MurphyA/hacker-news huggingface dataset:
by chrisshroba | 2025-08-22 17:52:02+00:00
This always astounds me about cities who have a reputation for people breaking certain traffic laws. In St. Louis, people run red lights for 5+ seconds after it turns red, and no one seems to care to solve it, but if they'd just station police at some worst-offender lights for a couple months to write tickets, people would catch on pretty quickly that it's not worth the risk. I have similar thoughts on people using their phones at red lights and people running stop signs.
by tracker1 | 2025-08-22 17:52:15+00:00
I was thinking about this.. if you look at (I think OpenAI) the scene generation and interaction demos, it's a pretty natural fit for their VR efforts. Not that I'm sold on VR social networks, but definitely room for VR/AR enhancements... and even then AI has a lot of opportunities, beyond just LLM integration into FB/Groups.

Aside, groups is about the only halfway decent feature in FB, and they seem to be trying to make it worse. The old chat integration was great, then they remove it, and now you get these invasive messenger rooms instead.
by SkyPuncher | 2025-08-22 17:52:24+00:00
I'm intrigued by this as it's a problem we're facing. However, I don't really understand pricing in the context of targeting multi-tenant SaaS companies.

> 3+ agents ($25 per agent/mo thereafter)

What is an agent? Specifically, how are these counted?

> 25+ active tables ($5 per table/mo thereafter)

This is clear and concise, but just doesn't resonate with me as a good lever for pricing. I'm just going to our our data team run a transformation to consolidate tables.

Number of rows/colummns ingested feels a lot more natural to me

> 15+ seats ($10 per user/mo thereafter)

How is a seat defined in the context of multi-tenant Saas?

Let's say company A has 200 employees in our system, but only 5 of them interact with the agent monthly. Are we billed:

* 1 seat - company A

* 200 seats - each employee of Company A

* 5 seats - only the users that interacted with the agent.
by rrrrrrrrrrrryan | 2025-08-22 17:52:35+00:00
People grow almonds in the desert specifically because they have access to artificially cheap water. In the U.S. lots of land comes with water rights: e.g. if a river or creek passes through your land you can use x% of the water to irregate your crops. Some of these water rights date back to the 1800s and they're locked in.

The water rights can be clawed back a couple ways: if they're unused for X years, or in times of drought.

There's an exception for droughts though: farmers with trees (that would die if unwatered) still get priority, while people that grow crops that replenish each season (like wheat) don't.

So this leads to perverse incentives where these farmers need to find a way to use ALL of their water, every year, or they'll lose access to their absurd water rights from the 1800s, and they need to use it on trees so it doesn't get clawed back during a multi year drought.

So, they end up planting the most water-hungry trees they can grow on their land (almonds), then they get to sell them to the world at artificially low prices because the water that was used to grow them is almost free.
by masklinn | 2025-08-22 17:52:40+00:00
The billion dollar mistake was made in 1965 but the term was coined in 2009, defined as the following:

> I couldn't resist the temptation to put in a null reference, simply because it was so easy to implement. This has led to innumerable errors, vulnerabilities, and system crashes, which have probably caused a billion dollars of pain and damage in the last forty years.
by scoofy | 2025-08-22 17:52:59+00:00
A really interesting essay. I'm genuinely surprised the author didn't delve more into philosophy here. I think the biggest issue this essay illustrates is the inductive-deductive jump that modeling (especially mathematical modeling makes). That is, if the axioms we are using are correct, then the output of the model should reflect reality. This is very obviously not always the case, and because of the black swan problem (in a very real sense) we can never really know if it does.

Any time we wade into solipsism, however, I think it's important to remember that statistical analysis is a tool, not an arbiter of Truth. We are trying to exist in the mess of a world we live in, and we're going to be using every possible advanced tool we have in our arsenal to do that, and the standard model of science is probably the best tool we have. At the same time, we should often return to that solipsism an remember that where we can improve the model, we should.
by Arnavion | 2025-08-22 17:53:08+00:00
The ext_data_control_v1 protocol I mentioned is a protocol specifically for clipboard managers. So a client that wants to be a clipboard manager would implement that protocol. There are already implementations of it like wl-clipboard. There is no need for the compositor to broadcast regular clipboard events (wl_data_offer).

Now the compositor could certainly keep an additional list of trusted applications that are allowed to be clients of the ext_data_control_v1 protocol. Though identifying the client to enforce such a thing is a bigger problem than just maintaining a list of applications, because the protocol has no client identification. AFAIK every compositor that supports that protocol has no restrictions on clients requesting it, though something involving the security-context protocol might change this in the future.
by yencabulator | 2025-08-22 17:53:30+00:00
Ehh Zed tried to push the collaborative editing before the AI hype was thing (that blog post is from 2022), and seemingly everyone outside of Zed developers promptly ignored the idea.

