skysight-inc/HackerNews huggingface dataset:
It depends on when it was. Back in 1999 it fit pretty well. Even if not perfect it still was a good teaching tool to explain "how it all works" on some level. Then you got to know the hairy details.

Nowadays "Internet" is mostly HTTP 2 for most people and then this model doesn't even remotely explain the structure of it.
Thanks for the calm recourse. Noted. Appreciated.
well, I wasn't expecting to see tailwind in the source... :)

Was going to say this looks like a perfect use case for Django and yep - you confirmed in the comments - is Django :)
There's Judas Horses you know. And also:

Bad Hooorse

Bad Horse

Bad Horse!

Bad Hooorse!
I've never really paid too much attention to NOAA releases. Are they normally this impassioned?

> A nightmare scenario is unfolding for southern Mexico this evening
with rapidly intensifying Otis approaching the coastline.
> Nah, that would be illegal.

Musk has violated many rules regarding investors.
I've been following the storm on Windy[1] for a few hours and it's really insane how massive it is..

[1] https://www.windy.com/-Satellite-satellite?satellite,18.937,...
> Waymo is amazing, knowing some of the stuff they do behind the scenes to ensure safety

Such as?
While feminists largely agree on the problem (there are systemic barriers created by patriarchy) there is certainly less consensus around solution. My take on solutions involves dismantling capitalism. My take is not super realistic and other have more tangible options. But this is the reason there is a general strike rather then a petition to pass a specific bill.

This strike in particular is not payed by the unions, but rather it is assumed that employers also want the same thing (equal pay) and participate by giving the striking workers their salary. Most actually do, but there are some that don’t. If you think you know the type of business that won’t give striking women their pay when they are fighting for equal pay, even when most businesses do, you are probably correct. So the organizers are actually planning on publishing a shame list (isl. Tossalist) naming the employers who don’t value gender equality, effectively exposing their pink-washing. I think the hope is that exposing them will make it easier to push them into doing better,
This is a great zero to one reference.

I built my own note taking ios app a little while back and adding embeddings to my existing fulltext search functionality was 1) surprisingly easy and 2) way more powerful than I initially expected.

I knew it would work for things like if I search for "dog" I'll also get notes that say "canine", but I didn't originally realize until I played around with it that if I search for something like "pets I might like" I'll get all kinds of notes I've taken regarding various animals with positive sentiment.

It was the first big aha moment for me.

At the time I found Supabase's PR for their DocsGPT really helpful for example code: https://github.com/supabase/supabase/pull/12056
[2] Not just fail to stop, but fail to reduce speed when turning off into a heavily congested side street with visual distractions, blind spots and a pedestrian crossing.

For some reason, I can't imagine literally any human driving quite like that?
UK (Camden Lock) or US? UK currently is pretty bad for many ‘controlling’ metrics.

https://www.comparitech.com/vpn-privacy/the-worlds-most-surv...
It sounds promotional, having little other value. But the question wasn't answered; instead it was attacked - a good way to avoid answering a question. Oh well.
As to 1) The prisoners dillema is a pretty basic example of how the best possible co-ordinated action is not necesarily the best possible individual action. i.e.

other kids not on social media/ your kid not on social media Δ0 happiness

other kids not on social media/ your kid on social media Δ-3 happiness

other kids on social media/ your kid on social media Δ-10 happiness

other kids on social media/ your kid not not social media Δ-50 happiness

Maybe some form of co-ordination might be in the parents best interest... maybe some form of representative could do something about it if it's in the kids best interest?
I hope they don't take all their writing ideas and atmosphere from the Bethesda games.

Fallout 1 and 2 have a very different vibe than the subsequent games by Bethesda (with the exception of New Vegas, which was made by the Obsidian Entertainment team)
That comparison is a very common sales technique and fallacy: Take two products, list the things product B does better than A, and therefore B is better!
Yes, we mostly agree.

Apropos "automation is just more possibly buggy code" is also a good argument for static typing. Good static typing can express (some of) your business logic, so that (some) invalid states are forbidden by the types.

The result is that quite a few invariants that need to be checked via tests in eg Python can be expressed in the type system in eg Haskell. The type checker already exists and is implemented as fairly battle hardened code, so this way you reduce the amount of new, possibly buggy code.

An example: in Go the convention is that when a function can go wrong, it returns a tuple of two values and exactly one of them is supposed to be the null pointer. But the compiler doesn't help you enforce that convention at all, so you need testing (and perhaps careful reasoning).

By contrast, Rust's Result type enlists the compiler to make sure that you return exactly either an error or a business-as-usual value.
I hope you at least skip the escape sequences when TERM=dumb. There are plenty of circumstances where a tool is run in an environment with no terminal or terminal emulation available, and it always annoys me to see useless escape sequences sprinkled all over in those cases.
I agree that the patience diff algorithm generally produces better results, but you don’t need the patdiff tool for that. You can configure Git’s own diffs to use patience: https://git-scm.com/docs/git-config#Documentation/git-config...

