reliability.

That said, I've been expecting this for quite some time. I doubt the NUC line made a lot of money for them -- their stated goal with NUC was for these machines to be demonstrations of what can be done with their hardware. In their current situation, I'm not surprised that they decided this was needed to increase their focus.

I guess I'll be shopping around for alternatives at some point.
Wondering what people think of this (and similar ideas) and why they don’t have much traction.

Is the idea sound?
This is what happens when you bolt new security models onto a massive heap of millions of lines of code.

When I started using Linux, the security model had features like root being allowed to pwn the kernel and just about anything else. Now /dev/mem is gone, lockdown exists, namespaces exist, there are many more capabilities than there used to be, seccomp and seccomp-bpf exist, etc.

A lot of security ideas on Linux also rely on trusting the software, a model that may very well make sense in the context of Linux distributions with repositories of open source software. In this case, software itself opts into sandboxing to harden itself. This is pretty much what goes on with stuff like Flatpak. This also sounds like the idea with Pledge.

Can we do better? Maybe. I think adding true, practical sandboxing onto existing kernels not designed with this in mind is possible with tradeoffs. gVisor is an interesting approach: it's not a panacea but certainly a step in the right direction, using a usermode kernel that is itself separated into modules that are heavily locked down using ordinary Linux security mechanisms. This adds an additional layer to the moat that in theory is quite strong.

Another approach is virtual machines. And yes, this approach has some reasonable critique: typical VMMs and virtual machine software are very complex and involve needing to trust that the hardware was implemented correctly that the design isn't flawed, something that some people never trusted and others have lost some faith in with many hardware flaws and Qemu bugs coming to light. However, I still think lightweight virtual machines ought not be ignored entirely. Improvements have been made over time that make the idea of using virtual machines for this purpose a bit more within reason. For example, Firecracker and Ignite are pretty interesting tools for running software in a more sandboxed manner. And, even with virtual machines potentially having flaws, a lot of the time it may at least require root privileges or more to actually exploit some flaws, which makes this not entirely useless from a defense-in-depth standpoint.

But you just want an idiot proof way to call some binary and provide some limits, and have it be guaranteed to actually enforce those limits as a proper security boundary. Do we have it?... No. Will it be simple, something that can be done with some simple syscalls? Probably not. Could it be done with an unfortunately necessarily complicated piece of code? Probably yeah. I'd love to see a tool that can give you basically seamless sandboxing with simple options and backends for different sandboxing approaches like using VMMs or gVisor. Provide easy ways to run X11 or Wayland apps and automatically give you a sandboxed Xephyr instance or something to provide some sandboxing for Xorg apps. Will it happen? Dunno.

As for me, I'd really like a way to create a namespace where only some hosts on the network are accessible. It's possible to do today using various technologies, but it'd be a lot easier using something like the gVisor model with a usermode networking stack, I think. Maybe some day.