The Zed developers quickly refocused on milking the AI cow.

I'll argue git is plenty good, and there are a lot of people who don't understand it very well. The ones talking about Github PRs as if they were related to Git in any way most definitely don't.
by const_cast | 2025-08-22 17:53:42+00:00
To an extent, but it's also priming, ie lying with statistics.

Obviously if you tell people you're doing something to protect children and that's its only for porn or whatever they'll say yes. You've primed them - you immediately put their minds on the focus of negative things like porn and children getting hurt. Nobody wants children hurt.

You need to ask the question more generically. "Do you support age verification to access certain categories of websites?"

Something tells me the numbers of agreeance will fall.
by bsimpson | 2025-08-22 17:53:56+00:00
They're already learning how to handle this in SF. (I don't live there anymore, so I can't give specific examples.)

Waymo markets itself as an automated driver - same reason they're using off-the-shelf cars and not the cartoony concepts they originally showed. Like real drivers, they take the law as guidelines more than rules.

De jure (what the law says) and de facto (what a cop enforces) rules have had a gap between them for decades. It's built into the system - police judgement is supposed to be an exhaust valve. As a civil libertarian, it's maddening in both directions:

- It's not just that we have a system where it's expected that everyone goes 15mph faster than posted, because it gives police an avenue to harass anyone simply for behaving as expected, and

- It's also dystopian to see police judgement be replaced with automated enforcement. There are whole classes of things that shouldn't be penalized that are technically illegal, and we've historically relied on police to be reasonable about what they enforce. Is it anybody's business if you're speeding where there's nobody to harm? Maybe encoding "judgment" into rules will be more fair in the long run, but it is also coaching new generations to expect there to be more rules and more enforcement. Feels like a ratchet where things that weren't meant to be penalized are becoming so over time, as more rules beget more automated, pedantic enforcement.

A slight digression, and clearly one I have a lot of thoughts on.

It's really interesting to see how automation is handling the other side of this - how you build machines to follow laws that aren't enforced at face value. They can't program them to behave like actual robots - going 24 mph, stopping exactly 12" before the stop line, waiting until there are no pedestrians anywhere before moving. Humans won't know how to interact with them (cause they're missing all the nonverbal communication that happens on the road), and those who understand their limits will take advantage of them in the ways you've stated.

So Waymo is programming a driver, trying to encode the behaviors and nonverbal communication that a human learns by participating in the road system. That means they have to program robots that go a bit over the speed limit, creep into the intersection before the turn is all the way clear, defend against being cut off, etc. In other words, they're building machines that follow the de facto rules of the road, which mean they may need to be ready to break the de jure laws like everyone else does.
by justsomehnguy | 2025-08-22 17:54:19+00:00
Depends on the usage and the initial claimed DWPD.

I've seen Samsung 860 Pro (DWPD of 0.6) doing fine after years under LUKS (the worst case for SSD). As soon as you go for DWPD > 1 (real or effective) the wearout is not a problem.
by leptons | 2025-08-22 17:54:34+00:00
Is this a 1-person dev team? Because on teams, one person has to submit a PR and then someone else on the team has to code review it, right? So then you're doubling the review time of the code. If you wrote the code yourself, you would already know that it works, then you submit the PR, and then someone else reviews the code one time, not twice. And typically reading and understanding code you did not write takes longer than writing the code yourself. It does not seem like "AI" coding is really saving anyone any time, and is probably wasting more time than it saves.
by the-rc | 2025-08-22 17:54:35+00:00
I think the problem in NYC will be getting medallions, assuming that's what self driving cars will need.

There are already so many (too many?) taxis and car sharing drivers, after TLC's massive increases of the last few years. You can play a game, based on something I read about last year: stand at a corner and count all cars/trucks/for-hire. The first two combined are barely outnumbered by the last group. And the few times I checked, half of taxis and car sharing vehicles were empty. (Of course that's different at peak times or when it rains.)

Will Waymo be allowed to add as many vehicles as they want, like a new class of cars, or will they need to buy out medallions from drivers? The former might undo all the progress in traffic relief that was brought by congestion pricing.
by alfalfasprout | 2025-08-22 17:55:04+00:00
> generic advice about how you should use the same tool and methodology (claude code, scrum) that everyone’s already using, lot of hand waving about being “senior,” This may be the most 2025 blog post ever written.

This part tracks. It's honestly rather generic.

> if anyone takes the art of software programming further using LLMs, it’s going to be young inexperienced people who grow up closely observing and learning the transcendental nature of LLMs and software, not hardened industry titans joyfully cracking their whip over an army of junior devs and LLMs.