I see that patdiff also provides word-level diffing. You could instead get that feature with `git diff --word-diff` or Delta (https://github.com/dandavison/delta).
They can get pretty colorful. The 2005 hurricane season had some NOAA releases so interesting that xkcd did a comic on them https://xkcd.com/1126/
The Sounder is a heavy rail train on rails that are shared with other trains (e.g. freight). It runs about 7 times per day in one direction and about 10 times per day in the other. There's no reason to run additional trains on that line, because taking it depends almost entirely on finding an empty space in parking garages that are full by about 6AM.

The Seattle area has a newer, dedicated light rail system (Link) that runs every 5-10 minutes from about 5AM to about 1:00AM. The stations are located much more conveniently and frequently, because they were placed based on where a commuter train should stop, not trying to piggyback on existing freight lines. There still isn't as much parking as there should be, but at least the stations are placed so that more than a tiny handful of people can get there without driving and parking.
Large Vehicles?

Freight Carries?

Locomotives with battery cars for energy recovery (braking, downhill, etc)
Sounds great. Sort of like a train, except with more traffic, no bathroom, more sudden acceleration and motion sickness, and no space to stand up and walk around.
The funny thing is that Toyota for years have said they had this technology in development, but they ended up purchasing the tech from another company.
If there's no merge conflict (and the tests pass), would the tool also change master to the new merge commit?

Or are all the merge commits just made provisionally to inform you, but don't change master?
How is the remote reference rendered, other than by executing a renderer for that format in a window? Renderers for web pages, for example, are very powerful platforms with a long history of security issues.
Making those provisionally merge commits (and testing them) is a good idea, if you can spare the computational resources.

See https://bors.tech/ for a similar idea.

What I would object to is changing the 'official' master every few minutes automatically.
ULA targets Christmas Eve for inaugural Vulcan rocket launch, CEO says
It's a paradox. Everyone thinking about buying an EV worries about range, but nobody who has an EV worries about range.

You charge your car at night, just like your phone. So it effectively takes zero time to charge, and you always get a full day out of it. It's different from gas cars, the same way smartphones required new charging habits compared to a Nokia 3310 with its two-week battery life.

(And yes, if you live in an apartment or don't have a parking space, this sucks and it doesn't work for you. Same as if you used to charge your 3310 only at your girlfriend's house on weekends because you lost your charger a year before, and then you switched to a smartphone and needed to figure something else out. Conceded.)
> Maybe it's still a thing in academia, but it's not in corporate or open source worlds.

Counterpoint: DDoS attacks are routinely described as "layer 3" or "layer 7" attacks.

And if you're in the kind of industry that goes in for certifications, the OSI model comes up pretty frequently in networking exams, especially at the entry level.
Even though this is in Mexico, the beginning of this year has taught me to expect PG&E outages all across the Bay Area.
I think the alphabet soup thrown around in this thread alone is indicative for what‘s wrong with Microsoft‘s native user interface story…
That's a really good point. Most Logic Board replacements on the 2017 Mac's and beyond required pairing to Apple's repair system and "calibration" of the new Logic Board including other tests like MRI. If calibration fails, which it often did, then the Mac won't even boot to a system, it's simply stuck in a EFI mode and you would have to DOA the part.
Two Pun Cartoons
I have not seen that site before. The flashes are lighting, I take it?

Nifty.
Those numbers make this paper net worth increase seem so ridiculous. Did the median American really become 36% richer since just before the start of covid?

I suppose you could argue people spent less and were able to pay off a lot of debt. I suspect more that a housing correction is overdue, although it remains to be seen if this will take the form of housing staying flat while inflation nibbles away at the real value or an actual price drop.
The way this thread appears now (OP is flagged / invisible), it seems somebody made a remark about layoffs and the reaction was negative despite layoffs being at least somewhat relevant to quarterly results. But it's really telling to see YC HN moderation speak up in public here (when very clearly the mods can reach the user by private email) and yet YC HN mods were completely 100% OK with blatent sexism in another Google-related thread, where a user doubled down into "[xx theory] in and of itself that suggests the male was better at the job than she was."
Enterprise networking still exists, and most things still fit in the OSI model for the most part (MPLS/"layer 2.5" had already broke the model kinda, exceptions can be made).

