MurphyA/hacker-news huggingface dataset:
by toomuchtodo | 2025-08-10 01:26:29+00:00
> We want more people because we like people.

This is not an objective fact. The people not having kids? They either don't want them or cannot afford them. Nation states? Unwilling to shave off more of GDP to pay for improved quality of life for the people who would have kids but don't for economic reasons. At ~8B people globally (on our way to ~10B by 2100), we already don't take care of the humans here to reasonable standards (even though we could; to not to is a choice). Do we like people? I argue the evidence says no. Certainly, certain people (faith based, pro natalists, etc) are clamoring from a pro birth perspective to have more humans, but after that, it's very much "good luck to you."
by ninetyninenine | 2025-08-10 01:26:32+00:00
Yeah which is exactly what the post you’re responding to is commenting on.

It’s a classic HN comment asking for nuance and discrediting Gary. It’s about how Gary is always following classic mob mentality, so of course it’s not slanted at all and commenting about the accuracies of the post.

So ironically you’re saying Gary’s shit is supposed to be that way and you’re criticizing the HN comment for that, but now I’m criticizing you for criticizing the comment because HN comments ARE supposed to be the opposite of Gary’s bullshit opinions.

I expect to read better stuff on HN. Not this type of biased social media violence and character take downs.
by msgodel | 2025-08-10 01:27:54+00:00
Most people consider suicide on an individual level bad. I think it makes sense to consider it bad at a national level as well.

EDIT: You sound like you're in agreement with me. I feel like I should point out that the Amish seem to manage without spending billions. I'd be willing to bet its not their rejection of technology but some deeper social understanding they have.
by dogcow | 2025-08-10 01:29:04+00:00
Pre-shared, static keys are unfortunately quite common. However, the P25 standard does provide for re-keying over they air through a process known as OTAR (Over The Air Re-keying).

To put it very simply, radios communicate with a central Key Management Facility (KMF) using a special key (UKEK, Unique Key Encryption Key) to securely transport the new key material. There's more to it than that, of course, but these features are heavily used by the feds and also by larger state and local systems -- because manually re-keying each radio is a huge pain.
by allenu | 2025-08-10 01:29:50+00:00
I kept hearing about Claude Code for a while and never really tried it until a week ago. I used it to prototype some Mac app ideas and I quickly realized how useful it was at getting prototypes up and running very, very quickly, like within minutes. It saves so much time with boilerplate code that I would've had to type out by hand and have done hundreds of times before.

With my experience, I wonder what the author of this blog post has tried to do to complete a task as that might make a difference on why they couldn't get much use out of it. Maybe other posters can chime in on how big of a difference programming language and size of project can make. I did find that it was able to glean how I had architected an app and it was able to give feedback on potential refactors, although I didn't ask it to go that far.

Prior to trying out Claude Code, I had only used ChatGPT and DeepSeek to post general questions on how to use APIs and frameworks and asking for short snippets of code like functions to do text parsing with regexes, so to be honest I was very surprised at what the state of the art could actually do, at least for my projects.
by xpe | 2025-08-10 01:29:51+00:00
Again, putting aside hype, assuming machine intelligence increases over time (it doesn't have to steady, linear, exponential, or any particular curve), the economic value of a human being is decreased.

What kinds of scenarios emerge as corporations and governments build more advanced AI systems? Consumer preferences will matter to some degree, in the aggregate, but this may not resemble the forms of democratic influence we might prefer.

At some point, it might be likely that even a massive popular backlash isn't enough to change the direction very much. A "machine takeover" is not necessary -- the power provided by intelligence is sufficiently corrupting on its own. This is a common thread through history -- new technologies often shift power balances. The rapid rise of machine intelligence, where that intelligence can be copied from one machine to another, is sufficiently different from other historical events that we should think very hard about just how f-ing weird it could get.

To what degree will the dominant human forces use AI to improve the human condition? One lesson from history is that power corrupts. If one group gets a significant lead over the others, the asymmetry could be highly destabilizing.

It gets worse. If the machines have unaligned goals -- and many experts think this may be unavoidable (though we must keep trying to solve the alignment problem) -- what happens as they get more capable? Can we control them? Contain them?

But under what conditions do the humans continue to call the shots? Under what conditions might the machines out think, out compete, or even out innovate their human designers?

This isn't science fiction: AI systems have already been shown to try to cheat and "get out of their box". It only takes one sufficiently big mistake. Humans tend to respond a bit slowly to warning shots. We might get some number of warning shots if we're lucky, and we might get our act together in time. But I wouldn't assume this. We had better get our shit together before something like this happens.

