MurphyA/hacker-news huggingface dataset:
by MattPalmer1086 | 2025-08-12 17:11:22+00:00
Any well designed privacy system does not rely on the server components doing the right thing. Servers and providers and governments are the main threat actors to be defended against. There should be no way for third parties to compromise that, by design. Almost certainly involving advanced cryptography.

Unlinkabilty and anonymity is not that hard to demonstrate in the design. At it's core it just means each proof or token is unique each time it is presented, and having no mathematical relation to others (and therefore not tied to any persistent identity either).

Client implementations may need auditing of course to make sure they are doing the right thing. But this is not really different to any other advanced technical system which we rely on every day (e.g. TLS).

As you say though, most of the public don't massively care about privacy (unless you mean their visits to porn sites I guess). But they do seem happy to accept crypto coin security assurances without being crypto experts.

As for "the purpose can change" well - so? That is also true or anything else, it does not seem like a reason to avoid having good protection now. Any change that could compromise that would not be undetectable - the fundamental crypto should not allow it. We would know if it happened.
by sofixa | 2025-08-12 17:11:26+00:00
I don't disagree with the gist of their argument, but the fact that they try to whitewash an actual genocide [1] with "politics" is absurd.

1 - if anyone is confused, the UN convention on genocide explicitly lists taking children of an ethnic group to give them to another in the definition of genocide. Russia is quite openly and blatantly doing this.
by andai | 2025-08-12 17:11:32+00:00
On a related note, the system prompt in ChatGPT appears to have been updated to make it (GPT-5) more like gpt-4o. I'm seeing more informal language, emoji etc. Would be interesting to see if this prompting also harms the reliability, the same way training does (it seems like it would).

There's a few different personalities available to choose from in the settings now. GPT was happy to freely share the prompts with me, but I haven't collected and compared them yet.
by throwaway173738 | 2025-08-12 17:11:52+00:00
The scary thing about ML isn’t that it’s poised to eat a lot of lower-reasoning tasks, it’s that we’re going to find ourselves in a landscape of “that’s just what the AI said to do” kind of excuses for all kinds of bad behavior, and we’re completely unwilling to explore what biases are encoded in the models we’re producing. It’s like how Facebook abdicates responsibility for how users feel because it’s just the product of an algorithm. And if I were a betting person I’d bet all this stuff is going to be used for making rental determinations and for deciding who gets exceptions to overdraft fees well before it’s used for anything else. It’s an enabling technology for all kinds of inhumanity.
by OutOfHere | 2025-08-12 17:12:32+00:00
Fwiw, OpenAI does have a decent active API model family of GPT-4.1 with a 1M context. But yes, the context of the GPT-5 models is terrible in comparison, and it's altogether atrocious for the GPT-5-Chat model.

The biggest issue in ChatGPT right now is a very inconsistent experience, presumably due to smaller models getting used even for paid users with complex questions.
by datadrivenangel | 2025-08-12 17:12:45+00:00
Depending on how many prompts per hour you're looking at, that's probably same order of magnitude as expensive SAAS. A fancy CRM seat can be ~$2000 per month (or more), which assuming 50 hours per week x 4 weeks per month is $10 per hour ($2000/200 hours). A lot of money, but if it makes your sales people more productive, it's a good investment. Assuming that you're paying your sales people say 240K per year, ($20,000 per month), then the SAAS cost is 10% of their salary.

This explains DataDog pricing. Maybe it will give a future look at AI pricing.
by muzani | 2025-08-12 17:13:03+00:00
We can't really speculate what the US would be like as a constitutional monarchy, as it's just very culturally anti-monarchic. The Second Amendment and free speech, for example.

In a monarchy, laws often restrict people from insulting the monarch. Not in UK, I believe, but even British culture pays their respects to the king. As a result, the king's words hold a lot of power. A president can "talk down" to congress, but a PM is still a servant of the king.

