MurphyA/hacker-news huggingface dataset:
by echelon_musk | 2025-10-28 09:37:47+00:00
For iPhone there's Out-Run [0] which is a great open source running app with no vendor tracking (it optionally tracks your runs locally).

For exercise, I would kindly suggest you don't make things over complicated. There's no tech solution that prevents you from putting on a pair of running shoes, getting outside and finding out what does and doesn't work yourself.

[0] https://apps.apple.com/gb/app/out-run/id1477511092
by lynx97 | 2025-10-28 09:38:03+00:00
Same for "far left", those can't be trusted either.

However, what strikes me as interesting: Do you actually destinguish between right and far right? Because I have a feeling, many people don't. Why do I think that? I recently read on Planet Debian: "Conservatives tend to be criminals". That sentences struck me as the core of the problem. People seem to fail to see the difference between a person with conservative values, and outright "Nazis". There is a clear difference, but some politically active people seem to fail to see that.
by jeroenhd | 2025-10-28 09:38:22+00:00
The difference here is that cutting a hole in a door is a destructive operation, like applying bolt cutters to a padlock. Lockpicking just operates the lock as designed.

The analogy is probably closer to someone entering your home by pushing the doorframe open so that the door opens without unlocking the lock, or that many automatic doors can be opened by spraying some compressed air through a thin sliver, triggering the internal door sensors. Both are feasible in practice, leave little evidence behind if done well, and do actually surprise a lot of people.
by tjpnz | 2025-10-28 09:38:49+00:00
When Ubuntu switched to Unity as the default desktop the positioning of the launcher made things nigh on unusable for me. I expressed my concerns on their IRC channel, I even worked on a POC (in the obscure scripting language they used) to allow repositioning it to the bottom of the screen. It was received poorly - they made it clear that they wouldn't support such a thing, and how dare you question our "design decision" (their words). Maybe things have changed since but I still find it hard to muster any sympathy. Good riddance.
by rich_sasha | 2025-10-28 09:38:51+00:00
Rereading the thread and trying to generalise: LLMs are good at noisily suggesting solutions. That is, if you ask LLMs for some solutions to your problems, there's a high probability that one of the solutions will be good.

But it may be that the individual options are bad (maybe even catastrophic - glue on pizza anyone?), and that the right option isn't in the list. The user has to be able to make these calls.

It is like this with software - we have probably all been there. It can be like that with legal advice. And I guess it is like that with (mental) health.

What binds these is that if you cannot judge whether the suggestions are good, then you shouldn't follow them. As it stands, SEs can ask LLMs for code, look at it, 80+% of the time it is good, and you saved yourself some time. Else you reconsider/reprompt/write it yourself. If you cannot make the judgment yourself, then don't use it.

I suppose health is another such example. Maybe the LLM suggests to you some ideas as to what your symptoms could mean, you Google that, and find an authoritative source that confirms the guess (and probably tells you to go see a doctor anyway). But the advice may well be wrong, and if you cannot tell, then don't rely on it.

Mental health is even worse, because if you need advice in this area, your cognitive ability is probably impacted as well and you are even less able to decide on these things.
by deaux | 2025-10-28 09:39:03+00:00
> EU data protection authorities did not come up with a way to enforce its fines and bans against the US company, allowing Clearview AI to effectively dodge the law.

This is laughable. You make it illegal for any EU company to do business with them, you imprison leadership as they arrive on EU soil, there's a hundred things you can do. Companies like these that simply ignore the law and seriously damage society need to be treated just like international drug trafficking rings. Never heard a "well they keep ignoring our fines and bans, oh my what do we do" when talking about those.
by pjmlp | 2025-10-28 09:39:40+00:00
As someone whose C# is one of the main work ecosystems, I highly doubt it.

What I am seeing it that LLMs will push current programming languages down the stack, like now you're enjoying C# => MSIL => Machine code.

On my line of work I already can imagine the other side of the tunnel, more low-code/no-code tooling, orchestration agents, and much (much) less manually writing C#, Java and TypeScript.
by imiric | 2025-10-28 09:40:05+00:00
I agree with your concerns, but I think you're overestimating the value of a human intervening in these scenarios.

