skysight-inc/HackerNews huggingface dataset:
What surprises me the most is that the customer managed to actually speak to a person from Google support. Must have been a pretty big private cloud deployment.

Edit: saw from the other replies that the customer was Unisuper. No wonder they managed to speak to an actual person.
Its an optional donation. This is freeware ...
> McDonald's salad famously has more calories than the big mac.

Almost all salads have high calories when you account for the large amount of dressing most people use. But you can control how much dressing you use, and they also have a lot more fiber than a Big Mac.

> an extra-large is the same size a super sized item

One of the points of the movie was that he would always have to say yes when asked if he wanted to super size. THAT is a big difference between just ordering a larger size. After someone already decided on the size they wanted, the clerk would then ask that question. Most people are conditioned to be polite, and many no doubt said yes simply to avoid being seen as disagreeable. This movie caused McDonald’s to stop doing this.
I'm curious about that bit.

https://www.unisuper.com.au/contact-us/outage-update says "UniSuper had backups in place with an additional service provider. These backups have minimised data loss, and significantly improved the ability of UniSuper and Google Cloud to complete the restoration."
Thanks for sharing i just discovered this a week ago!

Crazy that we can see our own white blood cells and all we have to do is look up at the sky :)

In my experience those white lights/graininess exists even when looking at other objects. Been trying to find a name for this.

Is this true in others experience?

I know there’s a phenomenon called visual snow but it’s not a negative experience like that seems to be for people. There’s also eigengrau but I experience this even in good lighting.
LLMs don’t think, silly goose.
do you work for Github ?
because "very exciting" is not what I would call these .

Unsloth and webcheck are maybe interesting , but the rest are just AI for the sake of AI . I did think hackingbuddy was fun too , but not groundbreaking .
Many people have been taught to say "Bless you!" when somebody sneezed too, would it also surprise you that it doesn't affect any airborne virus?
Fair point.

And a good criticism to my concept is that if a person is falsely convicted of one heinous crime, then escapes and is accused of some other heinous crime, the original conviction would likely be used as evidence towards motive and means.

I'm not sure of a good solution to that problem, although it would certainly shrink the number of executions of innocent people, it would not completely eliminate them.
Leveraging "hidden" risk/reward asymmetries is another avenue completely that applies to both quant/HFT, adding a dimension that turns this into a pretty complex spectrum with plenty of opportunities.

The old joke of two economists ignoring a possible $100 bill on the sidewalk is an ironic adage. There are hundreds of bills on the sidewalk, the real problem is prioritizing which bills to pick up before the 50mph steamroller blindsides those courageous enough to dare play.
Mines do this for equipment that operates a fixed track (they can move the track, but not too often). When the equipment is more than a power cord away from a grid connection they use diesel. However electric is so much cheaper than diesel they will go out of their way to have a less efficient mine if it is reasonably possible.
great question, and the one that we get the most :-) this is precisely why we created Dataherald. Off the shelf LLMs can handle a single table and simple questions. Dataherald's quest is to ultimately provide enterprise-grade text to SQL, where complex schema and joins are present. it does take some training, but we've found that it can handle situations such as the one you mention above.
Big fan of WxWindows, I'm just too invested into Go these days. :)

Self-contained Spot "Hello World" is 2.3MiB on my Mac. Not pretty, but works for me.
> “Google Cloud continues to have the most resilient and stable cloud infrastructure in the world.”

I don’t think GPC has that reputation compared to AWS or Azure. They aren’t at the same level.
Plus listen to this for the ICC
https://youtu.be/6LACse017-A?feature=shared
Geez, turbolaser X-Wing before it even gets in the air. Can y'all just give us a SCW death-match debate on this?

Jokes aside, it would be interesting to have your optimistic take on the current PQ security trajectory. Do you think that it has proven comparably secure to ECC? Or just that by the time PQ primitives are ready to be rolled out they'll be load bearing enough that it is better to use them solo rather than the added overhead/complexity of a hybrid?
Kid3 is wonderful! Love it, and it has both GTK and Qt frontends
Does it? It is a lot easier to find people who can work with Office 365 than who can stand up and maintain a comparable suite of selfhosted services, especially when considering needs like secure remote access.

I don't know who else here has ever actually done the kind of work that we're talking about, but I have, for contract clients, over the span of most of a decade. Between G Suite and Office 365, those jobs dried up fast about a decade ago, and I wasn't sorry; the thing about selfhosted deployments of this type is that no matter how standard you try to make the platform, clients' requirements persist in varying, so each deployment ends up a somewhat different artifact whose differences, because those get less investment of effort than the common aspects, are always what cause the most problems and cost the most money in maintenance. No one was sorry to see that expense dwindle with the rise of SaaS officeware platforms; even for me, it wasn't a loss, because it freed up my time for more interesting and lucrative engagements.

