MurphyA/hacker-news huggingface dataset:
by seadan83 | 2025-06-05 21:44:06+00:00
Second angle:

> If your AI scaling statement is accurate then the problem will eventually solve itself as organizations that mandated AI usage will start to fall behind their non-AI mandating peers.

I find one of the biggest differences between junior engineers and seniors is they think differently about how complexity scales. Juniors don't think about it as much and do very well in small codebases where everything is quick. They do less well when the complexity grows and sometimes the codebase just simply falls over.

It's like billiards. A junior just tries to make the most straight forward shot and get a ball in the hole. A senior does the same, but they think about where they will leave the cue ball for the next shot, and they take the shot that leaves them in a good position to make the next one.

I don't see AI as being able to possess the skills that a senior would have to say "no, this previous pattern is no longer the way we to do things because it has stopped scaling well. We need to move all of these hardcoded values to database now and then approach the problem that way." AFAIK, AI is not capable of that at all, it's not capable of a key skill of a senior engineer. Thus, it can't build a system that scales well with respect to complexity because it is not forward thinking.

I'll posit as well that knowing how to change a system so that it scales better is an emergent property. It's impossible to do that architecture up front, therefore an AI must be able to say "gee, this is not going well anymore- we need to switch this up from hardcoded variables to a database - NOW; before we implement anything else." I don't know of any AI that is capable of that. I could agree that when that point is reached, and a human starts prompting on how to refactor the system (which is a sign the complexity was not managed well) - then it's possible to reduce the interest cost of outsized complexity by then using an AI to start managing the AI induced complexity...
by contextfree | 2025-06-05 21:44:30+00:00
I don't really know Java, but .flatMap(...) seems to be equivalent to C# .SelectMany(...) which famously can be interpreted as a monadic bind operator.

The C# query syntax

from x in xs from y in GetYs(x) from z in GetZs(y) ...

is equivalent to

xs.SelectMany(x => GetYs(x).SelectMany(y => GetZs(y).SelectMany(z => ...)))

which is similar to monadic do-notation in Haskell.

So since there is monadic Scala code elsewhere in the project, I wonder if this is a result of someone thinking in Scala and translating it into Java in their head.
by bsder | 2025-06-05 21:44:50+00:00
> An ancestor lost the trait for vitamin C synthesis by chance, and because these primates were living in trees eating lots of fruit with vitamin C, evolution simply didn't notice. There is no disadvantage to being able to synthesise vitamin C, and no advantage in dropping the trait.

The fact that guinea pigs, fruit bats, and passerines (almost half of all bird species!) also have a mutated GULO gene suggests that there is in fact some pressure to get rid of it as soon as it is bioavailable from diet.
by miki123211 | 2025-06-05 21:46:02+00:00
This will impact the blind community in a pretty serious way.

In countries where Android is popular and iPhones are expensive, Commentary (Jieshuo) screen reader is a popular and arguably much better alternative to TalkBack, the built-in Android screen reader. Because it's a Chinese app and there's no major conglomerate behind it, it's not on the Play Store.

Because it needs to be able to read all screen contents and drive the entire system UI (that's literally what a screen reader is for), the permissions it requests are quite intrusive. Blocking it from accessing sensitive apps would entirely defeat its purpose, after all, if you need a screen reader in the first place, one that doesn't work in banking apps will be pretty useless to you.

Googlers will probably point to Webaim[1] and say that nobody uses the app so it's not a problem, entirely forgetting that Webaim is mostly filled out by well-off English speakers. If you look at data sources that better represent the global population at large, like the Yandex user survey, you will see something very different.

[1] https://webaim.org/projects/screenreadersurvey10/
by coolKid721 | 2025-06-05 21:46:57+00:00
Yeah I hit it again today, refactoring can use a ton. It did make a bit of a mess but planning it out making sure everything is tested and having it run through checking the tests making sure they all still pass uses lots of tokens but passively doing that while I'm working is way faster than doing it manually.

Sometimes I'll just experiment with weird stuff and end up reverting it or delete it afterword's. Also fun to build really nice data visualizations for data I'm working with.
by tough | 2025-06-05 21:47:09+00:00
posthog is just one of many ways to record a user's session.

the problem is if you have the user running browser extensions which modify the client code from the users' POV. they are also now mangled and not in the standard expected format by those session recording utils.

tbh sounds like it would be a small enough number of users on a big pool it wouldn't matter much in real case scenarios to me
by joshuamarch | 2025-06-05 21:47:29+00:00
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We’re hiring a founding full-stack AI engineer to:

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You should be:

• An AI-native builder with deep experience using APIs like OpenAI, Claude, Whisper, etc.