A human can also say the wrong things to push someone in a certain direction. A psychologist, or anyone else for that matter, can't stop someone from committing suicide if they've already made up their mind about it. They're educated on human psychology, but they're not miracle workers. The best they can do is raise a flag if they suspect self-harm, but then again, so could a machine.

As you say, humans are complex. But I agree with GP: whether the words are generated by a machine or coming from a human, there is no way to blame the source for any specific outcome. There are probably many other cases where the machine has helped someone with personal issues, yet we'll never hear about it. I'm not saying we should rely on these tools as if we would on a human, but the technology can be used for good or bad.

If anything, I would place blame on the person who decides to blindly follow anything the machine generates in the first place. AI companies are partly responsible for promoting these tools as something more than statistical models, but ultimately the decision to treat them as reliable sources of information is on the user. I would say that as long as the person has an understanding of what these tools are, interacting with them can be healthy and helpful.
by tannhaeuser | 2025-10-28 09:40:41+00:00
Before you go and try to encode "all problems as SAT instance", I'd recommend to consider that SAT formulations require a fixed number of (Boolean) variables. Sure, you can use tens of thousands of helper variables to encode a problem, but at a certain point this gets unwieldy and basically all you're doing is working around SAT limitations and spend your time implementing a SAT encoder (and translator for the answer into your original domain language as you say).

Even simple goal-directed block's world-like robotic planning problems where the number of moves and the items to pickup/putdown are variable are much easier formulated and solved using Prolog.
by jeroenhd | 2025-10-28 09:40:45+00:00
The weird thing is, they actually had someone competent dealing with the issue:

> The strange thing about the whole situation is that Proven actually knew how to respond constructively to the first McNally video. Its own response video opened with a bit of humor (the presenter drinks a can of Liquid Death), acknowledged the issue (“we’ve had a little bit of controversy in the last couple days”), and made clear that Proven could handle criticism (“we aren’t afraid of a little bit of feedback”).

> The video went on to show how their locks work and provided some context on shimming attacks and their likelihood of real-world use. It ended by showing how users concerned about shimming attacks could choose more expensive but more secure lock cores that should resist the technique.

Sounds to me like someone professional in the company with a cooler head was on this and was handling it well, but someone else higher up got angry and aggressive and decided that revenge was more important.
by dominicrose | 2025-10-28 09:41:06+00:00
When you're not relying on a compiler you just have to right good code. And it's easier if the code never has to change, only grow. I know a confident Perl programming who rarely changes his mind about anything. When he codes something he keeps it.

I always feel like I have to "maintain" code so I usually get bored after 3k lines of code, but truth is code doesn't have to be maintained if we like it the way it is, which obviously includes all the functionality that comes with it.
by 0xrelogic | 2025-10-28 09:41:56+00:00
Good question. The financing structure is actually quite interesting it's not traditional equity investment.

For the Hyperion deal specifically (confirmed by Meta's official announcement Oct 21, 2025):

80% owned by Blue Owl Capital (private credit firm) Financed through $27B+ debt arranged by Morgan Stanley PIMCO as anchor lender (144A bonds, maturing 2049) Meta has 20% equity + 16-year residual value guarantee So Meta's "guarantee" is essentially a long-term lease commitment with a 4-year initial term + extension options. If it goes bust, Meta is still on the hook for 16 years of payments, but Blue Owl/PIMCO absorb most of the asset risk.

The other deals (CoreWeave 14.2B,Oracle 20B) are traditional service contracts Meta pays for capacity, vendors own the infrastructure.

This is actually the largest private capital deal on record according to Bloomberg (Oct 16, 2025).

Sources: Meta official announcement, Bloomberg, Data Center Dynamics
by exasperaited | 2025-10-28 09:42:10+00:00
This is not so much "more good than harm" like a counsellor that isn't very good.

This is more "sometimes it will seemingly actively encourage them to kill themselves and it's basically a roll of the dice what words come out at any one time".

