MurphyA/hacker-news huggingface dataset:
by NadineCentrum | 2025-08-12 16:49:31+00:00
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To Apply: https://www.careers-page.com/centrum-ai/job/63W367VW
by spauldo | 2025-08-12 16:49:41+00:00
Is it? If the law would prevent Wikipedia from operating in the UK without adding age verification, blocking the UK is just a method of compliance. Organizations like the EFF want to strike down laws like this, but Wikipedia exists to operate a freely editable encyclopedia.

It's really down to whether Wikipedia feels that compliance would go against the organization's principles. If so, blocking the UK is a perfectly reasonable thing to do. If another organization steps in to mirror Wikipedia in a way that complies with UK law, there's no downside for Wikipedia - they maintain their principles and the UK continues to have at least some access to free information.
by F7F7F7 | 2025-08-12 16:49:54+00:00
Inventivatbly the files become a mess of their own. Changes and learnings from one part of the plan often dont result in adaptation to impacted plans down chain.

In the end you have a mish mash of half implemented plans and now you’ve lost context too. Which leads to blowing tokens on trying to figure out what’s been implemented, what’s half baked, and what was completely ignored.

Any links to anyone who’s built something at scale using this method? It always sounds good on paper.

I’d love to find a system that works.
Show HN: Humanmark verifies your users are human using hardware attestation
by ericinseattle | 2025-08-12 16:50:03+00:00
We built Humanmark to provide cryptographic proof that a request came from a human. It uses the secure hardware in smartphones to create attestations of user presence.

Note on trying it: The demo requires installing our free app from the App Store or Play Store.

Backstory: We were toying around with building an online service that was human-only and saw that existing off-the-shelf verification methods can't enforce this to any reasonable degree. CAPTCHAs are easily solved by automation, AI can trick behavioral analysis, and agents self-identify as human. The existing tools are OK at preventing bad bots from bringing down your service, but not so much at differentiating between good bots and humans. We prototyped a hardware-based approach and thought it could be widely useful, especially now that the required hardware is ubiquitous.

How the flow works:

1. Your backend creates a challenge with our API

2. Your frontend loads our SDK with that challenge

3. SDK shows a QR code on desktop or button on mobile

4. User scans the QR or taps the button to open our app

5. User authenticates with fingerprint/face/passcode

6. App generates hardware-attested proof of user presence

7. Our backend processes and verifies the proof, forwards a verification receipt to the SDK

8. SDK returns the receipt to your frontend

9. Your frontend uses the receipt to authorize the action however makes sense

There are no user accounts and zero persistence of user data (sensitive or not) across verifications.

So far we've built our rust backend, native iOS/Android apps, TypeScript/JavaScript SDK, user- and dev-facing websites, and a Discourse plugin for quick integration.

Limitations:

- Requires a smartphone

- Users must install our app to verify (the main friction point)

- Robots that can physically operate smartphones could pass

- Not an authN/identity product; focused on what users are, not who they are

We see this complementing existing verification methods. Services might use CAPTCHA or Turnstile broadly and add Humanmark for specific high-value actions. Or they could use it everywhere if their users accept the app installation requirement.

Looking for feedback on security considerations we haven't accounted for, integration patterns that would work better for your stack, use cases or industries where this could make an impact today. Happy to discuss and receive any feedback.
by kelseyfrog | 2025-08-12 16:50:12+00:00
In China, dissent is caged because it still has teeth. In the US, free speech is allowed because the teeth are all gone. We parade the animal about, saying, "Look, we still have free speech", but it has no ability to bite.

I don't know what's worse, being trapped in a cage or de-fanged and let loose. I've only ever lived without teeth, so the idea of biting sounds almost beautiful.
by steventey | 2025-08-12 16:50:23+00:00
After 9 months of private beta, we're excited to launch Dub Partners to the world!

Some stats: $9M+ affiliate revenue tracked to date $3M+ earned by 3K+ partners Used by top companies like Framer, Superhuman, Tella, Anara, Privy and more.

Excited to hear any feedback/thoughts about this!
by kqr | 2025-08-12 16:50:44+00:00
Thank you for making it. The imagery of it is striking and comes back to me every now and then. I cannot unhear "a high wall is not high to be measured in units of length, but of angle" -- beautifully put.

The idea was that it'd be good example of having to navigate somewhat foreign but internally consistent worlds, an essential text adventure skill.
by dkiebd | 2025-08-12 16:51:11+00:00
> If I own a social media site wouldn’t you argue that I should be able to control what content I “boost” in the first place? Am I forced to compulsory “boost” your content? In which case wouldn’t that mean I am “censoring” the PoV of the social media company?

That sounds cool as long as you forfeit your Section 230 rights since at that point you’re more of a newspaper than a social network.