Let's say someone like Sir Richard Branson decides to do a Trump. If he claimed that he had to do X for the security of the nation, the king would be able to call him out on it. As head of military, the king has access to all the confidential data. The Supreme Court and Congress may be missing data. As the PM has to get the king to rubber stamp military actions, the king still has the right to veto it.
by kmansm27 | 2025-08-12 17:13:08+00:00
Yeah, I would say that most Claude Code users are pretty technical, but I was surprised to see that there's a decent number of non-technical users using Claude Code to completely vibe code applications for their personal use. Those users seem to love tools like Codex (the openai cloud UI one, not the CLI) and things like Omnara, where there's no setup
by Esophagus4 | 2025-08-12 17:13:12+00:00
I am a pretty regular user - I’ve found it to be helpful, and a better way of searching the web for answers.

But I also haven’t used Google in years (I switched to other search engines) so their AI might be just as good.

Perplexity also has overlap with ChatGPT’s web search, but Perplexity is faster for me.
by piotrbednarski | 2025-08-12 17:13:31+00:00
Have you ever dreamed of an accurate, grammatically correct, practically independent and cheap tool for transcribing and automatically translating Chinese to English? I think I managed to create something like that recently and it works pretty well. In this article I’ll tell the story of the problems I struggled with while creating the cctv-xinwen-lianbo-en tool, which I published yesterday on GitHub.
by bmitc | 2025-08-12 17:13:43+00:00
The part in the article that is frustrating is something I've already been fearing, that GitHub is moving towards more and more AI. It's unfortunate, but GitHub has all but completely given up on improving GitHub features that don't have anything to do with AI. No more features or even regressions are happening in the realm of quality of life and usability features. Issues are just ghost towns of people requesting, for years, very basic but enabling features, and GitHub employees are nowhere to be found on these issues. It doesn't appear that they do _any_ non-AI feature development anymore beyond just basic keep things affloat maintenance.
by PaulHoule | 2025-08-12 17:14:01+00:00
The classic example is the Lisp Machine. Hypothetically a purpose-built computer would have an advantage running Lisp, but Common Lisp was carefully designed so that it could attain high performance on an ordinary "32-bit" architecture like the 68k or x86 as well as SPARC, ARM and other RISC architectures. Java turned out the same way.

It's hard to beat a conventional CPU tuned up with superscalar, pipelines, caches, etc. -- particularly when these machines sell in such numbers that the designers can afford heroic engineering efforts that you can't.
by andai | 2025-08-12 17:14:19+00:00
My understanding was that every few months Google was forced to adjust their algorithms because the search results would get flooded by people using black hat SEO techniques. At least that's the excuse I heard for why it got so much worse over time.

Not sure if that's related to it ignoring quotes and operators though. I'd imagine that to be a cost saving measure (and very rarely used, considering it keeps accusing me of being a robot when I do...)

From what I understand, that good old Google from the 2000s was built entirely without any kind of machine learning. Just a keyword index and PageRank. Everything they added since then seems to have made it worse (though it did also degrade "organically" from the SEO spam).
by foxyv | 2025-08-12 17:14:24+00:00
You got a lingering permit? The total lack of welcome in public spaces is palpable.

The war against homeless people in the USA has spilled over to the war against public existence. You can't hang out in front of a store and cool off before your ride home without being harassed by some rent-a-cop or even worse, a real one.

Benches, shelters, water fountains, public restrooms, and tables have all been removed. Businesses will call the police on you for hanging out in front under a tree.
by estearum | 2025-08-12 17:14:28+00:00
I understand (and agree with) the impulse against violence in general, and definitely for things that are reasonable points of political disagreement. But I think you'd probably agree there's a limit, correct?

As a self-aware reductio ad absurdum, you ought to agree that violence in response to a policy of rounding up a certain ethnic group and murdering them en masse would be justified or at least in the realm of "not regrettable?"

