MurphyA/hacker-news huggingface dataset:
by delusional | 2025-09-06 14:17:46+00:00
> The Twitter files [0] were front page material for a few weeks

You're again making vague gesturing towards "coordination" and "regular meetings" in service of justifying claims of "a pocket of authoritarians settled in the US intelligence services". You must know that "regular meetings" don't signal "packet of authoritarians" to anybody but the most diehard conspiracy theorists. Who were these authoritarians? what were they doing? and how were they doing it? The "Twitter Files" holds none of these answers, having been widely reported (according to the Wikipedia page you linked) as being a misrepresentation of normal communication between governmental entities and private companies.

> Again, you seem to be reading more than I'm writing with this one.

I disagree that I'm making any assumption outside of what you've written there, but I'll leave it there.

> I mean, if we're talking about the ~100 people who turned up armed

You're not answering the question. From your tone I can tell your answer is most likely that you don't consider the armed insurrection of the US capitol building connected to Donald Trump. What caused it then? Does Trump have any culpability for letting armed people take part of his march?
by FusionX | 2025-09-06 14:18:02+00:00
They partly address this near the end

> It’s doubly hard to distinguish valid statements from invalid ones when you don’t have any examples labeled as invalid. But even with labels, some errors are inevitable. To see why, consider a simpler analogy. In image recognition, if millions of cat and dog photos are labeled as “cat” or “dog,” algorithms can learn to classify them reliably. But imagine instead labeling each pet photo by the pet’s birthday. Since birthdays are essentially random, this task would always produce errors, no matter how advanced the algorithm.

> The same principle applies in pretraining. Spelling and parentheses follow consistent patterns, so errors there disappear with scale. But arbitrary low-frequency facts, like a pet’s birthday, cannot be predicted from patterns alone and hence lead to hallucinations. Our analysis explains which kinds of hallucinations should arise from next-word prediction. Ideally, further stages after pretraining should remove them, but this is not fully successful for reasons described in the previous section.
by twelvedogs | 2025-09-06 14:18:24+00:00
> Is the reproducibility of docker really worth the added overhead of managing containers, docker compose, and running daemons on your devbox 24/7?

Why wouldn't it be, containers are super easy to manage, dockerd uses bugger all resources in dev (on Linux anyway) and docker compose files are the simplest setup scripts I've ever used

I like docker because it's easy and I'm lazy
by b112 | 2025-09-06 14:18:50+00:00
Yes, that can happen. Then another city council gets in, and wants more parking.

The post I replied to said "The whole point of charging for parking" was to force people to, essentially, drive less. This is saying it's the only reason people charge for parking. Clearly not so.

And there is artificial scarcity too. I've seen cities where one company owned almost all the parking lots. In that situation, they controlled pricing entirely.

I've seen a lot more of "doing it for profit", including the city doing it for profit, than for environmental reasons.

That's doesn't mean I support this position or not. Describing reality as it stands is important, one cannot effect change one way or the other, without understanding what is.
Show HN: Gofred – Build responsive web apps in Go with WebAssembly
by gursoyhas | 2025-09-06 14:18:56+00:00
I've been working on a new approach to web development that lets you build responsive web applications entirely in Go using WebAssembly. I'm excited to share the gofred ecosystem with the community, though I should mention it's still very much in early development with lots of work ahead.

What is gofred?

Gofred is a Go library that compiles to WebAssembly and runs directly in the browser. Instead of writing JavaScript, you write pure Go code and get a small set of primitives for layout, components, routing, and events.

Key features:

WASM-first: Compile Go to WebAssembly and run directly in the browser

Composable widgets: container, row, column, text, image, button, and more

Routing and navigation: Lightweight router and navigation helpers

Responsive layout: Breakpoints and spacing utilities

Hot reload development: Built-in dev server with WebSocket support

Links:

https://gofred.io/ - Official website, live documentation and examples

https://github.com/gofred-io/gofred - The core library (MIT licensed)

https://github.com/gofred-io/gofred-cli - Command-line tool for creating and running apps with hot reload

https://github.com/gofred-io/gofred-website - Website source code

Why I built this:

I wanted to explore what's possible when you treat Go as a first-class language for web development. The result is a small, focused library that gives you the power of Go's type system and tooling while running in the browser.