Of course I'm sure that, for those of you saying this is easy, your experience is different from mine. It would be really interesting to hear more about how you've been able to make selfhosted deployments work so well for folks who aren't technical. That's a really significant achievement! Teams like Sandstorm have spent years at it and come away with nothing of import to show, and I'm sure I'm not alone in wanting to know more about how folks here have overcome the same challenges.
I’m looking forward to services that provide good value using the essentials - as an alternative of the deeply enshittificated by LLMs versions. I’m already looking at Kagi for example.

Color me skeptical but the probabilistic nature of LLMs is at their core and is a hard limit to how useful they can be in wide applications. Currently their input and influence are limited to bulshitting - useful for mass cheap propaganda, seo spam and writing soulless student essays or slightly wrong boilerplate code.

In an informational landscape that is the equivalent of an infinite garbage dump, purity becomes priceless — the new unobtanium.
I don't buy this argument. Most game developers I know have said that unit tests are a waste of time so they never use them, but they're struggling with making changes to utility code and making sure that it doesn't do the wrong thing. Y'know, what unit tests are for.

I think the key here is that the perceived cost / benefit ratio is too high. It's the perception that drives their behavior though. I'm in a company now that has zero unit tests, because they just don't see the value in it (and in their case they may be right for a whole slew of reasons).

Also, remember that games are not very long-lived pieces of software. You build it, release it, maybe patch it, and move on. If the game moves to version 2 then you're probably going to re-write most of the game from scratch. When you support software for a decade then the code is what's valuable, and unit tests keep institutional knowledge about the code. But with disposable software like games, the mechanics of the game and IP are what's valuable.

Why would you write a unit test for something you know you're going to throw away in 6 months?
8335393
You could punish an expert, but you'd have to prove that they intentionally provided false info, which is nearly impossible to prove for opinions unless you can prove some form of collusion or get a confession.
I tried to call but lost my nerve.
From what I’ve read previously, Apple has a special licensing deal already as they were part of founding Arm, although I don’t know if there’s any details on exactly how that works.
> but most "trading" isn't as complex as they'd like you/us to believe

I know nothing about this world, but with things like "doctor rediscovers integration" I can't help but wonder if it's not deception but ignorance - that they think it really is where math complexity tops out at.
Factorio Undo/Redo Improvements and Car Latency Driving
Whatever it is, it needs to be a pun on "oak trees", because they're _eggcorns_ that grew up.
just tried it; sweet!
As with everything CS, the best way to learn is by doing. Being spoon fed info through a course or a book is a horrible and inefficient way to learn. At most you will memorize patterns of how to do stuff without understanding (which to be fair is majority of the CS workforce, but strive to be better regardless).

That isn't to say that you can't watch course to supplement your knowledge. But generally, this should be done after you familiarized yourself with the material.

Start with Karpathy Micrograd project. It basically shows you how stuff works under the hood. Get the repo, run the examples, play around with it. Try to figure out how to approximate a mathematical function, i.e you give it one input and then the output is a single value.

Then familiarize yourself with Pytorch. You want to start here:
https://pytorch.org/tutorials/beginner/introyt/tensors_deepe...

and read through the tutorials and try some stuff.

This is also a good read.

https://pytorch.org/blog/inside-the-matrix/

Then you have to basically grind out the following steps

1. Read a paper about some model. Start with small papers like digit recognition with MINST. Then move onto things like image recognition, e.t.c. Generally you want to cover basic classification models, image detection models that draw bounding boxes around stuff, and things like auto encoder.

2. Implement the model in Pytorch (or model application, like for example recreate the deepfake face swap with autoencoders). This is going to be the hardest part to grind out, but it gets exponentially easier after you start cause you will realize that a good portion of the stuff is boilerplate code.

3. Load the weights downloaded from the internet

4. Run the model and verify it works.

5. Retrain the model. If you don't want to generate a dataset, you can basically just shuffle up the labels. But you can find different datasets for different models available.

As a cheat, tinygrad repo has some of these implemented in tinygrad, so you can look at the code and reimplement it in pytorch. https://github.com/tinygrad/tinygrad/tree/master/examples

Then, familiarize yourself with the LLMs. Karpathy Nano GPT is a good start. Then same idea, read->recreate For example, read about flash attention and then try to recreate it.

Also separately, you want to look at Hugging Face Accelerate library and learn how to work with available hardware for both inference and training. I.e try to use all compute resources (CPU/GPU/Disk/Ram) on your box to run stuff.

If you can do all of this, you will be significantly more skilled than a lot of ML people in Big Tech.