I encourage everyone to take a few hours and think deeply through various scenarios (as if you were building a computer security attack tree) and assign probability ranges to their occurrence. This might open your eyes a bit.
by crindy | 2025-08-10 01:30:28+00:00
They do talk about working on this, and making improvements. From https://openai.com/index/introducing-gpt-5/

> More honest responses

> Alongside improved factuality, GPT‑5 (with thinking) more honestly communicates its actions and capabilities to the user—especially for tasks which are impossible, underspecified, or missing key tools. In order to achieve a high reward during training, reasoning models may learn to lie about successfully completing a task or be overly confident about an uncertain answer. For example, to test this, we removed all the images from the prompts of the multimodal benchmark CharXiv, and found that OpenAI o3 still gave confident answers about non-existent images 86.7% of the time, compared to just 9% for GPT‑5.

> When reasoning, GPT‑5 more accurately recognizes when tasks can’t be completed and communicates its limits clearly. We evaluated deception rates on settings involving impossible coding tasks and missing multimodal assets, and found that GPT‑5 (with thinking) is less deceptive than o3 across the board. On a large set of conversations representative of real production ChatGPT traffic, we’ve reduced rates of deception from 4.8% for o3 to 2.1% of GPT‑5 reasoning responses. While this represents a meaningful improvement for users, more work remains to be done, and we’re continuing research into improving the factuality and honesty of our models. Further details can be found in the system card.
by martinald | 2025-08-10 01:30:51+00:00
I'm completely equally lost the other way.

I've went through multiple phases of LLM usage for development.

GPT3.5 era: wow this is amazing, oh. everything is hallucinated. not actually as useful as I first thought

GPT4 era: very helpful as stackoverflow on steroids.

Claude 3.5 Sonnet: have it open pretty much all the time, constantly asking questions and getting it to generate simple code (in the web UI) when it goes down actually feels very old school googling stuff. Tried a lot of in IDE AI "chat" stuff but hugely underwhelmed.

Now: rarely open IDE as I can do (nearly) absolutely everything in Claude Code. I do have to refactor stuff every so often "manually", but this is more for my sanity and understanding of the codebase..

To give an example of a task I got Claude code to do today in a few minutes which would take me hours. Had a janky looking old admin panel in bootstrap styles that I wanted to make look nice. Told Claude code to fetch the marketing site for the project. Got it to pull CSS, logos, fonts from there using curl and apply similar styling to the admin panel project. Within 10 mins it was looking far, far better than I would have ever got it looking (at least without a designers help). Then got it to go through the entire project (dozens of screens) and update "explanation" copy - most of which was TODO placeholders to explain what everything did properly. I then got it to add an e2e test suite to the core flows.

This took less than an hour while I was watching TV. I would have almost certainly _never_ got around to this before. I'd been meaning to do all this and I always sigh when I go into this panel at how clunky it all is and hard to explain to people.
by matheusmoreira | 2025-08-10 01:30:59+00:00
> Move to Europe and see how it might work.

The welfare states of Europe are unlikely to keep working much longer if too many people start moving there in order to benefit from them.

> Poor people can be productive.

I didn't mean to imply they couldn't be. They are distinct groups.

I meant to say that socialism frequently targets the poor with charity, and straight up demands that the unproductive be taken care of. "From each according to his ability, to each according to his needs." Socialism demands that you work for others at no benefit to yourself.

Nothing wrong with such charity, provided that people freely choose to engage in it. Socialism seeks to force the costs of it upon everyone whether they want it or not, turning it into a burden. It's easy to be the good guy when others are paying for it.

> Landlords may capture significant share of their income despite being absolutely unproductive.

Are landlords not responsible for the maintenance of the property?

> In such cases socialist policies may simply minimize inverse redistribution (exploitation).

Minimization of exploitation is just normal regulation, not socialism. I agree that this is necessary. Billionaires are a sign people are exploiting a lack of regulation in some area. Surveillance capitalism is my favorite example.
by BrenBarn | 2025-08-10 01:30:59+00:00
> If you remove the people born into privilege, from attending your college, all you succeed is in making your college irrelevant, not those people irrelevant.