Yes, I know all social networks do this currently which is why they should all lose their Section 230 rights.
by grafmax | 2025-08-12 16:51:18+00:00
No I mean small-d democratic rights which Trump has been eroding as he consolidates power - retaliating against free speech, deploying federal forces against protestors, suspension of due process, concentration camps, and undermining the independence of the judiciary by attacking judges. By limiting our focus to the legal justification of the militarizing of DC we miss the big picture - erosion of small-d democratic norms and processes in our country.
by Aurornis | 2025-08-12 16:52:09+00:00
I've tried to use Perplexity after reading all of the hype, seeing it praised by so many VCs, and seeing it appear on so many different lists of essential AI tools.

Yet most of my Perplexity queries have produced poor results. It always feels like they optimized for minimizing latency and producing output that feels good instead of doing actual research. Most of the time it feels like the same quality of results I'd get from skimming the top of the Google search page summaries if I didn't filter out the spammy site.

The product could be more useful if it spent several minutes researching, but that would defeat the wow factor that I'm sure their product managers are prioritizing.
by YesThatTom2 | 2025-08-12 16:52:10+00:00
My Commodore 64 had a spellchecker. It was a separate program. I had to save my file, exit my word processor program, switch floppies to the spell checker program, wait for it to load, and all I got was a list of misspelled words… no suggested corrections.

Thinking back, how the heck did they do spell checking algorithms on a 6502? That’s a bit of code I’d like to see reverse engineered!
by AnimalMuppet | 2025-08-12 16:52:15+00:00
From false premises, you can logically and rationally reach really wrong conclusions. If you have too much pride in your rationality, you may not be willing to say "I seem to have reached a really insane conclusion, maybe my premises are wrong". That is, the more you pride yourself on your rationalism, the more prone you may be to accepting a bogus conclusion if it is bogus because the premises are wrong.
by atonse | 2025-08-12 16:52:33+00:00
Ok thanks, I will look into this.

I may have said in another comment, that I was actually against most of these cuts. Those programs (like PEPFAR). I actually worked with USAID 20 years ago teaching programming classes in Romania and Serbia, and not once did anyone I encountered have a single cynical view on anything. We were all just working hard to "teach a man to fish". So I know that these types of programs play a huge part in showing the world that we actually walk the walk in wanting a better world.

I still can't get behind the idea of wishing violence for policy changes. Maybe that's a core principle of mine. It feels anti-American, since we (historically) try to rise above that, even if we often fail.

The nature of policy changes at such high levels is that many decisions are going to result in people dying (think of geopolitical decisions, think of Syria, the famine in Sudan right now, etc).

And while this administration has definitely been more damaging than the past administrations, my reaction is to argue till our faces are blue whether it was a bad policy decision or not, rather than wish violence.
by Illniyar | 2025-08-12 16:52:41+00:00
It's definitely a business model. Just like a dark pattern is a pattern :)

The counter to that argument is that it's creating an adverse effect on your most profitable customers, with an incentive to move to offerings that don't have free tiers (or where the free tiers are not considerably affecting your own costs).

If your free tier is so lucrative that you need to 25x the cost, then your free tier is too expansive and you need to tone it down until the economics make sense.
by firedup | 2025-08-12 16:52:43+00:00
I’m a quant who taught ML in finance at NYU for 4 years, and have spent ~6 months building an AI workflow that produces long-form equity primer reports. Not selling anything; I’m looking for blunt feedback from analysts who do equity research for a living.

What it does (brief)

Pulls public sources (filings, transcripts, ownership/insider, patent/R&D mentions, sentiment). Outputs a structured primer (business model, KPIs, financials/ratios, risks, comp set, pipeline/innovation, catalysts). All points are citation-backed to public links; no paywalled sell-side.

Where I need your critique

Biggest gaps vs. credible sell-side/independent work? Sections you’d cut/condense for real-world usability? Where would you not trust automation without a human pass? Preferred output format: single PDF/HTML vs modular notes?

Sample (mods: if links aren’t allowed, I’ll remove): RIG (Transocean) primer (HTML): https://storage.googleapis.com/derek-snow-at-outlook-co-nz-p...

Happy to answer technical/process questions in the thread. No DMs, no waitlists, just trying to make this genuinely useful for practitioners.
by the_af | 2025-08-12 16:52:46+00:00
We will have to agree to disagree, if you'll allow me the cliche.

I didn't use Adventure as an example of IF, it belongs in the older "text adventure" genre. Which is why I thought it would be more fitting to test LLMs, since it's not about experiences but about maxing points.

I think there's nothing to "solve" that an LLM can solve about IF. This genre of games, in its modern expression, is about breaking boundaries and expectations, and making the player enjoy this. Sometimes the fun is simply seeing different endings and how they relate to each other. Since LLMs cannot experience joy or surprise, and can only mechanically navigate the game (maybe "explore all possible end states" is a goal?), they cannot "play" it. Before you object: I'm aware you didn't claim the LLMs are really playing the game!

