MurphyA/hacker-news huggingface dataset:
by jazzyjackson | 2025-09-06 17:16:59+00:00
I wish I could fund an as campaign to free people from the perception that ads are to sell you products

Ads are there to change your behavior to make you more likely to buy products, e.g., put downward pressure on your self esteem to make you feel "less than" unless you live a lifestyle that happens to involve buying X product

They are not made in your best interest, they are adverserial psycho-tech that have a side effect of building a economic and political profile on you for whoever needs to know what messaging might resonate with you
by vintermann | 2025-09-06 17:17:36+00:00
I'm as red as they come in economic matters, but I never saw any reason to doubt the frequent assertion that stock buybacks and dividends are functionally the same.

Nor do I, in principle, see any problem with paying dividends: it's precisely because nothing grows into heaven. There should come in any company a time where it's grown enough that it doesn't have room to grow as much anymore, and can pay back its investors. Those investors these days will pretty much always reinvest in something else (because they are so rich, actually eating the dividend just isn't feasible). It's just reallocation from a venture which says "I can't grow as much as I used to" to other ventures.

(In theory, at least. I do see e.g. the notoriously fabulously capital intensive semiconductor manufacturers paying dividends/doing buybacks at the same time as begging governments for money, which makes me wonder if their actual business is what they say their business is. But never mind).

I also had no problem with the related concept that a business should usually have plenty of loans, and should not repay them. As a greedy investor, I think it's great that my company gets most of its money for expansion from the bank, because the bank in theory only demands to be repaid once, and in any case only demands a fixed %, whereas me and my greedy investor colleagues demand more money the more profit the company makes, and demand to be paid in perpetuity. Clearly, I prefer that the company is mostly financed by the comparatively less greedy bank, and only by my rival super-greedy investors as much as it absolutely has to.
by lif | 2025-09-06 17:18:00+00:00
thanks for asking! so: 4 day work week model (look up Iceland for an example of this)

And yes, 4 hours/day in the morning, intent here is just for most mentally demanding work to take place then

Overall, the above is to serve as a core time structure/focus principle (so to be clear, am NOT claiming ALL types/levels of work can be fitted into just 16h/wk -- tho ~30h/wk is worth striving for, imo)

the idea is to optimize for quality, and grind as needed in the later part of the work day.
by bko | 2025-09-06 17:18:01+00:00
>If someone wants extraordinary hours they need to be providing extraordinary compensation.

That's a naive approach. If you're in a place where people are fanatically devoted to the mission, it's a benefit in it of itself.

First you'll learn a lot. Residency is often grueling in terms of hours. The payout is much later as you learn more.

Also you're surrounded by very smart hard working people. Every high achiever I know hates working with low achievers or people who are lazy, incompetent or don't care. This is selection. So you learn a lot, in a very intense way, you'll learn a lot from smart people in a very short period of time.

But the most important thing I learned is that there is a huge universe of knowledge you can't learn from books or derive logically. You would learn more doing 996 following around a high performer over a short period of time than you would from years of school.

Some people like doing hard things. People do Ironmans and marathons, they train months for them and what do they get in return? Some endurance and strength that will dissipate within months of the end.

Finally it depends on your stage in life. If you're coming out of college, I would definitely recommend doing the most challenging thing you can find in your area of interest. If you have a family and kids, maybe pull back a bit.
by bezier-curve | 2025-09-06 17:18:48+00:00
This type of story kind of summarizes my feelings towards these mega rich people in general, it's not a coincidence they're spending most of their time self-preserving and building bunkers [1].

[1] https://www.wired.com/story/mark-zuckerberg-inside-hawaii-co...

Edit: Fascinating seeing downvotes over an insightful comment simply calling out the self-absorbed nature of billionaires. Have fun with that, probably my last comment on HN. This place is a circle jerk for techbros with charasmatic professional moderators that algorithmically punish the very things their own guidelines support. Waste of sincere people's time.
by cshores | 2025-09-06 17:18:50+00:00
I generally agree, but I think there is a real disconnect. Middle and upper management often do not understand how developers and engineers are actually supposed to use these tools.

For example, I work in operations, so most of what I touch is bash, Ansible, Terraform, GitHub workflows and actions, and some Python. Recently, our development team demonstrated a proposed strategy to use GitHub Copilot: assign it a JIRA ticket, let it generate code within our repos, and then have it automatically come back with a pull request.

That approach makes sense if you are building web or client-side applications. My team, however, focuses on infrastructure configuration code. It is software in the sense that we are managing discrete components that interact, but not in a way where you can simply hand off a task, run tests, and expect a PR to appear.

Large language models are more like asking a genie. Even if you give perfectly clear instructions, the result is often not exactly what you wanted. That is why I use Copilot and Gemini Code Assist in VS Code as assistive tools. I guide them step by step, and when they go off track, I can nudge them back in the right direction.

To me, that highlights the gap between management’s expectations and the reality of how these tools actually work in practice.
by cousin_it | 2025-09-06 17:19:11+00:00
The ads won't be for the product which will bring you maximum value. They will be for the product that will bring the advertiser maximum profit (for example, by manipulating you into buying something overpriced). The products which are really good and cheap, giving all their surplus value to you and just a little bit to the maker, will lose the bidding for the ad slot.
by rightbyte | 2025-09-06 17:19:13+00:00
> I'm fundamentally a capitalist

Being a capitalist is decided by access to capital not really a belief system.

> But, there really is just too much concentrated wealth in these orgs.

Please make up your mind? Should capital self-accumulate and grant power or not?