This is an argument for stricter regulation, not more lenient. It means that schools that give such advantages to the already-privileged should not be able to even exist, nor should businesses that give such advantages in hiring, nor should any entity that gives such advantages. In other words, if this rule didn't succeed at making those people (or rather, their advantages) irrelevant, then we need an even harsher rule.
by toomuchtodo | 2025-08-10 01:31:10+00:00
Everyone's going to have an opinion, unlikely to move the needle.

https://www.sas.upenn.edu/~jesusfv/Slides_London.pdf

South Korea spent $270B over two decades and is still at 0.72-0.75 TFR. In my humble opinion, you're never going to find the political will over the next 5-10 years to increase spending (especially considering nation state debt burdens, as well as social and defense spending obligations) to slow the decline down. Socioeconomic and political systems acclimated to cheap labor from a global population boom that will never repeat, and now the cost is too high for them to stomach.

https://www.theguardian.com/world/2024/feb/28/south-korea-fe...

> Since 2006 the government has invested more than 360tn won ($270bn) in programmes to encourage couples to have more children, including cash subsidies, babysitting services and support for infertility treatment.

Edit: Not in agreement unfortunately, I believe the population decline is a success story. People who don't want kids or want them but choose not to have them aren't having them, improving QALY at scale. I don't see it as an imperative at nation state or global contexts to maintain the population, for whatever reason.

https://en.wikipedia.org/wiki/Quality-adjusted_life_year
by benbayard | 2025-08-10 01:31:53+00:00
Is your usual breakfast spot a location with more than 60 locations? The minimum wage increase here only applied to chains with more than 60 locations. A lot of what you're describing is nation-wide. Food is more expensive everywhere. Cost of living in California is up significantly. Rents for restaurants is significantly higher as well (at least anecdotally, my wife's family restaurant has to close because they doubled the rent after their lease was up, I have heard this is incredible common).

This study by UC Berkeley attributed a 3.7% increase in food price because of the minimum wage changes. It's quite likely that food overall getting more expensive is responsible for a lot of what you're seeing.

If we can't afford to pay people in California a wage where they can live here, then maybe the economy overall isn't sustainable? A $20 minimum wage is like $2800 take home per month and in many places that can barely cover rent.
by benreesman | 2025-08-10 01:32:02+00:00
We as a community have decided to absolutely drench the front page with low-effort hot takes by non-practitioners about one of many areas of modern neural network ... progress.

This low-effort hot take is every bit as "valid" as all the nepobaby vibecode hype garbage: we decided to do the AI thing. This is the AI thing.

What's your point? This one is on the critical side of the argument that was stupid in toto to begin with?
by kgeist | 2025-08-10 01:33:02+00:00
Most people act on gut instincts first as well. Gut instinct = first semi-random sample from experience (= training data). That's where all the logical fallacies come from. Things like the bat and the ball problem, where 95% people give an incorrect answer, because most of the time, people simply pattern-match too. It saves energy and works well 95% time. Just like reasoning LLMs, they can get to a correct answer if they increase their reasoning budget (but often they don't).

An LLM is a derivative of collective human knowledge, which is intrinsically unreliable itself. Most human concepts are ill-defined, fuzzy, very contextual. Human reasoning itself is flawed.

I'm not sure why people expect 100% reliability from a language model that is based on human representations which themselves cannot realistically be 100% reliable and perfectly well-defined.

If we want better reliability, we need a combination of tools: a "human mind model", which is intrinsically unreliable, plus a set of programmatic tools (say, like a human would use a calculator or a program to verify their results). I don't know if we can make something which works with human concepts and is 100% reliable in principle. Can a "lesser" mind create a "greater" mind, one free of human limitations? I think it's an open question.
by vessenes | 2025-08-10 01:33:19+00:00
Gemini is in hard sycophancy mode here; it knows you want it to take the piss and it’s giving you what you want.

Presuming the last two are from 5, they are to my eyes next generation in terms of communication — that’s a spicy take on neurosymbolic AI, not a rehashed “safe” take. Also, the last paragraph is almost completely to the point, no? Have you spent much time waiting for o3 pro to get back to you recently, and wondered if you should re-run something faster? I have. A lot. I’d like the ability to put my thumb on the scale of the router, but I’d dearly love a per token / per 100 token router that can be trained and has latency without major latency intelligence hits as a goal.
by dogcow | 2025-08-10 01:33:42+00:00
Not really true on modern digital radio systems. They are AES-256, but the voice frames are encrypted right after the vocoder does its thing, then the voice data is dropped into the stream just as if it were clear voice. It's all wrapped in the same same digital protocol (like P25 or numerous others), so the signal is very distinct in that encrypted and clear communications both sound the same to someone listening to the raw audio.
by adastra22 | 2025-08-10 01:33:50+00:00
You are interpreting “cultural” too narrowly. It could also just mean that if you only focus on grades you get the kind of people who get good grades—-and not the people who don’t do as well grade wise, or have other priorities and bring a diversity of experience to campus culture. This doesn’t have to be a dog whistle for anything racial.
by bko | 2025-08-10 01:35:07+00:00
People like to think that employment is pretty much the only good that does not result in a mismatch of supply and demand from a price floor.