Current status:

- Core library is stable and MIT licensed

- CLI tool supports cross-platform builds (Windows, macOS, Linux) - Hot reload development server

- Comprehensive documentation - Still under heavy development - there's a lot to do and many features are planned

What's coming:

This is very much a work in progress. I'm actively working on expanding the widget library, improving performance, adding more layout primitives, and building out the developer experience. There's still a lot of work to be done, but I wanted to share the current state and get feedback from the community.

I'd love to hear your thoughts and feedback! What do you think about using Go for frontend development?
by onlyrealcuzzo | 2025-09-06 14:18:58+00:00
That's likely closer to reality now, but that's not counting the cost for R&D to add it to the car, any additional costs that come with it besides the LIDAR hardware, plus the added cost to install it.

All of that combined is probably closer to $1k than to $140.

And, again, that's - what - 10 years after Tesla originally made the decision to go vision only.

It wasn't a terrible idea at the time, but they should've pivoted at some point.

They could've had a massive lead in data if they pivoted as late as 3 years ago, when the total cost would probably be under $2.5k, and that could've led to a positive feedback loop, cause they'd probably have a system better than Waymo by now.

Instead, they've got a pile of garbage, and no path to improve it substantially.
by benreesman | 2025-09-06 14:18:59+00:00
Nah, their people are way involved in mdarray and ROCm is looking to have the "oh no its broken again" bit flipped off in the RDNA 4/5 cycle.

NVIDIA wants Python and C++ people, they want a new thing to moat up on, and they know it has to be legitimately good to defy economic gravity on chips a lot of companies can design and fan now.
by foogazi | 2025-09-06 14:19:42+00:00
Your comment presented the options as killing people at sea or doing nothing, when there are a range of more effective and lawful options

1. Negotiate with Venezuela to reduce drug exports

2. Increase drug interdiction efforts with other Caribbean nations

3. Prosecute the sale and distribution of illegal drugs in the US

4. Invest in treatment & rehab options for drug addiction in the US

All of those take time and don’t show up on TV but are effective options
by orlp | 2025-09-06 14:19:59+00:00
As I mentioned in my other comment:

> I'd just like to clarify that I'm not saying this is necessarily the solution the problem writers were looking for, or that it will run within the allocated time. Just that it's a feasible solution.

I don't doubt there's a clever dedicated flow algorithm the problem writers intended instead of the blunt tool which is LP.
by boomlinde | 2025-09-06 14:20:09+00:00
I don't agree with the framing of it as "faking" a higher than native resolution. The native resolution is what it is. The problem lies in how the view is sampled as it is rendered to the screen. What you ideally do when you have higher frequency content than the screen can represent is to oversample, filter and downsample the view, as in SSAA, or you approximate the effect or use it selectively when there is high frequency content, using some more clever methods.

It's really the same problem as in synthesizing audio. 44.1 kHz is adequate for most audio purposes, but if you are generating sounds with content past the nyquist frequency it's going to alias and fold back in undesirable ways, causing distortion in the audible content. So you multisample, filter to remove the high frequency content and downsample in order to antialias (which would be roughly equivalent to SSAA) or you build the audio from band limited impulses or steps.
by rickytheguy | 2025-09-06 14:20:16+00:00
I've been wondering for a long time about adding a layer of UV reflective material to a license plate (maybe even a spray?), built specifically to either alter the image so a camera sees different numbers/letters, or to block it altogether. With this it wouldn't be obstructing the licence plate at all for human eyes, so it's feasible that you could easily get away with it.
by signatoremo | 2025-09-06 14:20:20+00:00
Sports have been the ways of life for many many people since forever. People identify themselves with, and bond via the sport teams they support. Are you saying that isn't enormous? Kids playing sport because they look up to their icons. That's hugely positive. There are pros and cons of everything, but to say sports have no benefit to the society is very shallow.