And yes, I agree that many policy decisions can result in people dying. The moral valence of each one depends on the costs and benefits and the efforts undertaken to minimize the former and maximize the latter. And the intent is a factor too. Killing someone after a period of community deliberation for killing a child is a very different moral event than killing someone for fun.

In this particular instance, the cost/benefit analysis comes out to many people's calculation outrageously weighted to the cost side, and it is demonstrably the case that zero effort was put into minimizing those costs. This was also all knowable from Big Balls' position given that he knows how to use the Internet and could gain access to any expert in the world to more fully understand what he was doing. So he holds a lot of moral culpability (which does not imply carjacking him is a good way to deal justice, to be clear).
by vlugorilla | 2025-08-12 17:14:29+00:00
"They" refers to Qubic (by Sergey Ivancheglo), a blockchain network that uses a "Useful Proof-of-Work" system, so it is not built for traditional cryptocurrency mining that solves arbitrary puzzles. Instead, it uses the collective processing power of its miners to train an AI. Qubic's AI-training work is performed by CPUs, same as used by RandomX (Monero's mining algo).

Qubic was able to orchestrate its network of miners to temporarily halt their AI-related tasks and redirect their collective CPU power to mine on the Monero network instead.

Also, Qubic has implemented an economic strategy that involves selling the Monero it mines for a stablecoin like USDT and then using those funds to benefit its own ecosystem and attract more miners, and renting hardware to gain more hash power. The proceeds from the sale of XMR are used to buy Qubic's native token (QUBIC) from exchanges. These purchased tokens are then "burned" or permanently removed from circulation.
by utbabya | 2025-08-12 17:14:37+00:00
Whatever is making plain HTTP requests in 2025 should be a cause of concern. Wouldn't it be nice to have a low resource daemon watching for common pitfalls alerting users so we eliminate or minimise classes of problems like this?

I think lots of windows antivirus come with features like this? Perhaps with vast crystalized kno eledge nowadays we can afford to create OSS system level package that offers some level of protection.

I might actually do it, any down side?
by rs186 | 2025-08-12 17:14:40+00:00
3X if not 10X if you are starting a new project with Next.js, React, Tailwind CSS for a fullstack website development, that solves an everyday problem. Yeah I just witnessed that yesterday when creating a toy project.

For my company's codebase, where we use internal tools and proprietary technology, solving a problem that does not exist outside the specific domain, on a codebase of over 1000 files? No way. Even locating the correct file to edit is non trivial for a new (human) developer.
by grace77 | 2025-08-12 17:14:50+00:00
yes! to the second point, someone in our show HN proposed encouraging human designers to compete in submissions as well - we tried implementing this and found that, at least right now, LLMs are still so bad at design that asking a human to beat them is trivial - our plan right now is to focus more on this once it becomes more of challenges and therefore hopefully more interesting/entertaining
by pessimizer | 2025-08-12 17:15:06+00:00
I feel the main thing LLMs are teaching us thus far is how to write good prompts to reproduce the things we want from any of them. A good prompt will work on a person too. This prompt would work on a person, it would certainly intimidate me.

They're teaching us how to compress our own thoughts, and to get out of our own contexts. They don't know what we meant, they know what we said. The valuable product is the prompt, not the output.
by paffdragon | 2025-08-12 17:15:19+00:00
I don't know why you make up such stories for yourself. It's completely pointless and has zero value.

Let me share you something, maybe it helps to update your perspective.

We reject people not because they help themselves with AI, everyone on the team uses AI in some form. Candidates are mostly rejected, because they don't understand what they write and can't explain what they just dumped into the editor from their AI assistant. We don't need colleagues who don't know what they ship and can't reason about code and won't be able to maintain it and troubleshoot issues. I can get the same level from an AI assistant without hiring. It's not old vs. young, we have plenty of young people on the team, it's about our time and efforts spent on people trying to fake their skills with AI help and then eventually fail and we wasted our time. This is the annoying part, the waste, because AI makes it easier to fake the process longer for people without the required skills.
by mjr00 | 2025-08-12 17:15:48+00:00
> Will we be doing tool-calling for every task that's not just summarizing text?