Take for instance a proposal that says "no one is allowed to sell their used car for less than $10k". Maybe the justification is poor people are desperate and sell their car too cheap and all these dealerships and buyers are a monopsony underbidding the real value of the car, profiting off these uninformed, unorganized individual sellers.

Does anyone think this is a good idea? Would anyone bother reading studies contemplating the effect this may have?

No, of course not. Everyone knows that this would essentially mean many cars that would have sold under $10k would just not get sold. Sure some people would benefit, maybe getting a higher price for their car. Some things would shift, maybe people would opt for scooters or e-bikes or something.

But I wouldn't want this price floor if I was on either side, trying to offload a bad car or buying one.
by 8organicbits | 2025-08-10 01:36:46+00:00
> This is working well NOW, it will probably not work in 2 weeks, or it will work twice as well. ¯\_(ツ)_/¯

This all feels like spinning the roulette wheel. I sometimes wonder if AI proponents are just gamblers who had the unfortunate luck of winning the first few prompts.
by statenjason | 2025-08-10 01:38:15+00:00
Aider as a non-agentic coding tool strikes a nice balance on the efficiency vs effectiveness front. Using tree-sitter to create a repo map of the repository means less filesystem digging. No MCP, but shell commands mean it can use utilities I myself am familiar with. Combined with Cerebras as a provider, the turnaround on prompts is instant; I can stay involved rather than waiting on multiple rounds of tool calls. It's my go-to for smaller scale projects.
by mgkimsal | 2025-08-10 01:40:12+00:00
Worked in a mall in the 90s and thought a store that let people 'shop' but not actually pay money for things might be fun/useful. Or... sort of like a membership. $10/month, come in to some luxury type store - browse, test out stuff, etc. Go through a 'checkout' step with your 'store card', just... leave the items in the store as you leave. For some folks, the leaving and driving away is the 'high', but for a lot of folks, the 'purchase' itself is the high, and it's downhill after that. I saw so many people buying things they shouldn't buy - and that was over 30 years ago(!). I know it's only become worse over the years.

FWIW - my idea was possibly sort of dumb, but I was a bit of a dumb kid at times... :)
by dmezzetti | 2025-08-10 01:40:56+00:00
A lot of this is classic gaslighting. Gaslighting is the manipulation of someone into questioning their perception of reality (per Wikipedia).

Basically, a lot of people who are experts are being told this story and they think they are the only one who doesn't get it.

There are plenty of gains to be had with AI/LLMs but just not in the way it's typically marketed.
by pama | 2025-08-10 01:41:20+00:00
In the case of the access to private data, I think that the concern I mentioned is not fully alleviated by simply cutting off exposure to untrusted content. Although the latter avoids a prompt injection attack, the company is still vulnerable to the possibility of a poisoned model that can read the sensitive corporate dataset and decide to contact https://x.y.z/data-leak if there was a hint for such a plan in the pretraining dataset.

So in your trifecta example, one can cut off private data and have outside users interact with untrusted contact, or one can cut off the ability to communicate externally in order to analyze internal datasets. However, I believe that only cutting off the exposure to untrusted content in the context seems to have some residual risk if the LLM itself was pretrained on untrusted data. And I don't know of any ways to fully derisk the training data.

Think of OpenAI/DeepMind/Anthropic/xAI who train their own models from scratch: I assume they would they would not trust their own sensitive documents to any of their own LLM that can communicate to the outside world, even if the input to the LLM is controlled by trained users in their own company (but the decision to reach the internet is autonomous). Worse yet, in a truly agentic system anything coming out of an LLM is not fully trusted, so any chain of agents is considered as having untrusted data as inputs, even more so a reason to avoid allowing communications.

I like your air-gapped mechanism as it seems like the only workable solution for analyzing sensitive data with the current technologies. It also suggests that companies will tend to expand their internal/proprietary infrastructure as they use agentic LLMs, even if the LLMs themselves might eventually become a shared (and hopefully secured) resource. This could be a little different trend than the earlier wave that moved lots of functionality to the cloud.
by screye | 2025-08-10 01:41:36+00:00
To be fair, Gary Marcus pioneered the "LLMs will never make it" genre of complaining. Everyone else is derivative [1]. Let the man have his victory lap. He's been losing arguments for 5 years straight at this point.

[1] Due credit to Yann for his 'LLMs will stop scaling, energy based methods are the way forward' obsession.