WW2 had profound and positive impact in the society. It reshaped the geopolitical picture, just to name one. Many previous colonies became independence after WW2, countries like India, China, Vietnam, or Indonesia. Wars are brutal, but wars can have positive impact.
by fumeux_fume | 2025-09-06 14:20:33+00:00
> Hallucination is all an LLM does.

I wish people who take this stance would seriously reconsider their take on how hallucinations are defined and how unhelpful it is to conflate hallucination with generation from a probability distribution. I appreciate OpenAI publishing articles like this because, while the parent comment and I may have to agree to disagree on how hallucinations are defined, I can at least appeal to OpenAI's authority to say that such arguments are not only unhelpful, but also unsound.
by ACCount37 | 2025-09-06 14:20:45+00:00
This mostly just restates what was already well known in the industry.

Still quite useful, because, looking at the comments right now: holy shit is the "out of industry knowledge" on the topic bad! Good to have something to bring people up to speed!

Good to see OpenAI's call for better performance evals - ones that penalize being confidently incorrect at least somewhat.

Most current evals are "all of nothing", and the incentive structure favors LLMs that straight up guess. Future evals better include a "I don't know" opt-out, and a penalty for being wrong. If you want to evaluate accuracy in "fuck it send it full guess mode", there might be a separate testing regime for that, but it should NOT be the accepted default.
by simne | 2025-09-06 14:21:30+00:00
I don't know such way now.

From what I see, looking promising, to discontinue UNIX systems (based on C, and yes, Windows is also favor of UNIX, as NT was made directly on foundations of VMS from Digital), and switch to something more high-level, like OpenStep (with high usage of SmallTalk), or at least BeOS (based on C++).

Sure, would be better to use Prolog based OS, when one will appear, or may somebody will create OS based on OcaML (Haskell, Rust).

What I see problem for gamedev, in many cases they need very high performance, and when nearly all target (current) OSs are just C-machines, it is very much like discover epic huge wall, when need to switch from OcaML level to C to get additional few FPS.

So most people choose easy way, they learn just primitive subset of C++ and work with it.

https://en.wikipedia.org/wiki/Comparison_of_operating_system...
by AbrahamParangi | 2025-09-06 14:21:52+00:00
I use self-driving every single day in Boston and I haven’t needed to intervene in about 8 months. Most interventions are due to me wanting to go a different route.

Based on the rate of progress alone I would expect functional vision-only self-driving to be very close. I expect people will continue to say LIDAR is required right up until the moment that Tesla is shipping level 4/5 self-driving.
by tossandthrow | 2025-09-06 14:21:59+00:00
Infrastructure was an example of a common good that rich and poor people use alike - not something that necessarily is fixed with equality.

Thinking about taxes in terms of producing revenue completely misses the point. Taxes in this context is a tool for increasing equality.

As for the ceo killings, if not the US increases equality, we will likely only see more of that behavior going forward.
by hedora | 2025-09-06 14:22:02+00:00
I haven’t had the alignment problem and our roads are probably worse than yours. Potholes, gravel, dirt, mountain switchbacks, etc.

I found that America’s Tires charges $200 less per set than the dealership, but I get steering wheel vibration at around 75-80mph. With dealership install, there’s no vibration up till the electronic limiter hits at 93mph. I’m not sure if handling the same and sounding the same at 65 and 93 mph is a feature or a bug though. :-)

This is the only car that they couldn’t align + balance prop Our local mechanic gets the balance to work up to about 85mph. Maybe have the dealership fix the alignment?

We know some people with an old leaf. On certain points in their commute the ADAS emergency brakes every single day. It’s particularly bad if someone is tailgating them as they approach that spot, though it can’t be good for the tires either.

Used i3’s are going for way under $17K these days, fwiw. I was actually shopping for a used leaf, and ended up with an i3.
by hodgehog11 | 2025-09-06 14:22:24+00:00
I don't know what you mean by hallucination here; are you saying that any statistical output is "hallucination"? If so, then we are also constantly hallucinating I guess.