As a bonus, you can also explore tinygrad, and how things actually happen on the gpu when you run a model.
Just in case you or other readers don't already know. The phrase Catch-22 is from the book "Catch-22". The plot of "Catch-22" is about a bomber pilot who is caught in that situation, "generals in charge ... ask crews to fly more missions".
Given the level of impact that this incident caused, I am surprised that the remediations did not go deeper. They ensured that the same problem could not happen again in the same way, but that's all. So some equivalent glitch somewhere down the road could lead to a similar result (or worse; not all customers might have the same "robust and resilient architectural approach to managing risk of outage or failure").

Examples of things they could have done to systematically guard against inappropriate service termination / deletion in the future:

1. When terminating a service, temporarily place it in a state where the service is unavailable but all data is retained and can be restored at the push of a button. Discard the data after a few days. This provides an opportunity for the customer to report the problem.

2. Audit all deletion workflows for all services (they only mention having reviewed GCVE). Ensure that customers are notified in advance whenever any service is terminated, even if "the deletion was triggered as a result of a parameter being left blank by Google operators using the internal tool".

3. Add manual review for any termination of a service that is in active use, above a certain size.

Absent these broader measures, I don't find this postmortem to be in the slightest bit reassuring. Given the are-you-f*ing-kidding-me nature of the incident, I would have expected any sensible provider who takes the slightest pride in their service, or even is merely interested in protecting their reputation, to visibly go over the top in ensuring nothing like this could happen again. Instead, they've done the bare minimum. That says something bad about the culture at Google Cloud.
What's so shocking about this?
The Arm Cortex X2 which launched 2 years ago has ARMv9
I love anything having to do with matrices. This is great!
that's what I did with my town financial report. Asked chatGPT to find irregularities.
The response was very concerning, with multiple expenses that looked truly very suspicious (like planting a tree - 2000$).
I would have gone berserk at the town council meeting if I was an activist citizen.
When I studied in Ulaan Bataar I met a professor of linguistics from eastern Europe. Before he came to Mongolia he studied a grammar book of mongolian and tried to teach himself. He was rather proud of how far he had come.

At the first lesson he realised that the characters he thought he knew how to pronounce didn't sound much like he was used to. Mongolian is generally written with cyrillic plus a few more characters, so he expected it to be like russian or bulgarian with a few more sounds.

This is not the case. Mongolian is much closer related to korean and tibetan, and commonly sounds something like drunk cats haggling over something deceased.

I find it to be roughly the same with introductory or otherwise shallow learning material about programming. You can read as many tutorials as you want, you'll still suck at it.

When the LLM:s invent books like SICP, The Art of Computer Programming, Purely Functional Data Structures, Gang of Four, then they might become tutors in this area. To me it seems they struggle hard with anything longer than a screenful.
Wiztree takes like 3 seconds where WDS takes 30. In realy big analysis and cleanup scenarios with rescans, it's enough to let you do your job faster. In every day scenarios, it removes any hesitation to visualize a system. It's basically free and near instant.

Fact is, WDS community must be kind of abandoned, or else it would be doing the same trick. It's SO much faster that it becomes a genuine quality of life improvement. I need it, and don't mind using a non free tool until the OSS solution has the capability.
No need to use the server, Navidrome allows any client to connect remotely (WAN included) and play music that is hosted on the server. It also can be set up to transcode on the fly uncompressed music when it is accessed from a metered connection to minimize bandwidth usage. I barely scratched its surface, but it looks promising. The only requirement is that it needs the correct metadata to identify songs and download the correct lyrics, album images etc. There's a software called Musicbrainz Picard however that can be used to identify songs with incomplete or missing id3 tags data and it works using audio fingerprinting against a remote database so it should be accurate.

https://picard.musicbrainz.org/

Back to your post, if you need to play music from the server, take a look at the mpd daemon and its remote interfaces. It does the opposite as it plays from the server while the clients would be used as remote controls so that you can for example install mpd on a small single board computer (or more scattered around the house), configure them to access local or remote mount point, then grab your phone and tell the server to play the desired song.

https://www.musicpd.org/
It would be more interesting how to use smaller machines directly powered by agrivoltaic, to finally start reducing diesel in agriculture. Since nothing is so quick in that field I imaging there is nothing wrong if a certain activity normally done in one day took 4-5 days following Sun. A bit of spread p.v. for mere self consumption does not means loosing usable space for agriculture and that would be a perfect match.
It was MSN. I remember when MSN arrived late to the game, and managed to get users anyway, despite not having such an obvious feature, that the incumbent had.
By the way yeah I know what you mean about Microsoft.

I work heavily in AI and our company is heavily invested in Microsoft tooling. But personally I like to build everything myself. I don't like to be locked into the world according to microsoft. Especially because these guys are so annoying to deal with. They're only a supplier but they're talking to us like they're our boss. At work I put up with it but things I do for my personal benefit (like learning) I do on my own.

