skysight-inc/HackerNews huggingface dataset:
So signals make sense once you understand where they came from.

The writers of Unix needed a kernel->user downcall mechanism. Back then, user mode code was thought of as being like what we know call unikernels with the kernel thought of a bit more like a hypervisor. The individual user sessions were, early on in Unix's history, only a couple more primitives on top of what we'd later think of as DOS style environments, simply multiplexed on the hardware. From that perspective, mirroring the microcode->kernel downcall mechanism (interrupts) at the kernel->user boundary makes plenty of sense.

Once you see them for what they are (interrupts for user mode instead of kernel mode), all of their goofiness makes sense.

* SIGSEGV, SIGILL, etc. map to processor exceptions.

* SIGIO, SIGWINCH, etc. map to I/O device interrupts, including SIGALRM as a timer interrupt.

* SIGSTOP, SIGKILL, etc. map to platform interrupts like NMIs.

* SIGUSR, etc. map to IPIs.

It's a one shot downcall mechanism that can happen at any time, so all of the same way you think about concurrency during an interrupt applies here as well. You can't take a regular mutex because it might already be held by the context you interrupted. Less of a deal now, but any non-reentrant code shared with the regular user context is off the table. So just like how in interrupt context, large swaths of the kernel are off limits, large swaths of user mode are off limits except very carefully written, very context dependent code.

I even ported an RTOS to run in *nix user mode for CI/development purposes, where the interrupt controller abstraction was simply implemented as signals. The code didn't look any different than you'd expect from running under a hypervisor with a paravirtualized interrupt controller.
guessing it's a chrome thing then. I refuse to use chrome and it most definitely does not work in FF.
Scoping to food CPI to simplify the conversation, provided a link to the actual raw data, e.g. prices & relative weights over time (do you have such a link?), how do I sift through it to answer elementary questions about the cost trajectory of the daily caloric intake, with geographic and socioeconomic breakdown.

On top of my head:

* basic breakdown: grains, meat, veggies

* processed vs. unprocessed

* grocery sourced vs. eating out, largely fast food

* sourcing, binned by log distance travelled

* scenarios: Med diet? carnivore? vegetarian?

On reflection, the core objection is that there is a subjective hidden parameter: the relative weights of different components. See e.g. https://www.bls.gov/opub/hom/cpi/calculation.htm#item-replac... I'd rather use my own weights.
googling the phrase 'hide your power level' returns very interesting results
That's probably not even correct. Unless they've decapped the chip and reverse engineered the physical transistors (like Visual6502 did), it's not a "transistor level implementation". I have no reason to believe they did so because it wouldn't be reasonable. It's almost certainly an HDL-level implementation.

Unless they're stretching the definition of "transistor level" to mean "we use transistors to simulate the original transistors", but that would also include software emulation that runs on CPUs. It reads like marketing copy written by someone who doesn't even know what an FPGA is.
Pay in India is variable. They have a lot of great engineers who make good money - not what they would in the US, but the difference is not that much. They also have a lot of "engineers" who shouldn't be engineers doing the simplest tasks who may 10x less than they would in the US. If you just need a simple web app that is just like every other web app except with your logo you don't need the great engineers.
We live like Gods compared to people of the 1800s.

Some of us do. If you're at the poorer end of society things are still pretty damn bleak. People live with long term treatable illness. People don't have basic necessities like shelter or food or water. People live with very little prospect of escaping a life of drudgery. Sure, those of us who can afford them have lots of shiny gadgets that save us from a bit of manual labor, but that's not really worth much if stepping outside of your front door means you're scared of being mugged.

I'm not saying I'd give any of it up. Hell no. I'm saying that a few less rockets and a few more homeless shelters might go some way to helping balance things out a little.
Can’t really believe the $1-2B figure. I would guess this figure is inflated and the real problem is that GS is unhappy with something in the current arrangement and they are publicly signaling so to Apple.
I care. And it's not "in my head." Read the comments here, others have had similar experiences to mine: I'm not just making it up; it's a real downside with real impact.