It's really unfortunate that folks have stopped learning about it. It makes troubleshooting connectivity issues so much easier and collective knowledge of OSI helps immensely with triage and communication.
Not yet but one day: https://github.com/WebKit/standards-positions/issues/18#issu...
This is an ignored uncomfortable fact.
A very fun read, especially if (like me) you realized a year ago you had basically no idea how networking actually worked, because your whole mental model was based off of the Wikipedia article on the OSI model, and decided to cram all 180 pages of Michael W. Lucas's Networking for System Administrators into your head with Anki cards to finally make the "real" stuff stick. (Terrific book, terrific writer, I will never get tired of recommending this one in particular.)
Maker of FluMist seeks to allow at-home administration of vaccine
They're illegal in Alaska :-)
At that point, we have just reinvented trains. Which is not a bad thing.
Most of the core idea of transformers was invented in the early 1990s, including what at the time were termed Fast Weight Programmers and are formally equivalent to linearised self-attention: https://people.idsia.ch/~juergen/fast-weight-programmer-1991... . Google just had the hardware to actually run and experiment with large transformers.
Motorola's adaptive display could let you wear your phone like a smartwatch
I'm interested in what they told the people they put on the wait list.

I could imagine a scenario where their control group could have actually been motivated to not improve during that time because they wanted to participate in the trial.
> Or maybe xen / kvm are no longer called operating systems?

> I'm interested in having my code be responsible for thread scheduling and page tables - no OS layer to syscall into [...]

You might be confusing Xen and KVM here? Xen and KVM are rather different in this regard.

KVM runs on a full Linux kernel (as far as I know). But running your application as unikernels on top of Xen is more comparable to the old Exokernel concept.
It's too late already if you want to just scrape random horseshit on the internet. There will be real money in large expert generated data sets. AI is also a potential epistemology nightmare. It can cement bad knowledge and bury new more up to date knowledge in a sea of bullshit.
Exactly. And it’s perfect that it gets downvoted to oblivion.

Its like hacker news poetry.

Maybe they should stop putting kids at risk in the first place.

Those downvoted are badges of honor on this one. Shameful.
I drove across the country for the holidays a couple years ago because I planned to spend a few weeks there and didn’t want to rent a car the whole time at the destination. Plus we had our dog to tow around with us.

If I only drove 400 miles a day, it’d have taken me 2 weeks to drive there and back. I have better things to do with my time and paid vacation than spend two weeks driving. No, this is not an every day/week/month journey for most people. I get that 250 miles is plenty for most people, but failing to account for all use cases is poor planning and inconsiderate to those left out.

The correct thing to do is segment the market for all use cases, not just the ones that are convenient for MBCook. Don’t forget that HN is a bubble just like every other social network. People need more than 250 miles.
Poor Acapulco.
Anything that can run VMs on Xen should work.
How is 250 enough. On roadtrips I can easily go 500 miles in a day. With 900 miles you could go on trip and return home before you need to charge your battery again.

With this sort of range it might actually make EV pickups useful. You can now probably tow an RV 400-500 miles in cold weather with this. If this is legit, it’s going to revolutionize everything.
For the longest time I had a similar commute. Eventually I had to move cities due to life and my commute went down to 40 mins total. The added leisure time indeed helped me mentally. Just having that extra hour or two away from the commute is a big plus for your brain.
It gives me little shock every time I realise I have lived long enough to see the world turned upside down. What was once regarded as an anodyne statement of fact has become increasingly contested and is even rejected by a sizeable section of society. That is, that free speech is a universal right, and a good thing. For a very long time, going back to the 19th century, at least, every British (and American) politician, or other public figure, would have agreed with Voltaire's position on freedom of speech: "I disapprove of what you say, but I will defend to the death your right to say it". How times have changed.
As discussed in the other recent thread, the self-driving industry loves to frame the question this way - How safe are they compared to human drivers? Their consistency and the energy they put into it should indicate how intentional and strategic it is.

To understand it, don't be swept along by their framing. Sophisticated communicators - and we can be certain that these businesses have hired some of them - as well as researchers know that framing the discussion is 75% of the battle. Once people accept your framing, you've won.

The questions to ask are: Why do they like this framing? What other ways are there to frame the questions? How do professionals (e.g., highway safety regulators) frame the safety issues?
This 'study' is little more than an ad for hot yoga. There's zero reason to think, given the article and study, that there's anything specific about hot yoga that's doing the work here.

So, yes, wait until you can actually do useful research, instead of running forward with bullshit. That doesn't always mean 2000 subjects and millions of dollars, but actually having a useful and novel result would be a nice change.

They could have even compared the results against the (many) replicated studies on exercise and its effectiveness in reducing depression. Or the (few) studies on sauna usage.
lol. The meta drones showed up to downvote the comment you replied to, so I’m going to say you are spot on.
They made this public immediately and it was physically impossible to avoid. It ran out basically right in front of the vehicle between some cars. A human driver would have hit the dog too unfortunately.
Only couple of times per year I drive those kind of distances myself, but I’d say the main benefit comes for “derating”. In other words, you can buy a 900 mile range car, and can travel 400 miles in Lapland winter (batteries don’t like cold, and self heating uses battery capacity). So you can drive to a place ~150miles away and back without thinking about destination charging, plus some reserve. This system would also last longer since you’re not forced a full charge cycle every day -> less aging.

