MurphyA/hacker-news huggingface dataset:
by mark-r | 2025-08-22 01:40:29+00:00
A good scaling algorithm would take Nyquist limits into account. For example if you're using bicubic to resize to 1/3 the original size, you wouldn't use a 4x4 grid but a 12x12 grid. The formula for calculating the weights is easily stretched out. Oh and don't forget to de-gamma your image first. It's too bad that good scaling is so rare.
by foxylad | 2025-08-22 01:40:47+00:00
Cory Doctorow has a compelling theory that the megatech companies have to appear to be startups, or else their share price reverts to normal multiples. Hence the continuous string of increasingly over-hyped "game-changing technologies" they all (not just Meta) keep rolling out.

VR, blockchain and LLMs have their value, but it's a tiny fraction of the insane amounts of money being pumped into these bubbles. There will be tears before bedtime.
by xuki | 2025-08-22 01:43:22+00:00
For the past 15 years, mobile has been the main revenue source for Facebook. As big as Facebook is, they're at the mercy of the 2 competitors: Apple and Google. Apple has been very hostile to Facebook, because Facebook make a shitload of money off Apple's platform and they refused to pay a certain percentage to Apple - unlike Google who is paying 20B a year to access iOS users. Apple tried to cut Facebook off with ATT on iOS 14, but it didn't work.

Because of this, Zuckerberg has to be incredibly paranoid about controlling his company destiny, to stop relying on others' platforms to deliver ads. It would be catastrophic for Facebook to not be a main player for the next computing platform, and they're currently making a lot of money from their other businesses. Zuckerberg is ruthless and he is paranoid, he has total control of Facebook and he will use all the resources to control the next big thing. I think it comes down to this: Zuckerberg believes it's cheaper to be wrong than to miss out on the next platform, and Facebook can afford to be wrong (to a certain extend).
by Art9681 | 2025-08-22 01:43:52+00:00
It can be summarized as "Did you RTFM?". One shouldn't expect optimal results if the time and effort wasn't invested in learning the tool, any tool. LLMs are no different. GPT-5 isn't one model, it's 6: gpt-5, gpt-5 mini, gpt-nano. Each takes high|medium|low configurations. Anyone who is serious about measuring model capability would go for the best configuration, especially in medicine.

I skimmed through the paper and I didnt see any mention of what parameters they used other than they use gpt-5 via the API.

What was the reasoning_effort? verbosity? temperature?

These things matter.
by BobbyTables2 | 2025-08-22 01:44:50+00:00
I’m curious … So “transformative” is not necessarily “derivative”?

Seems to me the training of AI is not radically different than compression algorithms building up a dictionary and compressing data.

Yet nobody calls JPEG compression “transformative”.

Could one do lossy compression over billions of copyrighted images to “train” a dictionary?
by SnuffBox | 2025-08-22 01:44:54+00:00
> Today's analog seems to be that almost all nerds love anime and Andy Weir books and some of us feel a bit alienated by that.

Especially because (from my observation) modern "nerds" who enjoy anime seem to relish at bringing it (and various sex-related things) up at inappropriate times and are generally emotionally immature.

It's quite refreshing seeing that other people have similar lines of thinking and that I'm not alone in feeling somewhat alienated.
by andsoitis | 2025-08-22 01:45:51+00:00
> goalposts

I'm sorry you feel that way, but perhaps what I can say is that I'm trying to be hyper-precise about the boundaries (as I see them at least), rather than move them.

I think it is fine to be outraged about:

a) systematic racist (read: selective) application of the law

b) no due process

c) egregious mistakes

d) commanding the military to stampede cities (ok, in reality, it is more show than scary, but the precedent is unacceptable)

What I don't think is valid is arguing that the government should not apply the law as it stands, which empowers the government to revoke or deny visas (or residency application or naturalization application) for reasons enumerated by the State Department: https://travel.state.gov/content/travel/en/us-visas/tourism-...
by dlcarrier | 2025-08-22 01:46:38+00:00
The toilet flushing thing is performative. Even if toilet water usage were enough to be worth caring about, dual flush toilets use more water over the lifetime of the toilet, because the more complex designs have a higher failure rate: https://www.theguardian.com/environment/2020/sep/29/dual-flu...