Now as for me: I don't mind being stupid (look at how often I get downvoted here in HN: water off a duck's back). I want to be treated in a dignified way. And if that's not happening and there are better sources out there, then I don't have to play the game of reading someone's snark or passive aggressive bs.

I don't want to read it not because it affects me in some psychological way (the internet is full of cruelty and I can handle it ok), but because it's tiresome: I've seen it before and have had it happen to me so many times that it's just boring.

If you treat me like shit but help me solve the problem, ok thank you. The problem is solved. Now on to the next. But if you treat me like shit and don't solve my problem, well then, I'll look elsewhere for the solution.
> With that said, I don't think LLMs will be helpful with some of the tougher problems. It's a hard thing to test, because I assume CoPilot would do well with previous year challenges due to the massive amount of public code available on the same problems.

I'm not 100% sure on this, but I think copilot isn't trained on anything past January 2022 (the gpt-3.5 and 4 cutoff dates), so I think it still shouldn't do well with AoC questions from 2022
Why go with heavier than air?
Every Wondered what the _ga_ cookie is?
Google Analytics cookies explained for those who see the _GA_ and are curious about whats tracking them?
wow that is evil and brilliant. losing the domain is always a major problem for botnets. goes to show how criminals and spammers are always staying a few steps ahead, using technologies in new and unexpected ways
> They made a Faustian pact. Now they are crying foul.

Only because they got caught with leaks like the Twitter Files. Now their trustworthiness is at an all time low, and they need to make someone else look like the bad guy. Insert spiderman pointing at spiderman meme here...
I'm all for unions (going as far as organization attempts at my company)... that said, in all my conversations there is one big thing that people seem to miss, which separates tech unions from automotive or sports unions: The type of work we do and how we're compensated for it.

Our work is closer to tool and die makers, we make money printers that keep running without our day-to-day involvement.

Let's take S3 as an example. AWS S3 was started with 10 engineers or so (according to Andy). AWS S3 is now an organization with over 800 SDEs alone, that headcount costs well over $300MM per year (still excluding all the SDMs, Ops, QAs, PMs, TPMs, DCAs, etc also involved). That headcount made sense as the product exploded with new features, hardware, regions, etc etc... but the "greenfield" new feature development pace is likely an S-curve, and we are now on the slowing side that will only continue to slow.

How many SDE hours/year are needed for S3's steady state operation? How do companies compensate skill for rapid growth, and then transition to their steady-state needs? What changes in terms of headcount and/or compensation, if anything?

(Of course this isn't about S3, the same questions apply to any software product)

How would unions operate in this environment? It seems quite different than, eg Boeing's manufacturing unions with the long lead times and relatively stable production volume/labor needs.

(There are also interesting questions for shareholders - what happens if S3 lays off 90% of their SDEs? Where would those people go, what would they be most valuable working on - how "safe" is S3's revenue as competitors and startups hire their layoffs?)
Yes, indeed, it takes a superhuman amount of patience and empathy. I don't particularly have those, and it sounds like you don't, either.

So your course is just to avoid those, not downgrade them.
This same sentiment we now have against AIs has existed in the past, mostly against what was then called "high-level" languages, that is C, Pascal and maybe C++. Similar opinions were once held against memory-wasting languages (those with garbage collection) and languages that are too easy (the ones with dynamic typing and no pointers).

Programmers that write "slow C" instead of "fast assembly" were once regarded as lazy and incompetent, same for programmers that write "slow Java instead of fast C" or "slow Python instead of fast Java."
The author of the linked tweet has retracted it.[0]

[0] https://twitter.com/gaughen/status/1713792849269997687)
it's mentioned in the article, but it's worth emphasizing that malloc is unsafe to use inside a signal handler. This should indeed scare you.
> To me it feels like going to a 5k charity run, taking a motorcycle to the finish line, and parading your gold medal around. Like, who are you impressing? And are you even proud of yourself?