There doesn't seem to be a particularly consistent definition of what "hallucinate" means in the context of LLMs, so let's make one that is in line with the post.

"Hallucination" is when a language model outputs a sequence of tokens comprising a statement (an assertion that is either true or false) that is incorrect. Under this definition, hallucination is clearly not all that an LLM can do.

An easy way to avoid hallucination under this definition is to respond with something that is never a statement when there is a possibility that it can be incorrect; e.g. "I think that... I don't know...". To me, this seems to be what the authors argue. This has always seemed pretty obvious to most people I've spoken to (hell, I've reviewed grant applications from years ago which talk about this), so I'm not sure why it took so long for the "frontier" developers to actually try this.
by stego-tech | 2025-09-06 14:22:25+00:00
They’re removed from the realities of the working class. They have staff, live in a separate bubble from their workers with different social circles, different services, different mores and norms.

Executives make shitty decisions because they surround themselves with others who view wealth as a leaderboard to be climbed and flaunted, and have no fucking clue how difficult things are for the people doing the actual work creating products/services/value to the company. For those who claim to relate to the plight of the worker, their frame of mind is stuck in that precise moment just before they became fabulously wealthy, when they were likely busting ass - hence the “hard work pays off”/bootstrap mythos they peddle.

The few executives that do understand these plights, don’t make such shitty decisions, and are either roundly mocked for their lack of growth by those whose wealth was built atop the literal corpses of their workers, or occasionally featured in human interest pieces as an executive that’s strangely generous.
by boomlinde | 2025-09-06 14:23:16+00:00
> You mean back in the day when 30 fps at 1024x768 was the norm?

I recall playing games at 100 FPS on my 100 Hz CRT. People seriously interested in multiplayer shooters at the time turned vsync off and aimed for even higher frame rates. It was with this in mind I was quick to upgrade to a 144 Hz display when they got cheap enough: I was taking back territory from when the relatively awful (but much more convenient) flat screens took over.

> because the other player undoubtedly had a 240hz 4K monitor rendering the player coming around the corner a tick faster.

I play 99% single player games and in most of those, response time differences at that scale seem inconsequential. The important difference to me is in motion clarity. It's much easier to track moving objects and anticipate where they will be when you get more frames of animation along their path. This makes fast-paced games much more fun to play, especially first person games where you're always rapidly shifting your view around.
by zahlman | 2025-09-06 14:23:33+00:00
It's still honestly amazing to me that people buy, or want, devices like this, even before considering the downsides. I mean, I don't even like leaving voicemail messages. So the idea of talking to nobody in particular, within my own home, to cause something to happen, totally freaks me out. I really don't need more excuses for physical laziness, either.
by chubot | 2025-09-06 14:23:33+00:00
OK, but I think it will end up being more than 25 years behind schedule, taking into account the claims

which is what people like Chris Urmson and Bill Gurley already said prior to 2018 (see my sibling comment)

https://en.wikipedia.org/wiki/List_of_predictions_for_autono...

We're going to end up with complete autonomy

Ultimately you'll be able to summon your car anywhere … your car can get to you. I think that within two years, you'll be able to summon your car from across the country

---

(Also, in 2018 I said I'd be the first to buy a car where I could sleep behind the wheel while going from SF to Portland or LA. That obviously doesn't exist now.

Anyone want to take a bet on whether this will be possible in 2032, 7 years from now? I'd bet NO, but we can check in 2032 :-) )
by 1oooqooq | 2025-09-06 14:24:31+00:00
github because the project is open source (would get close to gh with proprietary information!), we mirror there to run build and tests on their money.

ts because we made the mistake of assuming it would be good a while ago and regret it every single day. but its still the least worse if you have to ship js to the browser.

that's about it.
by daveguy | 2025-09-06 14:24:32+00:00
The "lidar is a crutch" excuse is such a fraud. Musk is doing it so he can make more money, because it's cheaper. Thats it. Just another sociopath billionaire cutting corners at the expense of safety.