Also, in about half of the country, aquifers replenish as fast as they are used, so there's no point in regulating their use. The largest concern is usually whether or not the well is contaminated.
by ineedasername | 2025-08-22 01:46:50+00:00
Maybe I should clarify: Society, in general, supports the idea that writers, artists, film makers, coders, etc— everyone who creates IP- should have a place in the economy. Basically just that it should be possible to make a living and have a career at it. It can be spun different ways, and those differences are important, but this is the basic thing.

This doesn’t seem like a disputable statement to me. For anyone who thinks actors’ likenesses, authors’ words, all of it- that all and everything should be up for grabs once written or put anywhere in public, that is not a widely held opinion.

Once that’s established, it all comes down to implementation details.
by Wowfunhappy | 2025-08-22 01:47:29+00:00
Because Google majorly screwed up, in a piece of software that runs with administrator privileges! Why the heck was it running with those privileges in the first place?! It's kind of nuts that Google faced basically no blow-back for rendering people's systems unbootable.

The Chrome updater could also have had a bug that completely deletes your home directory, and SIP wouldn't protect you. I guess your computer would still boot in that case, but how much would you care? The actual damage would be worse.

Anyway, this entire incident was notable precisely because it was so unusual—in ~9 years of SIP I'm not aware of any other instances where turning it off caused problems.
by godelski | 2025-08-22 01:47:36+00:00
Is `uv format` supposed to be an alias for `ruff check`?

Stupidly I ran `uv format` without `--check` (no harm done and I can `git diff` it) so I didn't see the changes it made but `ruff check` does still show things that can be fixed with `ruff check --fix`. If I'm guessing correctly the difference is coming down to the fact that I have (in my submodule where all changes were made) a pyproject.toml file with ruff rules (there's also a .flake8 file. Repo is being converted). Either way, I find this a bit confusing userside. Not sure what to expect.

I think one thing I would like is that by default `uv format` spits out what files were changed like `uv format --check` does (s/Would reformat/Reformatted/g). Fine for the actual changes not to be displayed but I think this could help with error reduction. Running it again I can see it knows 68 files were changed. Where is that information being stored? It's pretty hard to grep out a number like that (`grep -R \<68\>`) and there's a lot of candidates (honestly there's nothing that looks like a good candidate).

Also, there's a `--quiet` flag, but the output is already pretty quiet. As far as I can tell the only difference is that quiet suppresses the warning (does `--quiet` also suppress errors?)

uv format warning: `uv format` is experimental and may change without warning. Pass `--preview-features format` to disable this warning. 36 files reformatted, 31 files left unchanged uv format --quiet 36 files reformatted, 31 files left unchanged

I like the result for `--quiet` but I have a strong preference that `uv format` match the verbosity of `uv format --check`. I can always throw information away but not recover. I have a strong bias that it is better to fail by displaying too much information than fail by displaying too little. The latter failure mode is more harmful as the former is much more easily addressed by existing tools. If you're taking votes, that's mine.

Anyways, looking forward to seeing how this matures. Loved everything so far!
by buckle8017 | 2025-08-22 01:48:32+00:00
Well yes the actual please has meaning.

Green cards are for people who intend to continuously by resident in the united states.

If you go home for 3 months and get a job and rent a house then you no longer continuously reside in the united states.

It's that's simple, but there's no hard or fast rule on how many days.
by ProllyInfamous | 2025-08-22 01:48:32+00:00
>prisons are literally useless in stopping criminal behavior

"Con College" — where you learn tricks of the trade, and further divide with racism / hatred.

>stealing ... [because] regular jobs aren't considered manly or cool.

This, but also too many lazier-mindset people think this will be an easy lifestyle to sustain long-term (it's not).
by yieldcrv | 2025-08-22 01:48:40+00:00
okay, lets reset

I don’t find buybacks to be controversial, I find the Price to Equity metric to be controversial and its relevance up for review because it is based on the idea that there will be future yield in the form of dividends, and people muse about or lament how many years it would take for a shareholder to ROI from dividends at a certain share price.

But since that is not a market reality the PE ratio can be ignored as its not about the time horizon or tolerance of shareholders.