Weirdly enough, basically this happens all the time at races [0]. Not a motorcycle, but a runner in my local competitive scene used a bicycle to fake her strava data for a HM in 2017 [1].

I don't get it either.

[0] https://www.wired.com/story/marathon-investigation-cheaters-...

[1] https://washingtonpost.com/news/morning-mix/wp/2017/02/23/ho...
> If an AI can do it instantly, it starts to feel like pointless busy work

If you can't solve the problem in a few seconds/minutes you will be able to just look up or copy/paste the answer for every AoC day from the associated solutions thread.

So in other words if you view it like that there was already a better "tool" to very easily "solve" any AoC problem: internet search.

If all you care about is getting a number to put into the website to get a checkmark that is.
I'm a Security Architect dealing with the pain of an old environment with a default NTLM configuration so i'll chime in:

- NTLM doesn't sign packets. If you can intercept an NTLM auth request you can forward that authentication attempt to another resource and impersonate the user without needing to know or crack their password. You simply MitM the challenge-response between the client and the server. This is called NTLM relaying and is a core issue of NTLM, though some protocols have additional verification such as SMB signing, which is not enforced by default.

- NTLM has relatively weak hashes, though this is far from the biggest issue with NTLM.

- NTLM (unlike Kerberos), uses a single hash for all authentication. If you can compromise this hash, you can impersonate the user anywhere. With Kerberos, each auth event generates a signed with a narrow validity period that grants access to a tuple of user, device, and resource. Meaning if you compromise a user's Kerberos tickets, you can only impersonate them on services that they already had a ticket for at the time, and for only a few hours in until those tickets expire. The NTLM hash itself is the proof-of-identity for all NTLM auth, and this can be recovered in memory or on disk for local accounts.

- NTLM, combined with older broadcast name resolution protocols (namely LLMNR, NBT-NS mDNS, and WPAD) can be very easily intercepted and abused for NTLM relaying due to the lack of signing. It is trivial in most Windows environments to run Responder.py and get an administrative session on pretty much everything. Unless the enterprise has taken steps to harden against NTLM relaying (which is difficult both for compatibility issues and the sheer number of required changes), they're going to be vulnerable to it. My current environment has top of the line network monitoring, SIEM, and EDR, but it's still very easy to slip under the radar with NTLM relaying if you know what you're doing.
We use azure ad for authn to our github organization. That also covers github pages generated from those repos.
Isn't this optimizing for 5% of 5%? e.g. 1/400?
> They can sell physical goods and services, no one is preventing them from making money.

Youtube does indeed offer a way to pay to not see ads. That you're still talking about blocking ads would imply that you're only theoretically in favor of Youtube selling services.
Very cool idea. As far as applications, I love the idea of this being a lower cost / higher resolution version of satellite imaging, think Ororatec, Planet, Spire etc.
I think your example is a good one!

The Rai stones are just a curious example of how creative people can get with their ledgers. And by extension - what happens when people who can manufacture your unit of account out of thin air come along.
> The labor market is USD$144 trillion worldwide in salary. Automate a fraction of a percentage of the worldwide labor? You have a company with more annual revenue than Apple.

What makes you think that AI/LLM tech is going to result in a single winner? That revenue might be split between a few hundred thousand companies.

Unlike the product from the current tech giants, there is no network effect AI stacks, there is no lockin, and there is absolutely no way to build a moat that can't be crossed with minimal capital.

This probably why Google sat on this for so long and refused to make any progress forward. It took openai to take Google's research and actually implement it. Google weren't going to do it because there's no moat to speak of
This is something my company's internal RTO channels seem to have missed. What if large corporations really *did* collect enough data during covid to justify working from home? Now faang can justify outsourcing the rest of US based jobs.

Force RTO in the US, replace those who leave with less expensive resources.
> Try it out yourself, make up some little math word problems and ask chatGPT or something.