spoiler: Yes. This has already become standard for production use cases where the LLM is an external-facing interface; you use an LLM to translate the user's human-language request to a machine-ready, well-defined schema (i.e. a protobuf RPC), do the bulk of the actual work with actual, deterministic code, then (optionally) use an LLM to generate a text result to display to the user. The LLM only acts as a user interface layer.
by ch4s3 | 2025-08-12 17:15:51+00:00
What exactly did he say online that got him accused of espionage? I seem to remember the issue being that he was accused of conspiring with Manning to release classified documents, and possibly gaining unauthorized access to congressional records via an exploit in the systems access controls. I don't like the idea of the US government hounding journalists who work with leakers, but Assange was always tiptoeing up to and possibly just past laws unrelated to speech. I not a simple and straightforward case and does not prove that the US is like China in terms of censorship. You can be jailed in China for simply talking about the Tienanmen Square massacre or implying Taiwanese sovereignty, nothing comparable happens in the US.
by qcnguy | 2025-08-12 17:16:12+00:00
The concerns of voters were absolutely not respected, you are completely right about that. The political class is completely bought into mass migration being a moral good, which is why getting it under control requires a complete replacement of that political class.

There were lots of things the UK could have done in theory which wouldn't have had any impact in reality. You can interview people and ask, do you have funds? Do you have a job? They say yes and go in, that's the end of it. There isn't a way under EU law to just say no there are too many people already, you can't come.
by dawnofdusk | 2025-08-12 17:17:08+00:00
It's not that troubling because we should not think that human psychology is inherently optimized (on the individual-level, on a population-/ecological-level is another story). LLM behavior is optimized, so it's not unreasonable that it lies on a Pareto front, which means improving in one area necessarily means underperforming in another.
by ninetyninenine | 2025-08-12 17:17:19+00:00
>This is because the transformers are not able to take in or output actual text efficiently. Instead, the text is converted into numerical representations of itself, which is then contextualized to help the AI come up with a logical response. In other words, the AI might know that the tokens “straw” and “berry” make up “strawberry,” but it may not understand that “strawberry” is composed of the letters “s,” “t,” “r,” “a,” “w,” “b,” “e,” “r,” “r,” and “y,” in that specific order. Thus, it cannot tell you how many letters — let alone how many “r”s — appear in the word “strawberry.”

This is a great example. The LLM doesn't know something but it makes up something in it's place. Just because it made up something doesn't mean it's incapable of reasoning.

The thing with LLMs is that they can reason. There's evidence for that. But they can also be creative. And the line between reasoning and creativity at a low level is a bit of a blur as reasoning is a form of inference but so is creativity. So when an LLM reasons or gets creative or hallucinates it's ultimately doing the same type of thing: inference.

For us, we have mechanisms in our brain that allow us to tell the difference most of the time. The LLM does not. That's the fundamental line. And I feel because of this we are literally really close to AGI. A lot of people argue the opposite. They think reasoning and is core to intelligence and a separate concept from creativity and that all LLMs lack reasoning. I disagree.

In fact humans ourselves have trouble separating hallucination from reasoning. Look at religion. Religion permeates our culture but it's basically all hallucinations that we ultimately mistake for reasoning. Right? Ask any christian or muslim, the religions make rational sense to them! They can't tell the difference.

So the key is to give the LLM the ability to know the difference.

Is there some way to build into the transformer, some way to quantify whether something is fact or fiction? Like let's say the answer to a prompt created an inferenced datapoint that's very far far away from a cluster of data. From that we can derive some metric that quantifies how likely the response is based on evidence?

Right? The whole thing is on a big mathematical multidimensional durve. If the inferenced point on the curve is right next to existing data then it must be more likely to be true. If it's far away in some nether region of the curve then it's more likely to be false.