Palantir specifically has government contracts, very large ones, and is in a position to create and be selected for more contracts. Tightly coupled with this administration and the domestic and geopolitical environment.
by brendoelfrendo | 2025-08-22 01:49:31+00:00
Bad news: it doesn't seem to work as well as you might think: https://arxiv.org/pdf/2508.01191

As one might expect, because the AI isn't actually thinking, it's just spending more tokens on the problem. This sometimes leads to the desired outcome but the phenomenon is very brittle and disappears when the AI is pushed outside the bounds of its training.

To quote their discussion, "CoT is not a mechanism for genuine logical inference but rather a sophisticated form of structured pattern matching, fundamentally bounded by the data distribution seen during training. When pushed even slightly beyond this distribution, its performance degrades significantly, exposing the superficial nature of the “reasoning” it produces."
by JustExAWS | 2025-08-22 01:49:39+00:00
Why would you need Kubernetes with a startup instead of in the case of AWS just using some EC2 instances, a load balancer and an autoscaling group and a monolithic application? For your backend just use a hosted version of MySql/Postgres/ElasticSearch ?

It’s simple, no “cloud locki in” (which is really over exaggerated). The only reason to use K8s is for resume driven development. Which honestly is not a bad idea in an of itself because your startup is going to statistically fail and you might as well use the experience to get another job.
by moduspol | 2025-08-22 01:50:23+00:00
> I have bought a house, and they want bank records going back like a few months or maybe a year at most.

I had to juggle with this a little bit because I had sold some crypto for the down payment, but it's crypto that I had been keeping in a hardware wallet for years. As a result, I could certainly generate records showing how long I'd had it, but they'd be my own records based on the blockchain--not from any bank.

They ended up accepting transaction records from Coinbase, though even those mostly just showed some Bitcoin being received into the account and then being sold before transferred to the bank. But I guess that was enough for them.

In any case: I did ask about it and they told me it wasn't actually for KYC laws or money laundering. The reason they want a paper trail is to make sure you didn't actually just borrow the money from someone else. And that makes sense, since they're super picky about you not opening any new lines of credit while trying to close the mortgage.
by threecheese | 2025-08-22 01:51:00+00:00
The fact that GitHub’s Copilot has an enterprise feature that matches model output against code having certain licenses - in order to prevent you from using it, with a notification - suggests the model outputs are at least potentially infringing.

If MS were compelled to reveal how these completions are generated, there’s at least a possibility that they directly use public repositories to source text chunks that their “model” suggested were relevant (quoted as it could be more than just a model, like vector or search databases or some other orchestration across multiple workloads).
Show HN: Traceprompt – open-source SDK for tamper-proof LLM audit trails
by paulmbw | 2025-08-22 01:51:13+00:00
Hi HN!

I’m Paul, founder of Traceprompt. We’re building an open-source SDK that wraps your LLM calls and generates tamper-proof audit trails, so you can prove who did what, when and with which model.

You can check out the Node SDK (more languages coming soon): https://github.com/traceprompt/traceprompt-node

We built Traceprompt because LLMs are being used everywhere without a clear plan for audit and compliance. From research and discussions with other devs, I often see fintech and healthcare teams manually stitching together API Gateway, CloudWatch Logs and S3 buckets to track prompts/responses and retention. This is both complex and costly as there's little to no proof of immutability. Most current tools (Langfuse, Heliclone etc.) focus on LLM observability; few help generate verifiable evidence for compliance. That’s where we come in.

To add, regulations are also moving in this direction (e.g. the EU AI Act requires logging for certain high-risk systems, HIPAA calls for audit controls and FINRA/SEC rules push WORM-style retention). The goal is to make “prove nothing changed” boring.

Our SDK is simple:

1. BYOK architecture with AWS KMS. We never see plaintext prompts/responses; only you can decrypt. Other KMS providers are on the roadmap.

2. Append-only, hash-chained logs with a public Merkle anchor for independent verification. Repo: https://github.com/traceprompt/open-anchors

3. Audit packs: export CSV rows + proofs (and receipts) when someone asks “what exactly happened on this day and time.” You can also verify the audit packs — if a single byte was altered or a row removed by a bad actor, verification fails.