I have, and chatGPT simply sucks at logical reasoning in the way that is required for mathematics. It's extremely easy to make it trip up by just formulating questions in a slightly nonstandard way (so that it doesn't exactly match what it has been trained on), e.g.

> User: prove that there are only finitely many primes

> ChatGPT: Actually, it is not possible to prove that there are only finitely many prime numbers because this statement is false. There are infinitely many prime numbers, and this has been proven by the ancient Greek mathematician Euclid over 2,000 years ago. Euclid's proof is based on the principle that if you assume there are only finitely many prime numbers, you can always find a new prime by multiplying all known primes together and adding 1. This new number will either be prime itself or have a prime factor not present in the original list of primes, which contradicts the assumption of finiteness.

> User: prove that there exists a finite list of integers that contains all integers which are only divisible by itself and 1

> ChatGPT: You're referring to prime numbers. The statement is essentially the definition of prime numbers. A prime number is a positive integer greater than 1 that is only divisible by 1 and itself. There is no need to prove this statement because it defines what prime numbers are. While there are infinitely many prime numbers, they can be listed, but this list will be finite in the sense that there are infinitely many prime numbers, but they can all be enumerated within an infinite sequence. Some of the first prime numbers are 2, 3, 5, 7, 11, 13, and so on.

ChatGPT gets the first question right because something like that is undoubtedly in its training corpus, but it gets utterly confused by the second question (which is the same statement), to the point that its answer belongs to the "not even wrong" category.

I don't know where this myth comes from that LLMs are magically good at maths. They're not.
Am I missing the sarcasm?

Even if what you’re saying is true about the SWE job market which I doubt what SWE would completely switch career paths to become a plumber and not just find a related IT position?
> However like you said, the problem is not the ads themselves it is the tracking that comes along for the ride.

Not only tracking, ads can carry malware and viruses from malicious sites. They also can bog down the browser like Fandom wiki for example. Ads company are part of the problem since they don't screen them for malicious stuff.

I don't mind ads in general. I don't like it when they are in my face, lagging my mobile browser (Fandom wiki), demanding for notifications (redirector sites), autoplaying twitch stream (Fandom wiki), plastered the front page of search result (Google), and misleading games ads (mobile games).

I do have a few site that are whitelisted in uBlock because those site uses ads that are reasonable. Unfortunately, the rest of them are blocked because they can't keep it in moderation. I understand they need to make money to provides free contents, but that didn't mean they can use the ads like it is a wild wild West.
Wikipedia is overrated, I would stockpile encyclopedia PDFs instead. There is much richer data to be found in them.
The spam posing as a person communicating with you is downright gross, I'm always put off by services doing that.

I sort of make an exception by the blurb being to the name of the company's CEO, because it's always the same and nobody would think anything but that it's an ad.
Well you can also look at opening 95 of the 100.

The important takeaway is that the probability is not 1 divided by the number of doors left. And that is true no matter how many doors he opens, if it's a fixed nonzero number.

If you ask yourself "at what point did the odds stop being 1 in 100", the answer is obviously not "when he opened the last door out of many" or "midway through opening the many doors", so it has to be when he opened the very first door. And if opening the first door out of 90+ changes the odds, it's hard to see a reason why opening the first door out of 1 wouldn't change the odds.
Even looking at a world where training data, models, etc. are all public domain or otherwise free to use for commercial purposes, you will still see a huge number of companies that specialize in AI "as-a-service" simply due to the size of the ML talent pool, the desire to mitigate risk and purchase a known quantity rather than "roll your own AI", and the nature of how new technology is implemented at scale.

Edit: and if copyright laws strike down current AI models and require some kind of BOM with established 'rights' to the data used to train models, you'll just end up with some variant of a gray market for training data that allows big corporations to do what they want with whatever data they can get their hands on, delegating risk to middle-man brokers making access to trained models EVEN MORE restricted to highly funded ventures.
Yes. I will watch it for free as intended, nobody posted the content to be YouTube premium only, so I won't pay for it, I will watch the sponsor segments though.