This, I'm not sure applies either. TBH the biggest risk I'm seeing already right now is how quickly we're starting to see juniors trying to enter the job market who don't have the faintest idea how actually code. Let alone build software (but let's be honest, that's usually been the case). What decisions to make when writing something are based on factors outside just implementing the functionality: how maintainable is this? how extensible?

Giving a junior a sycophant that's reasonably competent at spitting out something functional (not necessarily functional in the sense you need it to be but apparently working) is a recipe for disaster IMO.

There will absolutely be some who "get it". But, how does that scale?

More worryingly, something I don't see discussed enough is "review fatigue". It's far more fatiguing reviewing the output of an LLM than writing the code yourself a lot of the times. Early on in your career, this might lead to the tendency to just say "eh, looks alright enough".
by wcunning | 2025-08-22 17:55:11+00:00
Student housing near the engineering campus at University of Michigan is about 1/2 mile away from the reasonably close Kroger grocery store. When I started there in 2009, the carts didn't have the locking wheels and many people would take the cart all the way back to their apartment complex -- this meant that the Kroger store manager had to rent a moving van every so often and go collect them all as the carts cost $500~1000 new, so replacing them when they're 1/2 mile to a mile away wasn't good economics. Eventually this got so bad (never a cart at the store when you wanted one, had to go get them all the time) that they switched to the geolocking wheels, which was a pain because the geolock frequently false detected if you were at the back of the annoyingly small parking lot, so there were always carts stuck in the back ~20 spots.

Later, my girlfriend told me that the specialty foreign foods store near the Big Lots she worked at in a different Detroit suburb would intentionally come steal the Big Lots carts, rather than pay for their own (see above, expensive), so the Big Lots clerks would occasionally get sent on a mission with a moving van to get a bunch of their carts from the next shopping center over's parking lot. I think they might not have ever paid for the geolocking wheels, since Big Lots is low margin and those options are pretty expensive, but you can see the incentive to do so.
by novok | 2025-08-22 17:55:25+00:00
Any large codebase has a large ramp up time by virtue of being large. And the large codebase can have devex automation to get past the initial ceremony setup of larger languages like Java. It feels like the wrong thing to optimize for. As a better alternative to small services that would've been made in python or node, yes for sure, then the quick setup and simplicity of go makes sense. Which is why the biggest audience of people who use go and used another language previously is python engineers and people who want to make small network services.

At the larger codebase go company I worked at, the general conclusion was: Go is a worse Java. The company should've just used Java in the end.
by bootsmann | 2025-08-22 17:55:30+00:00
Maybe as a small anecdote: I had a coworker ask an AI to write them a function to auth to aws using boto3 and environment variables. The LLM happily complied and gave them a 30 line snippet but it failed to point out that if they were to open boto3 docs it would tell them that it will already default to environment variables when it has no credentials and the whole function is just reinventing the wheel.

If you’re throwing the LLM at APIs you don’t know, how could you possibly verify it is using them properly?
by jjice | 2025-08-22 17:55:31+00:00
NYC (at least the parts I've spent a bit of time in) is pretty grid like with fairly simple roads. The drivers are the hard part :)

I am excited to see them tackle Boston at some point because of how strange some of those roads are. The first time I had ever been I came to an intersection that was all one ways and there were like 7 entry/exit points. My GPS said turn left, but there were three paths I'd consider left. Thank god I was walking.

And I don't really pose much doubt because it seems like Waymo's rollout plan has been solid, but I'm just interested to see how well they tackle different cities.
by nostrademons | 2025-08-22 17:55:40+00:00
"Land communism" isn't a bad way to put it.

But I think you need to make a pretty clear distinction between "land" communism and, well, communism. Communism is based on public ownership of the means of production: if you own a steel factory, you don't really "own" a steel factory, the people own the factory and the state appoints a bureaucrat or manager to run it. You can receive no profit from it, you can't sell it, really you have no rights to it other than the state's promise to let you manage it (and whatever they pay you for that).

Georgism explicitly still admits private property: if you own a steel factory, you actually do own a steel factory, you can make decisions about the management of that factory, you can sell it, etc. In many ways it's more capitalist than today's capitalism, because single-tax Georgism also states that there should be no income or capital gains tax, and so you receive 100% of the profits from building that factory. You just have to pay a tax to the state for the land that the factory sits on, set in proportion to what others would be willing to rent the land for.