The reason this is clear is because, except for a brief period in late 2022, Teslas have included some combination of radar and ultrasonic sensors. [0]

[0] https://en.m.wikipedia.org/wiki/Tesla_Autopilot_hardware
by ben_w | 2025-09-06 14:24:57+00:00
Many accidents are caused by low-angle light dazzle. It's part if why high beams aren't meant to be used off a dual carriageway.

When was the last time you saw a paper bag blown across the street and mistook it for a cat or a fox? (Did you even notice your mistake, or do you still think it was an animal?)

Do you naturally drive faster on wide streets, slower on narrow streets, because the distance to the side of the road changes your subconcious feeling of how fast you're going? Do you even know, or are you limited to your memories rather than a dashcam whose footage can be reviewed later?

etc.

Now don't get me wrong, AI today is, I think, worse than humans at safe driving; but I'm not sure how much of that is that AI is more hallucinate-y than us vs. how much of it is that human vision system failures are a thing we compensate for (or even actively make use of) in the design of our roads, and the AI just makes different mistakes.
by weitendorf | 2025-09-06 14:25:01+00:00
I don’t think that argument really works in situations like this because hacking Burger King requires a pretty high level of intent + ability and isn’t something that just naturally happens. Like you have to sit down and say “Today I want to try to hack Burger King” and then spend several hours doing just that.

To me it seems like quite a stretch for “don’t hack me” to get framed as “Burger King is leveraging their corporate power to tell me what to do against my will”.

And to be clear I actually do think that it would be better for Burger King to invite and reward responsible disclosure, in the same way that you’d want your bank to have a hotline for people to report problems like doors that won’t lock. But if the bank didn’t have that hotline it wouldn’t excuse breaking in.
by CuriouslyC | 2025-09-06 14:25:11+00:00
A deep plan cycle will find stuff like this, because it's looking at the whole relevant portion of your codebase at once (and optionally the web, your internal docs, etc). It'll just generate a very short plan for the agent.

The important thing is that this process is entirely autonomous. You create an issue, that hooks the planners, the completion of a plan artifact hooks a test implementer, the completion of tests hooks the code implementer(s, with cheaper models generating multiple solutions and taking the best diff works well), the completion of a solution + PR hooks code+security review, test red teaming, etc.
by briandw | 2025-09-06 14:25:11+00:00
Lidar is the first thing brought up in these discussions. Lidar isn’t that great of a sensor. It does one thing well and that’s measure distance. A visual sensor can be measured along the axis of spatial resolution (x,y,z) temporal resolution(fps) and dynamic range(bit depth). You could add things like light frequency and phase etc. Lidar is quite poor in all of these except the spatial z dimension, measuring distance as mentioned before. Compared to a cheep camera the fps is very low, the spatial resolution in x and y is pathetic 128. in the vertical, higher horizontal but its not mega pixels. Finally the dynamic range is 1 bit(something is there or not). Lidars use near infrared and are just as susceptible to problems with natural fog (not the theatrical fog like in that Roper video) and rain. Multiple cameras can do good enough depth estimation with modern neural networks. But cameras are vastly better at making sense of the world. You can’t read a sign with lidar.
by jaybrendansmith | 2025-09-06 14:25:27+00:00
This is a bit better. You are saying it IS happening, but just not gonna be that bad. I sure hope that's correct, but don't you think 1000s of climate scientists have taken this simple fact as a consideration in their analysis? Even if the effect is logarithmic, we are now at 420 CO2, well above preindustrial 280. We’ve already added 1.2 degrees of global warming. Continuing on the current trajectory will push us to 560 or higher within this century for multiple additional degrees C of warming. The fact that each extra ppm does a bit less does not mean the danger goes away, it means you need bigger increments of CO2 to get the same forcing, and presently we are adding those big increments very quickly. Climate scientists already use the logarithmic law of CO2 and the forcing geometry in all their calculations.