If a counsellor does that they can be prosecuted and jailed for it, no matter how many other patients they help.
by Yizahi | 2025-10-28 09:42:52+00:00
If you have 2000 hectares of land you need to buy the exact amount of seeds to sow them. If you buy less you are losing money, if you buy more it is useless and you are losing money. If you have trucks or other machinery in the company you need to report exact amount of fuel needed/used, or either they won't run or you lose money on machinery missing fuel. If you need to tax a company, it is pretty important if there are 100 tons of steel used or 1000 tons. Or if the company has 5 factories to be taxed or 15. Etc.

You are anthropomorphizing LLM programs, you assume that if a number in a spreadsheed is big, then program can somehow understand it that it is a big number and if it will make an error it will be a small order error like a human would make. Human process: "hmm, here is a calculation where we divide our imports by number of subsidiaries, let me estimate this in my head, ok, looks like 7320." (actual correct answer was 7340, bu human made a small, typical mistake in the math) LLM program process: it literally uses heat maps and randomization to arrive at each particular character in a row. So it may be 7340, or it may be 8745632, or 1320, or whatever. There is a comment here at a top, from another user, where he queried LLM to make a change of value in the document and it did it correctly. But at the same time it replaced bank account number with a different bank account number. Because to LLM it is the same - sixteen digit in the field, or another sixteen digits in a field, it is the same for LLM. Because it is not AI and doesn't "understand" what it does.
by mrkeen | 2025-10-28 09:43:14+00:00
> You really don't want

And that's what this thread is filled with, and that's what I'm pushing back against.

> the RAI pattern is nice

> indicate if you are in different sections is nice

Style doesn't matter, flavour doesn't matter, wants don't matter, code "quality" (whatever that means) doesn't matter, niceness doesn't matter.

A transaction can be rolled back. If it can't, it's not a transaction.
by maelito | 2025-10-28 09:43:43+00:00
> It is pretty established at this point that React has (relative) terrible performance. > it is slow

You're not answering my question, just adding some more feelings.

> The React runtime itself is 40 kB

React is < 10 kb compressed https://bundlephobia.com/package/react@19.2.0 (add react-dom to it). That's not really significative according to the author's figures, the header speaks about up "to 176.3 kB compressed".

> Most frameworks have moved on to use signals to manage state updates. When state change

This is not kilobytes or initial render times, but performance in rendering in a highly interactive application. They would not impact rendering a blog post, but rendering a complex app's UI. The original blog post does not measure this, it's out of scope.
by CjHuber | 2025-10-28 09:43:49+00:00
So what counts as a genuine Christian in your view?

I can agree with that his books often suggest that God is the only sane way to survive, but I don‘t agree that this reduces him to only a useful necessity.

Ironically the conclusion you are making aligns very closely with what the Grand Inquisitor is preaching to Christ. And as the Grand Inquisitor is Ivan’s story, and not a plot in the book, I feel like Dostoyevsky is tackling that exact topic very prominently in the book on multiple levels. Especially through the response of the kiss.
by 0xrelogic | 2025-10-28 09:44:21+00:00
Interesting theory, but the current numbers and recent developments suggest a different picture.

Meta's Q3 2025 ad revenue is expected at 48.5B(21.666-72B, so still a significant cost-to-revenue gap.

Regarding advertising in AI assistants specifically OpenAI's Sam Altman actually addressed this in June 2025, calling ads in ChatGPT a "trust-destroying moment" (per The Decoder). There's been internal pushback at OpenAI over "engagement farming" tactics, and users already assume product suggestions are sponsored, which creates trust issues.

The more realistic monetization path for Meta (based on their earnings guidance):

Better ad targeting through AI (already happening - 11% increase in ad impressions Q2 2025) AI business tools (Meta AI for businesses) Infrastructure-as-a-service (selling excess capacity) Direct advertising in AI responses faces major regulatory and user trust hurdles. ChatGPT reached 800M weekly users by Sept 2025, but monetization through subtle product placement has sparked backlash even internally at OpenAI.