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Ask HN: Is GPU nondeterminism bad for AI?
by ramity | 2025-06-05 21:47:52+00:00
Argument:

- GPUs use parallelism

- Floating point math is not associative

- Rounding error accumulates differently

- GPUs generate noisy computations

- Known noise vs accuracy tradeoff in data

- Noise requires overparameterization/larger network to generalize

- Overparameterization prevents the network from fully generalizing to the problem space

Therefore, GPU nondeterminism seems bad for AI. Where did I go wrong?

Questions:

- Has this been quantified? As I understand it, the answer would be situational and tied to other details like network depth, width, architecture, learning rate, etc. At the end of the day, entropy means some sort of noise/accuracy tradeoff, but are we talking magnitudes like 10%, 1%, 0.1%?

- Because of the noise/accuracy tradeoff, it seems to hold that one could use a smaller network trained deterministically and achieve the same performance as X bigger network trained non-deterministically. Is this true, even if we're talking only a single neuron of a difference?

- If something like the problem space of driving a car is too large to be fully represented into a dataset (consider the atoms of the universe as a hard drive), how can we be sure a dataset is a perfect sampling of the problem space?

- Wouldn't overparameterization guarantee the model learns the dataset and not the problem space? Is it incorrect to conceptualize this as using a polynomial of a higher degree to represent another?

- Even with perfect sampling, noisy computation seems incompatible when a small amount of noise is capable of causing an avalanche. If this noise is somehow quantified to 1%, couldn't you say the dataset's "impression" left in the network would be 1% larger than it should, maybe spilling over in a sense? Eval data points "very close to" but not included in training datapoints would be more likely to incorrectly evaluate to as the same "nearby" training datapoint. Maybe I'm reinventing edge case and overfitting here, but I don't think overfitting just spontaneously starts happening towards the end of training.
by anteloper | 2025-06-05 21:48:27+00:00
For retrieving Mac OS screen time programatically? Not that I'm aware of.

In any Apple device, In settings -> Screen Time there's an option for "share across devices". If that is turned on, all devices will report your cumulative totals. So if you're interested in retrieving your screen time from all your devices, you can turn that on and then your iPhone will report everything, which you could retrieve with this API. But you wouldn't be able to differentiate where the screen time came from.
by jsight | 2025-06-05 21:49:08+00:00
That is a fair point. I own a Y and have had both sides to this. Sometimes I carry very irregular cargo that fits perfectly and the space is really incredible.

Other times, I have something that should fit, but can't readily fit through the oddly shaped rear hatch and it becomes a problem.

I'd agree with you with regard to luggage. That's a scenario that really hits the strength of the Y setup, especially with the relatively large frunk. I often end up with a few backpack sized items up there on longer trips.
by neilv | 2025-06-05 21:49:34+00:00
Agreed. For me, the popularity of Markdown on (pre-Microsoft) GitHub and GitLab was all I needed, to declare that the company wiki, code-embedded API docs, and anything else appropriate should just use Markdown.

Markdown is good enough for most of the documentation that software engineers do (other than diagrams), they already have to know it, and I don't want yet-another-markup-language to be a barrier to capturing and communicating institutional knowledge.

I also tell people that, if you're new to Markdown, even a plain text approximation that doesn't quite format correctly is strongly encouraged, so long as they capture the info somewhere accessible. I'll even offer to cheerfully fix the missing/bad Markdown, so that we have working docs and people can learn the very few parts of Markdown they missed; it's really not much.

(I personally have heavily used many much-much better technical documentation systems, and helped develop a WYSIWYG-ish SGML-based one professionally, but just using Markdown is a no-brainer right now. There are much more important things I want people learning and doing, than N different ways of minimally formatting documentation in N different places.)
by bsder | 2025-06-05 21:49:43+00:00
Well, there is some "cause-and-effect" in evolution.

Whenever a species winds up isolated in a cave, it loses eyesight really quickly in evolutionary terms because making and maintaining an eye is so metabolically expensive. So, while the mutations are random, any of them that can save the energy of developing vision get selected for very quickly.

So, even though the mutations are random, it really looks like "cause-and-effect" from the outside: get isolated in cave->lose vision; get exposed to outside light again->regain vision.

By the same token, changes that aren't very expensive metabolically will have very weak "cause-and-effect" because there is no particular pressure to carry the mutations forward or clean them up.
by Merovius | 2025-06-05 21:50:46+00:00
> (that is the reason the people spend years to solve it)

I don't think anyone actually spend years trying to solve it. It's just that over the years, many people have tried to solve it - each for a grand total of maybe a week or so. If you look at the list, you'll see a lot of different proposal authors: https://seankhliao.com/blog/12020-11-23-go-error-handling-pr... Most of these do not post any other issues and many of those don't even respond in the discussion to their own proposals.