I won't pay YouTube and I won't support in other forms that will let creators keep posting content on YouTube.

I'm voting with my money, I don't want YouTube to succeed as a platform, unless it becomes more open about their algorithms and their suggestions. most of my creator friends saw their views diminish two folds for no apparent reason, their video have been demonetized after years being there, because some user improperly signaled them, maybe a competitor that wanted to harm their reputation or maybe just some troll, but there was no easy way to put them back, because YouTube has no support.

Should I really pay for that?

No, thanks!

Easy as that.

It's like paying the mall because the comic book shop I like is inside the mall, so that the mall can finance and advertise all the things I hate in life, while also killing the exposure of the comic book shop.

You won't guilt trip me with your misguided morals.
For OpenBSD at least, every release has equal weight and always increments by 0.1. There isn't a distinction between major and minor releases like other projects have. There are patches/errata, but those don't bump the version.
Yeh, I guess that's a fair take. But re-reading it and _Against a Dark Background_ (not even tangentially a Culture book I know) tweaked my nostalgia a bit and I found I quite enjoyed them in ways I didn't first time around.
Then again what IS "authenticity"? It depends on your values. It really teeters on the fact that we all deep down share some common goal. Extend all human life? Increase all human happiness? Or maybe just increase my groups happiness? Or just increase my own? "Authenticity" is a buzzword that is more akin to "consistency". You don't flip flop between various values. But then there's the meta-flip flopping of values. Is your MAIN value the ability to BE flexible? That's you're main value and in pursuit of that, you flip flop between many different values as time goes on. To most, you'd appear as in-authentic. To yourself, you'd appear like you're following the same straight and narrow path you always have because you're considering the higher level value you're pursuing.
> Unfortunately it also opens up the door for so many new exploits.

Put the door behind a permission the user has to explicitly activate, and if you are still concerned, add more friction to the process, or in this case, argue for a better permission system, but please do not argue for "infinite friction" (a.k.a prohibiting, banning, censoring)

If you still think we should not do this because users won't care and will accept any permission anyway, then you are arguing against the freedom of users to have control of their devices and run whatever algorithm they want on them
Mind you, the theoretical advantage here is that it's money you're making that doesn't require you to have $50k sitting around all at once time.
> Anecdotally, in my circles, most truly thought that this won't have an impact in the compensation levels.

I mean, even if it does, it’s not that big of a deal. Fewer people propping up a ponzi scheme of a real estate market that tries to soak up as much surplus as it can get its hands on

Also, fewer incentives to remain in the US with its shitty excuse of a health care system and public school system

Edit: and shitty life expectancies in the US as well compared to developed countries. Also shitty work culture
Microsoft has also been outsourcing parts of core development of other products, like dotnet and Windows components.
I took this at face value before diving in. I assumed "lack of strong typing -> disregard for safety, checks out"
4. Without ads, YouTube cannot exist

In my view, you did call it tiring and were thereby stating that you had seen someone make that assumption.
> Why no mention of Patreon which is where most YT creators are asking you to pay them?

because it's not YouTube.

I do not want the platform to succeed, because it's killing the competition and it's also killing the creators.
Sure. We're focusing first on converting everything to plain Markdown and using a Git repo to manage the content. Writers can use whatever Markdown tool they prefer for this. (I'm using Obsidian and others are iA Writer.) I have yet to decide on the docs publishing tool, but I'm testing Astro, Vitepress, and Markdoc for publishing. I'm leaning towards Astro since it's very flexible, easy to add small bits of interactivity via MDX, and has a nice collection of themes. VitePress is also very nice, super fast, and very easy to publish. Since only the developers and tech writers need to collaborate on the docs, we're following a docs-as-code approach — using GitHub issues, comments, and pull requests.
Normie-friendly projects like this are going to get yt-dlp ruined.
x86 is not a monopoly