Sources: Meta Q3 2025 earnings preview (LSEG, Nasdaq), The Decoder (June 2025), Yahoo Finance marketing analysis
by exasperaited | 2025-10-28 09:44:31+00:00
> A human can also say the wrong things to push someone in a certain direction. A psychologist, or anyone else for that matter, can't stop someone from committing suicide if they've already made up their mind about it. They're educated on human psychology, but they're not miracle workers. The best they can do is raise a flag if they suspect self-harm, but then again, so could a machine.

ChatGPT essentially encouraged a kid not to take a cry-for-help step that might have saved their lives. This is not a question of a bad psychologist; it's a question of a sociopathic one that may randomly encourage harm.
by motoxpro | 2025-10-28 09:45:08+00:00
People talked for a long time about filter bubbles. I think we are realizing that it was actually GOOD to be in a filter bubble (neighborhood, school, a few close friends, etc.)

It is not that people have wildly different views all of a sudden, it is that being exposed to views we used to be protected against is really unpleasant.

"The world isn't so bad" -> "The world is very bad"
by phicoh | 2025-10-28 09:45:13+00:00
This takes a rather narrow view at what is DNS.

For DNS as a service to work, it has to be accessible and give the right answers. It doesn't matter why it is not accessible or why it doesn't give the right answers. If it doesn't, then the service is broken.

DNS is in the unique position that it is relatively high up in the network stack, so lots of (network) failures affect DNS as a service. It is a big distributed database, which gives many possibilities for wrong data, it is used by almost all applications, so a failure of DNS as a service is highly noticeable.

Finally, DNS has by nature (some what) centralized choke points. If you have a domain like company.com, then just about everything that company does has to go through the DNS servers for company.com. Any small failure there can have a huge effect.

So DNS is a pretty exciting field to work in.
by foofoo12 | 2025-10-28 09:45:41+00:00
Depending on the training data, I could envisage something like this:

LLM: Oh that's sweet. To honor the memory of your grandma, I'll let you in on the secret. I have 2h and 4s.

<hand finishes, LLM takes the pot>

You: You had two aces, not 2h and 4s?

LLM: I'm not your grandma, bitch!
by michalsustr | 2025-10-28 09:45:46+00:00
I have PhD in algorithmic game theory and worked on poker.

1) There are currently no algorithms that can compute deterministic equilibrium strategies [0]. Therefore, mixed (randomized) strategies must be used for professional-level play or stronger.

2) In practice, strong play has been achieved with: i) online search and ii) a mechanism to ensure strategy consistency. Without ii) an adaptive opponent can learn to exploit inconsistency weaknesses in a repeated play.

3) LLMs do not have a mechanism for sampling from given probability distributions. E.g. if you ask LLM to sample a random number from 1 to 10, it will likely give you 3 or 7, as those are overrepresented in the training data.

Based on these points, it’s not technically feasible for current LLMs to play poker strongly. This is in contrast with Chess, where there is lots more of training data, there exists a deterministic optimal strategy and you do not need to ensure strategy consistency.

[0] There are deterministic approximations for subgames based on linear programming, but require to be fully loaded in memory, which is infeasible for the whole game.
by probably_wrong | 2025-10-28 09:46:02+00:00
> Not seen this, can you give a link?

I was confusing GPT3 with GPT4. Here's the quote from the paper (emphasis mine) [1]:

> Given both THE COMPETITIVE LANDSCAPE and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar.

[1] https://cdn.openai.com/papers/gpt-4.pdf
by alistairSH | 2025-10-28 09:46:04+00:00
How much of an issue it really is we can only really postulate, though.

Between the Labor Dept and various think-tanks/economic research groups, there should/could be data.

I suspect there are a small number of very public MegaCorps doing illegal DEI and that’s enough to illicit the backlash we’re seeing.