It's a thing that a lot of people coming to the language get frustrated by, think "here is an obvious way to make this better" and file a (usually half-baked) proposal about. It's not a thing that people spend years of focused effort on to polish into something that works.

Compare that to generics: Not only did Ian file a proposal about that roughly every year. The final design also had over a year of intense discussion, with at least a dozen or two consistent participants (and a hundred or so occasional ones). With at least three or four direct iterations.

Error handling is something that a lot of people care a little about.
by biomcgary | 2025-06-05 21:50:57+00:00
Cysteine plays a key role in redox metabolism and removing reactive oxygen species (ROS). During brown fat burning, high flux of electrons increases the NADH/NAD⁺ and FADH₂/FAD ratios — shifting redox state toward a more reduced environment, which is exactly what you would need if deprived of cysteine.
by tndl | 2025-06-05 21:51:53+00:00
Things are changing quickly in this area. Several projects/companies working on AI data assimilation (an alternative route to creating analysis data like ERA5)[0].

Also a lot of companies working on the data collection side, replacing/augmenting government data collection. Spire's an example of this in the space domain, and Windborne and Sorcerer (my company) do weather balloons.

[0]: E.g. Brightband's AIDA (https://www.brightband.com/blog/aida/) and Project Aardvark (https://www.turing.ac.uk/blog/project-aardvark-reimagining-a...)
by nobody9999 | 2025-06-05 21:52:26+00:00
>I'm of the opinion that AI is and will continue to be a net positive for society. So I see this as essentially saying "let's go an remove this and delay the development of it by 10-20 years and ensure people can't train and run their own models feasibly for a lot longer because only big companies can afford real training datasets."

Absolutely. Which, presumably, means that you're fine with the argument that your DNA (and that of each member of your family) could provide huge benefits to medicine and potentially save millions of lives.

But significant research will be required to make that happen. As such, we will be requiring (with no opt outs allowed) you and your whole family to provide blood, sperm and ova samples weekly until that research pays off. You will receive no compensation or other considerations other than the knowledge that you're moving the technology forward.

May we assume you're fine with that?
by creer | 2025-06-05 21:52:35+00:00
> phased in over a long period of time

Obviously?! Phasing in changes over long periods would solve lots of problems - at usually low cost to society it seems. You could - if anyone cared - educate the population on the time frame for the deployment, and you could - if anyone cared - advertise the time-value of the change, for example on the valuation of property before, through and after the change. And things would be fine.

But the reality of things seems to be that a politician will be in power for just a few years. So that either they need the change to go in effect so they can claim the deed and the effects (alleged - because who cares if it's real?), or they prefer the change to happen just after they have left (so the change / effect can be blamed on the next guy? or can be postponed should they get re-elected.)

Nobody (?) looks to make the change "fair" to the population. There is no electoral value in that.

This shows up everywhere: agricultural subsidies, tax rate changes, property tax changes, construction / permitting / zoning changes, usage of an area (similar to zoning see construction or extension of an airport and residential nuisance), planned future freeway path, legalization or criminalization of any activity, climate change rules. So that some industries become perpetually on the lookout for the next cycle (mining, oil, finance?), while others constantly get away with claiming unawareness (zoning, permitting?)
by Dylan16807 | 2025-06-05 21:52:51+00:00
If you want such constant updates that's tricky to distribute and hard to collect, but let's put that aside for a bit. I want to focus on the amount of data and how the car would use it. With $500 of SSD being nice and cheap.

> i am talking about the processing of the data on the 8TB SSD on the car while at speed.

I'm not worried about that. The actual driving takes such powerful computers that even if there was a petabyte of total data, the amount the car would have to process as it moves would be a trickle in comparison to what it's already doing. Max 50KB per 10 milliseconds. And obviously the data would by sorted by location so there's very little extra processing required.

But you tell me, how many data points do you think you need per meter of road?

I really don't think you need millimeter-level surface perturbations all the way across. Mapping the precise edges of the road and lanes should only need dozens of data points, 4 bytes each. And then you can throw a few more dozen at points inside the lanes to flesh it out. You can throw a hundred data points at each pothole without breaking a sweat. Measuring the surface texture in various ways and how it responds to weather is only going to take a handful of bytes per square meter, in a way that repeats a lot and is easy to compress.

> 568143,964990,0,0.07,02_36250355,2,02_39,Ohio,S161,DUBLIN GRANVILLE RD,State,Paved,4,88,3,7,0,0.000759951397761616

That's an extremely inefficient format. Unnecessary object ids, repeating metadata over and over, way too many decimal places, and all stored as text.