If the LLM can be more self aware and we can build this quantitative metric into the network then use reinforcement learning to kind of have the network be less sure about an answer if it's far away from a cluster of training data points we can likely very much improve the hallucination problem.

Of course I'm sure this is a blunt instrument as even false inferences data can be very close to existing training data. But at least this gives the LLM some level of self awareness of how reliable it's own answer was.
by firasd | 2025-08-12 17:17:24+00:00
A big problem with the chat apps (ChatGPT; Claude.ai) is the weird context window hijinks. Especially ChatGPT does wild stuff.. sudden truncation; summarization; reinjecting 'ghost snippets' etc

I was thinking this should be up to the user (do you want to continue this conversation with context rolling out of the window or start a new chat) but now I realized that this is inevitable given the way pricing tiers and limited computation works. Like the only way to have full context is use developer tools like Google AI Studio or use a chat app that wraps the API

With a custom chat app that wraps the API you can even inject the current timestamp into each message and just ask the LLM btw every 10 minutes just make a new row in a markdown table that summarizes every 10 min chunk
by naasking | 2025-08-12 17:17:55+00:00
> It's not a sentiment, it's a reality that we have to deal with.

And I think you missed the main point of my reply: that people often think we need more data, but cleverness and ingenuity can often find a way to make meaningful progress with existing data. Obviously I can't make any definitive judgment about your specific case, but I'm skeptical of any claim that it's out of the realm of possibility that some genius like Einstein analyzed your problem could get no further than you have.
by snapplebobapple | 2025-08-12 17:17:55+00:00
As gently as possible, you've utterly misunderstood reality. The whole system is designed around all levels of government trying to impose their own version of stupid on all the others and providing effective PFO levers that work at varying timescales. You just witnessed a longer term PFO lever being pulled on to overturn an abortion ruling that best case had very weak constitutional grounds to stand on for its existence. There was not anywhere near civil war level violence here. What happened was the court ruling was obviously unjust to enough people that, over time it grew a stronger and stronger movement that influenced judicial appointments over decades via the ballot box.

You've also misunderstood this supreme court. It has swung towards giving a great deal of care about originalism with the argument they should not be making law, the legislators should change the constitution via the legislative pathway if they want change and it is the job of the supreme court to uphold the constitution as written/intended. That context makes it even more likely they were going to overturn abortion because in an originalist context the support for what was done in Roe V Wade is zero. The current judges will die and be replaced and if you want them replaced with people who care less about originalism then you need to adjust your political platform to ensure you can be in power often enough to swing some of those seats. In this regard the system is working perfectly.
by ecocentrik | 2025-08-12 17:18:01+00:00
Claims of privacy and user control are mostly "trust" based. A car that can be controlled and surveilled remotely, will be controlled and surveilled remotely. To dissuade potential customers of that notion they require faith in independent public or private institutions and their ability to verify that attacks on their privacy and autonomy are not possible. That doesn't seem possible in the zero trust environment people like Musk are promoting. Musk is his own worst enemy.
by potato3732842 | 2025-08-12 17:18:31+00:00
>These people are all doing what they think is right, they just aren't a super diverse group ideologically and there are social channels that tend to create more cross-brand homogeneity.

Exactly. Nothing intentionally nefarious is happening. Unintentionally nefarious things are happening all the time as a result of subsets of industries becoming insular circle jerks of like minded individuals. You see this in everything, it's not just for RightSpeak enforcers at FAANG.

It's just there's a lot more consequences for the rest of us bunch people at Meta do it to influence public discourse than when some business gets run off a cliff because the MBAs had too many sigmas or whatever.
by johnnyanmac | 2025-08-12 17:19:04+00:00
They lose the brand so that's the most important part. And chrome has far divestd from chromium in all the important ways Google makes money. It'd take years for chrome to to lose its marketshare even if Google had a chrome clone made tomorrow.

If anything, they may try to start from scratch, like with Fuschia. In which case the anti-trust was a success in making companies compete again.