If "AI audit trails" are on your mind or on your roadmap, I'd love to talk. There are a few ways to start:

1. Checkout the repos: review code, install the SDK and experiment; open issues if anything breaks — https://github.com/traceprompt/traceprompt-node + https://github.com/traceprompt/open-anchors

2. Landing page: https://traceprompt.com — details on integrations and pricing; 7-day free trial (or 2M-token cap).

3. Join our Discord: https://discord.gg/2yUSXDECQk

4. Book a free 30-minute demo call: https://cal.com/traceprompt/traceprompt-intro

We'd love to hear your feedback, so we'll be in the comments! If you're a dev, I am happy to dive into more technical details or answer any questions. If you're in the AI audit and compliance space, please do get in touch as we have lots to learn and uncover :)

Thank you!
by bumby | 2025-08-22 01:56:10+00:00
I wonder how much of that is driven by poor performing behavioral models. There was a HN article from a few weeks back and it only had an accuracy of about 70% determining if someone was awake or asleep. I would guess that the secondary behavioral data used in this data (like cardiovascular fitness) are much harder to predict from raw sensor data than being awake or asleep.
by itake | 2025-08-22 01:56:12+00:00
There are a few problems.

- Real estate: Self-checkout takes minimal floor space. Stores can fit ~10 stations in the area of 2 cashier lanes. Even if you hire more cashiers, there’s no room to add lanes.

- Demand vs. staffing: Checkout demand is dynamic, staffing is static. You can’t instantly add cashiers during a rush, and you don’t want them idle when it’s slow. Self-checkout stations are basically ~free to run.

- Cart size: Trader Joe’s works without self-checkout because their stores are small, carts are tiny, and checkouts max ~20 items. Their cashier lanes are smaller but occupy a bigger share of store space than Walmart or Kroger. In big stores with huge carts, no one wants to be stuck behind a full cart. Once you pick a lane, you’re locked in even if another line moves faster, whereas self checkout lanes are serviced by all machines.

But in the big stores with huge inventories, no one wants to wait behind a person with a huge cart and once you commit to a lane, you're stuck, even if someone else finishes faster.
by raggi | 2025-08-22 01:57:30+00:00
For a large LLM I think the science in the end will demonstrate that verbatim reproduction is not coming from verbatim recording, as the structure really isn’t setup that way in the models under question here.

This is similar to the ruling by Alsup in the Anthropic books case that the training is “exceedingly transformative”. I would expect a reinterpretation or disagreement on this front from another case to be both problematic and likely eventually overturned.

I don’t actually think provenance is a problem on the axis you suggest if Alsups ruling holds. That said I don’t think that’s the only copyright issue afoot - the copyright office writing on copyrightability of outputs from the machine essentially requires that the output fails the Feist tests for human copyrightability.

More interesting to me is how this might realign the notion of copyrightability of human works further as time goes on, moving from every trivial derivative bit of trash potentially being copyrightable to some stronger notion of, to follow the feist test, independence and creativity. Further it raises a fairly immediate question in an open source setting if many individual small patch contributions themselves actually even pass those tests - they may well not, although the general guidance is to set the bar low - but is a typo fix either? There is so far to go on this rabbit hole.
by mc3301 | 2025-08-22 01:59:58+00:00
They do this in Japan occasionally. I've been on (officially organized by the railroad company) beer trains, wine and cheese trains, local food-tasting trains, etc. Last time, it was like 5,000 yen. All-you-can drink local beer, 2 hour round-trip with stops along the way where local mayors would hope on the train for a quick "hello" speech. Trivia quizzes, bathroom stops at stations (with perplexed-looking late-night commuters), souvenirs for sale... Good times!
by credit_guy | 2025-08-22 02:00:06+00:00
Here's my experience: for some coding tasks where GPT 4.1, Claude Sonnet 4, Gemini 2.5 Pro were just spinning for hours and hours and getting nowhere, GPT 5 just did the job without a fuss. So, I switched immediately to GPT 5, and never looked back. Or at least I never looked back until I found out that my company has some Copilot limits for premium models and I blew through the limit. So now I keep my context small, use GPT 5 mini when possible, and when it's not working I move to the full GPT 5. Strangely, it feels like GPT 5 mini can corrupt the full GPT 5, so sometimes I need to go back to Sonnet 4 to get unstuck. To each their own, but I consider GPT 5 a fairly bit move forward in the space of coding assistants.
Show HN: Ophishal v0.1.0, a Red Team CLI Phishing Framework
by ropbear | 2025-08-22 02:00:33+00:00
Putting a beta out there. This uses OpenAI's models to generate phishing emails, but with enough flexibility to simply use a JSON config and Jinja2 templates.