The distinction is pretty key, because it gets at the heart of human agency and incentives. Georgism does not admit private ownership of the land because the land was here before any humans were; no human suddenly built the land, and no human can destroy it, they can only manage its use. Likewise for other common goods (like pollution, the electromagnetic spectrum, natural resources, etc.) which Georgism seeks to manage. Georgism does admit private property, because when you construct a machine or a factory or invent a new process, that came out of your own efforts. It could be summed up as "private persons own what they build or buy, the public owns what was here before".
by abdullahkhalids | 2025-08-22 17:56:10+00:00
Any digital platform (like social media or a marketplace), which satisfies the following conditions

- decides which wares (social media posts or products) by sellers are shown to users by automated algorithms

- Makes money when users engage with said wares

- Is owned by a large number of investors

Will, if you believe standard optimization theory and that sellers are clever, devolve into crap.
by SirMaster | 2025-08-22 17:56:16+00:00
>I'll throw this out there: your human-driven car already accounts for acceleration and braking on slippery roads, without the need for the human. Traction control systems and electronic stability control systems exist! They're in fact incredibly common on modern cars.

These systems don't help with the problems I am talking about.

You have to drive completely differently in heavy snow, significantly slower, brake sooner, turn less sharp, accelerate much slower, leave significantly larger gaps, leave space to move out of the way and be ready to move if someone behind you is coming at you too fast and can't stop in time, etc. I've spend my entire life in the midwest.

The traction control system in my 2023 camry didn't help one bit when I applied the brakes on black ice and the car didn't react at all, it just kept sliding at the same speed across the ice.
by dang | 2025-08-22 17:56:21+00:00
The article's title was longer than 80 chars, which is HN's limit. There's more than one way to truncate it.

The previous truncation ("From GPT-4 to GPT-5: Measuring Progress in Medical Language Understanding") was baity in the sense that the word 'understanding' was provoking objections and taking us down a generic tangent about whether LLMs really understand anything or not. Since that wasn't about the specific work (and since generic tangents are basically always less interesting*), it was a good idea to find an alternate truncation.

So I took out the bit that was snagging people ("understanding") and instead swapped in "MedHELM". Whatever that is, it's clearly something in the medical domain and has no sharp edge of offtopicness. Seemed fine, and it stopped the generic tangent from spreading further.

* https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
by astrobe_ | 2025-08-22 17:56:34+00:00
"Isn't it just temporary, and AI will get better?"

There are 2 instances of the word "understand" in the first paragraph, 3 if you count the beginning of the second.

In my book, "understanding" is a synonym for "intelligence" - the roots of the word are "read between the lines", where something else that just knowledge is, the ability to use and manipulate knowledge [1].

But the thing is, despite this tech being classified as "artificial intelligence", it does not understand a thing - or so little.

So, if we extrapolate Betteridge's law of headlines, no it is not temporary for this type of technology. But I think connecting it with formal computations - inference engines for formal logic, calculators [2], etc. could be amazing.

[1] https://en.wiktionary.org/wiki/intelligence - well, yes, that's a bit cherry-picked.

[2] https://arxiv.org/abs/2406.03445 - amazing result, and maybe will find out that it is exactly what we do "under the skull", but doing arithmetic with Fourier transforms is not the best use of a microprocessor.
by jungyubl | 2025-08-22 17:56:36+00:00
Hey HN,

With all the recent layoffs, I've been thinking a lot about the human side of it all. Beyond the headlines and numbers, there are real people whose confidence and sense of direction just got shattered.

I went through this myself a while back. The gut reaction is to panic and start firing off resumes to anything that moves. The problem is, that often leads you right back into another job that isn't a great fit, and the cycle repeats. The real challenge, I think, is managing the emotional fallout so you can make a clear-headed decision about what's next.

I wanted to build something to help with that specific problem. It's a small web app called Deeper Lights: https://www.deeperlights.com

What it is: It’s not a job board or a resume builder. It's a structured space with guided journaling and small, daily exercises to help you process the anxiety, rebuild some confidence, and get clear on what you actually want before you start the next big job hunt. The goal is to help you pause and reflect, rather than just react.

I would love to get your honest feedback. I'm in the very early stages and know there's a ton to improve. Tearing it apart is welcome.

Specifically, I'm wondering:

Does the core idea resonate? Is this a problem you or people you know have faced?

Is the landing page clear? When you look at the site, do you immediately get what it's for?

What are your first impressions of the onboarding? Is it confusing? Is it too much to ask of someone who's already stressed?

Any obvious features missing? What would you expect from a tool like this?

I'm the founder and will be here all day to answer questions and listen. Thanks in advance.
by rbongers | 2025-08-22 17:56:42+00:00
>The discipline required to use AI tools responsibly is surprisingly difficult to maintain

I don't find that this requires discipline. AI code simply requires code review the same as anything else. I don't feel the need to let AI code in unchecked in the same way I don't feel the need to go to my pull request page one day and gleefully hit approve and merge on all of them without checking anything.