But here's a test for your set of LLMs: how would they "win" at "Rematch"? This game is about repeatedly dying, understanding what's happening, and stringing together a single sentence that will break the cycle and win the game. Can any LLM do this, a straightforward puzzle? I'd be impressed!
by Someone1234 | 2025-08-12 16:53:02+00:00
Before this they supposedly had a longer context window than ChatGPT, but I have workloads that abuse the heck out of context windows (100-120K tokens). ChatGPT genuinely seems to have a 32K context window, in the sense that is legitimately remembers/can utilize everything within that window.

Claude previously had "200K" context windows, but during testing it wouldn't even hit a full 32K before hitting a wall/it forgetting earlier parts of the context. They also have extremely short prompt limits relative to the other services around, making it hard to utilize their supposedly larger context windows (which is suspicious).

I guess my point is that with Anthropic specifically, I don't trust their claims because that has been my personal experience. It would be nice if this "1M" context window now allows you to actually use 200K though, but it remains to be seen if it can even do that. As I said with Anthropic you need to verify everything they claim.
by kaiplatschke | 2025-08-12 16:53:03+00:00
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- teamdecoder is ideology free, - works with a proprietary framework to structure a team's work and - has a unique lists view that allows for endless combinations.

We are positioned in between HR tools on one side, and project mgmt/ ressource mgmt on the other. Most teams do not have a solution for this, yet. They work with Excel and Powerpoint files or org charts that are not operationable. Using teamdecoder enables the team to adapt constantly and stay stable.

Studies show that the clarity and transparency we provide leads to wellbeing, our process makes the teams resilient and both make them more productive, while sick days and burn outs are decreasing.
by toastercat | 2025-08-12 16:53:15+00:00
+1 to Codeberg, seems like it is the best combination of familiarity and longevity. Forgejo Actions still seems incomplete, but its Woodpecker CI seems a little more mature from what I can tell. Definitely not as fleshed out as Github Actions -- a good alternative would be to mirror your repos that require Github Actions to Github, but otherwise keep repos on Codeberg.
by bachittle | 2025-08-12 16:53:21+00:00
OpenAI definitely tarnished the name of GPT-5 by allowing these issues to occur. It's clearly a smaller model optimized for cost and speed. Compare it to GPT-4.5 which didn't have these errors but was "too expensive for them".

This is why Anthropic naming system of haiku sonnet and opus to represent size is really nice. It prevents this confusion.
by protimewaster | 2025-08-12 16:53:26+00:00
Plus, they supposedly had it turn off the automatic features just before it detected an imminent crash, ensuring that they could always correctly tell everyone that "Auto Pilot was off at the time of the crash". Of course, that doesn't mean that it wasn't used in the 20 seconds prior.

So, those details weren't actually insightful. They were just PR bullshit.
by Ray20 | 2025-08-12 16:53:28+00:00
> Also commercial water rates appear to be about £2.50 / cubic meter.

I even became interested in how much energy is needed to desalinate water by boiling it, taking into account recuperation and everything else.

> Desalination depends on electricity prices, which are fairly high in the UK at the moment.

Electricity prices are largely dependent on the need to deliver a steady flow of energy and store it, which are not a concern in the context of desalination water.
by fluorinerocket | 2025-08-12 16:54:10+00:00
In MDAO you definitely know all the constraints at compile time, but inequality constraints can be active or inactive as the optimizer progresses.

That's how SNOPT, IPOPT, presumably KNITRO and nonlinear programming optimizers work.

Yes MDAO is "just" constrained nonlinear optimization.

You come up with a model for your thing, which often involves multiple "disciplines" like mass, propulsion, aerodynamics, loads, trajectory/equations of motion, and then usually use some framework to calculate the constraints values and objective value and their gradients
by sneak | 2025-08-12 16:54:23+00:00
Does it have any onboard flash? Embedded SBCs that have no wireless and no onboard state (like the RPi3 without wifi) are quite useful for security applications like offline cold signing/CAs.

The RPi4/5 have a flashable bootrom now so they don’t qualify any longer. The 1/2/3 load their second stage bootloader from the micro-SD, their first stage is burned at the factory and cannot be modified. If you remove the SD and physically destroy it, they can not persist state or exfiltrate data.
by sdesol | 2025-08-12 16:54:34+00:00
I don't use Cursor so I can't say, but based on what I've read, they optimize for smaller context to reduce cost and probably for performance. The issue is, I think this is severely flawed as LLMs are insanely context sensitive and forgetting to include a reference file can lead to undesirable code.

I am obviously biased, but I still think to get the best results, the context needs to be human curated to ensure everything the LLM needs will be present. LLMs are probabilistic, so the more relevant context, the greater the chances the final output is the most desired.
by muzani | 2025-08-12 16:54:53+00:00
They are not the same degree. The monarch is simply there to override irrational behavior.