Don't really have the time to maintain it properly but hopefully someone finds it interesting, inspiring, or best case useful for their red team.
by kacesensitive | 2025-08-22 02:00:43+00:00
You’re describing a narrow, short-run, partial-equilibrium effect. In the real world, general-equilibrium effects swamp it:

Cut low-wage immigration and you don’t just raise some hourly rates. You also shrink output, kill complementary jobs, and push prices up for everyone, which erodes those wage gains. The National Academies’ comprehensive review finds immigration’s impact on native wages is small overall and often positive for some groups, with clear long-run growth benefits. https://nap.nationalacademies.org/catalog/23550/the-economic...

Classic natural-experiment evidence like the Mariel Boatlift shows big low-skill inflows had essentially no hit to local low-skill wages. Labor markets adjust. https://davidcard.berkeley.edu/papers/mariel-impact.pdf

Meta-work by Peri and coauthors show across many settings, native wage effects are near zero, while immigration raises productivity and lets natives move up the job ladder. https://giovanniperi.ucdavis.edu/uploads/5/6/8/2/56826033/pe...

Recent CBO work attributes stronger labor-force growth and higher GDP to immigration. Reverse that and you get slower growth and upward price pressure that cancels your “clear” wage story. https://www.cbo.gov/publication/60569

So yes, if you freeze the rest of the economy in place, fewer workers can bid up some wages. Once you allow demand, complementarities, and prices to move, the simple “less supply → higher pay” slogan stops matching the data.
by dlcarrier | 2025-08-22 02:01:55+00:00
I live in California, where half of the state is a desert half is a rainforest. The politicians here like to think that everyone lives in urban desert cities built on fault lines next to pyrophytic forests, so our regulations assume that every household needs earthquake proofing, fire proofing, thick insulation, and major urban planning.

I live in an area where pretty much non of those things matter, but one of the regulations that stands out the most is that the water everywhere has to be metered, even though the reserviour near me regularly has to be drained, because it's to full to make it through the wet season.

My water districts solution was to set the price per unit of water at cost, so I pay $40/mo for insfrastructure, and a dollar or two for water. If I quadrupled my water consumption, I wouldn't even notice the price change. I actually pay more to service the meters than I pay for water.
by s-lambert | 2025-08-22 02:03:36+00:00
The rule is necessary because the maintainers want to build good will with contributors and if a contributor makes a bad PR but could still learn from it then they will put effort into it. It's a "if you made a good effort, we'll give you a good effort" and using AI tools gives you a very low floor for what "effort" is.

If you make a PR where you just used AI, it seems to work, but didn't go further then the maintainers can go "well I had a look, it looks bad, you didn't put effort in, I'm not going to coach you through this". But if you make a PR where you go "I used AI to learn about X then tried to implement X myself with AI writing some of it" then the maintainers can go "well this PR doesn't look good quality but looks like you tried, we can give some good feedback but still reject it".

In a world without AI, if they were getting a lot of PRs from people who obviously didn't spend any time on their PRs then maybe they would have a "tell us how long this change took you" disclosure as well.
by mrandish | 2025-08-22 02:03:48+00:00
Indeed, for big valley tech companies it's crucial to have a new business developing in the wings which has plausible potential to be the "next big thing." They're desperate to keep their stock price from being evaluated solely on trailing twelve month revenue, so having a shiny, ephemeral hype-magnet to attract inflated growth expectations is essential.

So far, it appears the psychology of investors allows the new thing to fail to deliver big revenue and be tacitly dropped - as long as there's a new new thing to replace it as the aspirational vehicle. Like any good mark in a con game, tech investors want to believe.