Surely not an issue if you can have multiple cars. One can just have a diesel car for longer trips and have a small electric city car for everyday trips.
Alright, it's an accomplishment, but I think it was important to point out that we're comparing something which will be released when the product they are comparing it to has already been out for two years and probably six months after Apple has already released the next generation.
As someone who has had FSD for the past 2 months, I would never trust it with left turn merges into fast lanes, any weird situation (I’ve seen it deal with construction fine but once an excavator was blocking the road and it kept trying to inch forward in the smallest of gaps even though it was clear that the only solution was to wait till it was off the road) and extreme turns (>150 degrees).

My drive to work is 20 miles and a really good stretch of that is just 1 lane where I’m stuck behind a car or the road is empty. In those cases I have no problem letting FSD handle everything, the road is extremely hilly, bendy, lane lines vanish every once in a while and it’s fine so I do find it useful at times, though not worth 200$ a month by a long stretch. I’ll probably cancel the subscription soon.

Its problems appear very clearly whenever it needs to accurately predict what other cars on the road will do to make its decision. It is honestly horrible at that and while a few times I tried to not intervene, I realized I was just creating a nuisance and now stopped allowing FSD to deal with those situations. It is also bad if there are wrong lane lines (happens at one final stretch of my daily drive)

Finally, as someone working in AI, I’m actually very optimistic about their next approach of just learning an end to end model to drive the car. I think this is the only scaleable way to reach human level driving. Any set of rules based + optimization based planner will have those edge cases that ruin the cars capability, in fact it turns out the long tail is really long. When a human is not drunk and focused he is a remarkably good driver. On the other hand, if you just need to capture the edge cases data and add it to your training set to solve it, you can capture all the possible driving conditions that come up on road. This reminds of how there were hundreds of failure modes and jailbreaks for ChatGPT early on while now there are close to None, presumably because they just added them to the training set. If a good human level self driving car appears, I’m convinced it will be an end to end approach, whether the Tesla team are capable of this, who knows.

Also for those who think, OpenAI’s scale based approach only works for language, I have access to ChatGPT Vision and its capabilities astound me. Scale for sure works
I was curious about Bolyai's appendix itself and was intrigued to see it was originally in Latin (https://www.unesco.org/en/memory-world/janos-bolyai-appendix...). I'm not a math expert by any stretch (nor a historian of math) but I had thought that German had become the lingua franca of mathematics by that point. Does anyone know if Latin was still the default for math in 1832?
What framework would you recommend instead?

Just curious.
Yes, they're often impassioned when they're deadly serious, emphasis on the deadly, about the impact of the weather. They generally write with more humanity than might be expected of any other service — but they also so often bear awful news that is so often summarily ignored, that I can't fault them for their impassioned pleas to 'please, pay attention to us, it will prevent your avoidable deaths'.
Dupe: https://news.ycombinator.com/item?id=38002305
My area dropped for 3 days due to a stiff breeze with 20mph gusts.
oh what machine? with how many workers? doing what?

search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21
Hmm maybe, cause working out sure didn't work AT ALL for me, if anything it made things worse "another hope fades away".
This paper is about training the diffusion models on progressively higher resolutions, spending comparatively more iterations on smaller resolutions (which use much less time and memory per iteration). Their method is flexible enough for any multidimensional problem which is amenable to similar scaling (the use the example of generating video, which includes the additional dimension of time).

The models converge much more quickly during training by using this multi-resolution paradigm. There's a figure (4) in their paper showing how quickly these models converge to a good accuracy on a standard training set at 256x256 resolution, comparing them in particular to a Latent Diffusion implementation.

They showed that their baseline models were slightly better than Latent diffusion in terms of training efficiency. However, when they pretrained their models on 64x64, they converged much much faster. The Apple models converged at around 60k iterations to a better score than where Latent Diffusion arrived at in around 300k iterations.

The caveat is that for my example above, they pretrained the model for 390k iterations on 64x64 before setting it to train at 256x256, which is indeed more than Latent diffusion got the opportunity to train for - however, those 390k iterations were using something proportional to 16 times less resources.

This would be a very good paper for our friends creating Stable Diffusion to copy when creating the next versions, it would likely save them a lot of GPU time and I bet it would improve robustness for different dimension output.
Have they considered making Edge run faster than a drugged slug?
They look smaller than a lot of the suvs I see in the city while living here.
How Big Data Can Help You Make Sense of Social Media