One example: https://en.wikipedia.org/wiki/Kajang_Move

There was a popular candidate a party wanted as prime minister, who was not yet allowed to run as senator because of a sodomy conviction. So they tried to get his wife elected into a prominent position to streamline his path to prime minister. The party held the richest state in the country by a large majority and forced the head of state to step down, triggering a by-election. The wife won elections easily in that territory. It was a dick move because she is never physically in the area, but the area also didn't want to elect the Islamist party and voted for this more secular party. So she was voted as senator representing citizens in a region she didn't particular care about.

But senator wasn't enough, they wanted her in a head of state position. The sultan called out this BS and requested three names for candidates. The party submitted only one name. Sultan insisted on three names, and when they submitted three, he picked the second name as head of state.

So while kings don't have the power to block a democratic process, in this case, it prevented nepotism, which would also have messed up democracy.

In 2022, none of the three major coalitions won enough seats to form the government. Votes were split 38%, 30%, 22%. They all hated each other and part of the campaign promises were to bring down the other coalitions for corruption. The monarch ended up combining the parties into a unity government, which also entailed picking the Prime Minister.
by mark_l_watson | 2025-08-12 16:55:04+00:00
I am sort of with you. I am down to asking Gemini Pro a couple of questions a day, use ChatGPT just a few times a week, and about once a week use gemini-cli (either a short free session, or a longer session where I provide my API key.)

That said I spend (waste?) an absurdly large amount of time each week experimenting with local models (sometimes practical applications, sometimes ‘research’).
by lordkrandel | 2025-08-12 16:55:44+00:00
Though this article is meant to be against the so called "purges", which is an horrible name, because real purges were not just "bans" from communities, but real violence against people who had no way to avoid them... Though this article is really flaggable for right wing propaganda, at least has driven me to look more into NixOS and consider it as next distro I'd like to try.
by mccoyb | 2025-08-12 16:56:14+00:00
One big question I have, in the era of Claude Code (and advancements yet to come) — is why should a hacker submit to using tools behind a SaaS offering … when one can just roll their own tools? I may be mistaken, but I don’t think there is any sort of moat here.

Truly — this is an excellent and accessible idea (bravo!), but if I can whittle away at a free and open source version, why should I ever consider paying for this?
by zkmon | 2025-08-12 16:56:27+00:00
I have used WordStar in 1993. But I don't remember anyone really using the spell checker or feeling a need for it those days. Work was slow and we had enough eyes and time to catch the spelling mistakes. When we were upgraded to MS Word on Windows 3.1, we were astonished to see that it has a feature to preview the document before printing. But somehow WordSatr still looked more fluid and faster than GUI-based word processors.
by saguntum | 2025-08-12 16:56:48+00:00
This was actually put into practice during the Spanish transition to democracy. The King gave a televised address denouncing an attempted fascist coup and ordered them to stand down: https://en.wikipedia.org/wiki/1981_Spanish_coup_attempt#Juan...

To this day, bullet holes remain in the ceiling of the Spanish parliament building to remind them of the coup attempt. I can't find it anymore, but there was a good drama movie about these events on Netflix a while ago.
by CharlesW | 2025-08-12 16:56:51+00:00
> I’ve been having decent luck telling it to keep track of itself in a .plan file, not foolproof, of course, but it has some ability to “preserve context” between contexts.

This is the way. Not only have I had good luck with both a TASKS.md and TASKS-COMPLETE.md (for history), but I have an .llm/arch full of AI-assisted, for-LLM .md files (auth.md, data-access.md, etc.) that document architecture decisions made along the way. They're invaluable for effectively and efficiently crossing context chasms.
by kelseyfrog | 2025-08-12 16:56:55+00:00
A current example would be Tiktok artificially boosting ice related challenges.

Why? Because it makes searching for immigration and customs enforcement content much more difficult to find. It lower the social temperature and stops it from metaphorically boiling over.

Is crowding out content censorship? Who knows. If tilting feeds in one direction and away from another has the same effect and isn't censorship because of a definitional technicality, does it really matter?
by film42 | 2025-08-12 16:57:11+00:00
Agree but pricing wise, Gemini 2.5 pro wins. Gemini input tokens are half the cost of Claude 4. Output is $5/million cheaper than Claude. But, document processing is significantly cheaper. A 5MB PDF (customer invoice) with Gemini is like 5k tokens vs 56k with Claude.

The only downside with Gemini (and it's a big one) is availability. We get rate limited by their dynamic QoS all the time even if we haven't reached our quota. Our GCP sales rep keeps recommending "provisioned throughput," but it's both expensive, and doesn't fit our workload type. Plus, the VertexAI SDK is kind of a PITA compared to Anthropic.