But even then, your database is so tiny compared to the size I suggested that I don't think we can extrapolate anything useful. Even if we 4x it or whatever to compensate for a lack of rural roads.
by jessoteric | 2025-06-05 21:53:50+00:00
This right here. Every time I talk to someone claiming 2-4x multipliers, after a few rounds of conversation they eventually admit "yeah you have to learn when to stop when it's no longer productive, you get a feel for when it's veering into wasting your time".

It can't be both. It can't be 2-4x multiplier _and_ be wasting your time to the extent that you have to "get a feel for when it has been wasting your time".
by lo_zamoyski | 2025-06-05 21:54:53+00:00
The burden of proof is to show that there is any real or substantive similarity between the two beyond some superficial comparisons and numbers. If you can't provide that, then you can't answer those questions meaningfully.

(Frankly, this is all a category mistake. Human minds possess intentionality. They possess semantic apprehension. Computers are, by definition, abstract mathematical models that are purely syntactic and formal and therefore stripped of semantic content and intentionality. That is exactly what allows computation to be 'physically realizable' or 'mechanized', whether the simulating implementation is mechanical or electrical or whatever. There's a good deal of ignorant and wishy-washy magical thinking in this space that seems to draw hastily from superficial associations like "both (modern) computers and brains involve electrical phenomena" or "computers (appear to) calculate, and so do human beings", and so on.)
by behnamoh | 2025-06-05 21:56:01+00:00
While Tokasaurus’s Async-TP shows impressive throughput gains, it seems over-engineered for common use cases. The CPU overhead from async tensor parallelism only pays off at 6k+ token batches, and you need NVLink-connected GPUs to see real benefits. Most prod deployments don’t need this complexity — you’re better off with simpler approaches unless you’re specifically optimizing for massive batch throughput. The adaptive manager skipping “optional” tasks under load also feels concerning from a reliability perspective.
by mmooss | 2025-06-05 21:56:23+00:00
I know that argument, but it may not persuade enough people. And how about Russia killing Americans - or any people - that make software that Ukraine uses in the war? How about Ukraine killing Americans or others who make software for Russia?

Lots of American make things for all sorts of brutal regimes. Are they acceptable targets?

We can argue about it - I actually agree that people making bombers seem like acceptable targets to me - but that's mostly irrelevant. The question will be the effect on support and morale when the news shows someone's home burning and even other civilians dead, and whether the benefit is worth those costs.

> building bombers

I don't think they are building any bombers at this point; they lack the components. Maybe repairing and supporting them?
by ang_cire | 2025-06-05 21:57:26+00:00
> non-technical users that will be suggesting changes

Suggesting is not making. Non-technical users will not be making changes.

> You are conflating "bad or no support" with "gate-keeping".

If the support is intentionally removed with the goal of keeping out people, then it's both. That was the premise accepted by both of the comments above mine, hence my comment working from that premise.

> Having a "noob" version of installation instructions for something like Arch/Gentoo will have the effect of allowing someone to fumble about and maybe achieve getting something functional, but they won't actually understand what they are actually doing and this will cause them problems in the future as they won't understand how to fix issues when they arise.

Everyone is a noob at some point, so getting rid of documentation is only a means to prevent someone from learning. There is no cost to anyone if someone installs Arch without being an expert in the CLI.

> It is extremely difficult for even for large companies to run their own fork of large open source projects.

Agreed. And if there aren't enough people who are willing to support a fork to manage one, there aren't enough people to justify preventing a change that keeps the current version as it is (which is what in this case, that fork would be).

I.e. if there aren't enough people who support the current version, to maintain an unchanged version as a fork, there aren't enough people who support the current version to justify not changing it in the first place.

> If you aren't willing to "pay your dues", then it maybe better for you to not be involved.

Where are you getting this from? The whole conversation was newcomers making changes. Code contributions (i.e. changes) are explicitly the "dues" that OSS devs 'pay'.

> If you go to Church you have to accept certain tenants about the faith or at least respect them while you are there.

If enough of the congregation feels it needs to change, it will (or it will die out). Modern versions of religions look nothing like they did hundreds of years ago, and not all the changes happened due to schisms/ forks. Everything changes, or it dies.
by palata | 2025-06-05 21:57:31+00:00
> Social media laws aren't really about limiting consumption of the content, they are about limiting who can sign up to actively contribute

First, I can't really consume content on Facebook or TikTok because I don't have an account. So I believe that your statement is not entirely correct.

Second, for social media there is the network effect. If suddenly most kids can't access them anymore, then they lose value for them. You'd need most of them to work around the check. Porn you can find in torrent, but a social media account you can't.

Again, I totally understand the issue with the check: who will be left out? What if adults get disconnected because they don't have a way to verify their age? Not sure that it would be a big issue for TikTok, but it would be a problem for WhatsApp (assuming that one would want age verification for WhatsApp).