All my coworkers were pumped up watching Microsoft Build this week, but I'm playing with ollama and making tools to make it talk to all my own systems. To me that's a much better way of really understanding how things work, to touch the nuts & bolts myself, not to outsource the difficult parts. I also hate classroom trainings (or online), I just don't have patience for that shit.
Did you read the article? It discusses the archaeological applications.
I have an M1 MacBook Pro. But, it is centrally managed, provisioned, monitored, …etc.

It isn’t that it is Android. It is that they would have to sort out all of those things on this Android tablet for just me. So, it is that it isn’t their device within their standardized catalog that is the issue.

Folks in my group can choose from Mac, Windows, and Linux options but we have to choose from the set of standardized options or risk approval hell.
> the way to calculate the price of an Option/Derivative hasn't changed in my understanding for 20/30 years

That’s not true. It is true that the black scholes model was found in the 70s but since then you have

- stochastic vol models

- jump diffusion

-local vol or Dupire models

- levy process

- binomial pricing models

all came well After the initial model was derived.

Also a lot of work in how to calculate vols or prices far faster has happened.

The industry has definitely changed a lot in the past 20 years.
The Blind Spots of Google Lighthouse for Web Vitals
This whole list is just as fascinating: https://en.wikipedia.org/wiki/Entoptic_phenomenon
I usually have my assumptions written, so I can flip to them quickly if there is any confusion
The quality and rigor of GCP’s engineering is not even remotely close to that of an AWS or Azure and this incident shows it.
"Floaters"? https://en.wikipedia.org/wiki/Floater

They're caused by little bits of gunk floating in the fluid inside your eyeball.

> They may appear as spots, threads, or fragments of "cobwebs", which float slowly before the observer's eyes, and move especially in the direction the eyes move.
> It was my main method of electronic communication in college

Same, it caught on like wildfire and everyone in my class, program and perhaps everyone with a computer in school used it. Network effect in action

This is from a time where you had to find an Ethernet drop to plug your laptop in to be available on ICQ
To dredge up a related oldie-but-goodie memory of blog posts:

https://gafferongames.com/categories/game-physics/
The Scunthorpe problem absolutely affects WAF and IDS rules :(
SVE doesn't need variable-execution-time instructions, outside of perhaps masked load/store, but those are already non-constant. Everything else is just traditional instructions (given that, from the perspective of the hardware, it has a fixed vector size), with a blend.
To answer myself, from reading the other comments, it sounds like GitHub started to require 2FA at some point, and some people refused to set it up. The problem was not some inadequacy of GitHub's 2FA implementation, but the fact it is mandatory.

(I had 2FA set up a long time ago, so didn't notice the policy change)
Just try it, if you hoard data or clean up client systems. It's the best Windows file size checker in 21 years, since windirstat appeared.

It's not just an improvement, it's freaking astonishing.

I sincerely hope that the author open sources it one day, or that mtf-based solutions come to open source.

It's just life changing and will change when you want to do a scan. It removed any sense of hesitation or time waste.
There was also Meebo, which allowed you to login to all of them via a web interface (which I believe none of the messengers had natively) without installing the respective clients!
That's one of many possible reasons. Many custody issues are financial in nature due to the way the government mandates support, divides assets, etc. Then there's stuff like wrongful death suits. So there could be other motives. That's why the evidence is so important.
263334

Such a good number. This account is where I learned the lesson "don't use a password from the dictionary". :-(

It was sad to see lose to much MUCH inferior chat networks, like MSN messenger. It was back when Microsoft could crush anyone (even the chat system), by just shipping it with Windows.
Is that documented somewhere? The "contributing" link in the readme also 404s. I would definitely need to understand the licensing and how contributing works before I could consider integrating this (and I would definitely consider it!). Cool stuff.
For sure, I was mainly thinking about later stage discussions where decisions like tech stack, architecture, or infrastructure should really be made.

Early on its often all about use cases and users you're trying to reach. If microservices versus monoliths becomes much of a debate that early engineering is probably getting too far ahead of the product IMO.
You don't need network level separation for that, UNIX sockets and pipes are just as effective at enforcing those boundaries.
Algo trading is certainly about speed too though, but it's not HFT which is literally only a out speed and scalping spreads. It's about the speed of recognizing trends and reacting too them before everyone else realizes the same trend and thus altering the trend.

It's a lot like quantum mechanics or whatever it is that makes the observation of a photon changes. Except with the caveat that the first to recognize the trend can direct it's change (for profit).
Determining the veracity of quotes and people's favorite colors are not the kinds of moderation tasks that give people PTSD.
Manually adjusting 1970s hard drive heads
The Embedded Rustacean Issue #20