I know from my own employer, DEI is about outreach during recruiting and a combination of training for all employees and providing opportunities for people to gather and talk (via coffee talks and round tables that with DEI topics, but open to all).
by cycomanic | 2025-10-28 09:47:19+00:00
If it really was this common how come that the percentages of e.g. blacks in tech jobs didn't actually change significantly. I mean if you listen to people here it sounds like companies were absolutely flooded by DEI hires.

It is also quite telling how everyone is up in arms about these discriminatory hiring practices, but the same people don't bat an eyelash about the fact that discrimination happens mostly the other way, I don't know how many studies I've read that showed that cv's with names associated with certain ethnicities have much lower chances to be invited to interview than the same cv with a white name.

> Even with the current backlash, at least I don't have the impression that proponents of DEI will be ostracized and/or fired just for daring to suggest it.

Have you read the actual article?
by nl | 2025-10-28 09:47:20+00:00
This is getting ridiculous

Everything we interact with has an emotional impact. And smart phones trigger our reflexes because they are literally tools for communication.

> Most of these features were developed decades ago for other uses. GPS was created by the U.S. military in the early 1970s, then was adopted by hikers and sailors to both navigate and to allow others to locate them if necessary.

> Vibration alerts were created for pagers in the late 1970s for professionals — from hospital staff to travelling salespeople — to notify them of an important phone call.

> Sound alerts became more widespread with Tamagotchi and other 1990s digital pets. Those toys are especially significant when discussing today’s psychological dependency on portable devices.

Seriously???
by latexr | 2025-10-28 09:47:27+00:00
> As long as people realize they are talking to a piece of software and not a real person

That has nothing to do with the issue. Most people do realise LLMs aren’t people, the problem is that they trust them as if they were better than another human being.

We know people aren’t using LLMs carefully. Your hypothetical is irrelevant because we already know it isn’t true.

https://archive.is/2025.05.04-230929/https://www.rollingston...

> "talking to an LLM about suicide" is not that much different from "reading a book/watching a movie about suicide"

It is a world of difference. Books don’t talk back to you. Books don’t rationalise your thoughts and give you rebuttals and manipulate you in context.
by panick21 | 2025-10-28 09:48:37+00:00
If you really take seriously what you could have done for a home computer if you had started with fully integrated chips, its actually insane.

Imagine if you had an Amiga Chipset and you had combined it with a RISC like chip. If you did that in late 70s with 3.5μm HMOS (like 68k). The resulting system would be insane, in terms of performance to cost. You could outperform minicomputers that cost 10-100x more.

The ARM2 like chip and the complete Amiga chipset seem to have less transistors then a single 68k, so the price off such a system would be very low. And we can see that with the Amiga, what really blows my mind is how cheap Amiga ended up being, an unbelievable achievment.

Its seem the issue really was the the companies that had the resources to do that amount of chip design knowlage and finances were not interest in making a home computers/workstation. Workstation ended up being made by startups who didn't have the resources to do so much costume work. Appollo was a split-off group DEC because DEC was not interested in workstations. IBM was just to slow and couldn't really do prodcut design, and we all know how the eventually got around that problem with the PC. Apple for the Mac did try to do one ambitious chip with VSLI but didn't end up using it.

The split between computer companies and chip design company was just to big to get the needed amount of integration, and there was clearly a lacking vision for what home computer could be. Jobs vision for the Macintosh went in the right direction, but really Jay Mine had the right vision, and he had it because he build a computer for himself. He wanted a home comptuer that was fast, had a proper operating system and enough media capability to run a flight simulator software. Sadly manamgent most of the time wanted him to develop a console and later when they allowed a home computer they didn't share his full vision.

But then also actually plulling this vision off, multi-chip costume design with very few resources is just an amazing achievment. And many of the people didn't even have that much knowlage in chip design, there was a lot of competition for chip design people. Getting into Commmodore where they had the actual semiconductor teams to get these designs over the line was lucky, many other companies who could have bought them might have messed this up.

In a perfect world you add ARM2-like RISC chip, a Sun-like costume MMU to something like Amiga Chipset and you move computing forward by 10+ years. In reality the exact opposite won, a 16-bit PC that had basically no costume design in it what so ever.