Portraying capitalism as some sort of force of nature that one doesn't "know another system that will work better" might be the neoliberals biggest accomplishment.
by sacul | 2025-09-06 17:19:19+00:00
Yeah, thanks for asking. My reasoning is this:

That chatbot you're interacting with is not your friend. I take it as a fact (assumption? axiom?) that it can never be your friend. A friend is a human - animals, in some sense, can be friends - who has your best interests at heart. But in fact, that chatbot "is" a megacorp whose interests certainly aren't your interests - often, their interests are at odds with your interests.

Google works hard with branding and marketing to make people feel good about using their products. But, at the end of the day, it's reasonably easy to recognize that when you use their products, you are interacting with a megacorp.

Chatbots blur that line, and there is a huge incentive for the megacorps to make me feel like I'm interacting with a safe, trusted "friend" or even mentor. But... I'm not. In the end, it will always be me interacting with Microsoft or OpenAI or Google or whoever.

There are laws, and then there is culture. The laws for AI and surveillance capitalism need to be in place, and we need lawmakers who are informed and who are advocates for the regular people who need to be protected. But we also need to shift culture around technology use. Just like social customs have come in that put guard rails around smartphone usage, we need to establish social customs around AI.

AI is a super helpful tool, but it should never be treated as a human friend. It might trick us into thinking that its a friend, but it can never be or become a friend.
by aprilthird2021 | 2025-09-06 17:19:20+00:00
> This admission makes it clear that the AI spends are being made up not based on business value/demand...

Well, isn't that okay? All the companies are racing to capture a nascent market. It would make sense to spend beyond current demand and even projected 5Y demand if it gives you a larger share of a market that might last 20+ years
by skybrian | 2025-09-06 17:19:24+00:00
For nearly all open source projects, we are free riders. We use them and don’t contribute anything back. Open source is not about fair exchange; it’s about gift-giving and copying other people’s homework.

If you choose to give gifts to the world, that’s great, but you should go into it with your eyes open and not expect anything back. The world includes a lot of terrible people and you’re giving them gifts too. It’s okay to change your mind.

Calling it a “rug pull” when a software vendor relicenses seems like biased language. We still have all the gifts they gave us. It’s unfortunate that they changed direction, but nothing lasts forever.
by jeswin | 2025-09-06 17:19:27+00:00
> Lets establish some proof of value first

Recently spoke to someone who said that most startups in their (very large) portfolio are using AI to write most of their code. I personally know this to be true in several startups I've seen; and I've seen slow but steady adoption in larger companies.

We can debate about spending hundreds of billions per year, but the value is beyond question at this point at least in software.
by tikhonj | 2025-09-06 17:19:33+00:00
Performative hours are, fundamentally, a symptom of a lack of trust. A lack of trust in others but also a lack of trust in yourself.

Not trust others is pretty obvious: leaders push for long hours because they don't trust people to be intrinsically motivated or to work in the most effective way for them. If you assume people are inherently unmotivated and lazy, well, trackable hours and artificial pressure seem like the obvious consequence.

But it's also a sign of not trusting yourself. Being judged on outcomes—never fully under your control—is scary. Being judged on anything fuzzy or arguable—taste, experience, skill, insight—is scary. If you're the sort of person who is content to "grind", the best way to win competitions is to turn them into grinding competitions. You can't be confident that you are more skilled, more intelligent or have better taste than others, but you can always just "grind" that extra hour. For a certain personality, time spent is by far the easiest metric to control.

If you grow up constantly being praised for how "hard" (read "long") you work, constantly out-competing people by doing more rather than better, the inherent value of "hard" work over everything becomes fundamentally ingrained in your personal story. And, unfortunately, our culture tends to put those people into positions of power, so this tendency gets reinforced and propagated.

Taking a step back, doing something good with less effort ought to be more impressive than doing it with more effort. That's what real potential looks like.

More importantly, even if working more hours purely increased your effectiveness and productivity—and we absolutely know that it doesn't—it would still be a weak form of leverage. Maybe you can work 2× the hours, but you can never work 10x. On the other hand, with taste and experience, you can absolutely come up with a 10× better design, or a 10× better understanding of what you're doing, and, unlike long hours, those 10× advantages compound.

If you trusted your own taste and creativity to give you the leverage you need, you wouldn't work ridiculous hours because you'd know it's counterproductive.

But when you don't, long hours are an easy, socially accepted fallback.
by dcminter | 2025-09-06 17:19:42+00:00
Sigh, enforced is always top down, sure, if you want to be pedantic. But normally the process starts with enthusiastic devs, propagates out through other devs until a consensus is reached (e.g. source control is the only sane way) and then management starts to enforce it - often with a crappy enterprise take on the basic idea (I'm looking at you IBM Team Connection and Microsoft Visual SourceSafe).

AI seems to have primarily been pushed top-down from management long before any consensus has been reached from the devs on what it's even good for.

This is unusual; I suspect the reason is that (for once) the tech is more suitable for management functions than the dev stuff. Judging from the amount of bulletpointese generation and condensation I've seen lately anyway.
by Jensson | 2025-09-06 17:19:54+00:00
That is wrong, I just generated 5 random letters in python and sent it to gpt-5 and it totally failed to answer properly, said "Got it, whats up :)" even though what I wrote isn't recognizable at all.

The "capability" you see is for the LLM to recognize its a human typed random string since human typed random strings are not very random. If you send it an actual random word then it typically fails.
by maxlin | 2025-09-06 17:20:54+00:00
This and that. FUD this FUD that. Tesla have communicated clearly why "adding" LiDAR isn't an improvement for a system with goals as high as their are. Remember, no vision system yet is as good as humans are with vision, so obviously there's a lot to do with vision still.

Check this for a reference of how well Tesla's vision-only fares against the competition, where many have LiDAR. Keep it simple wins the game. https://www.youtube.com/watch?v=0xumyEf-WRI
by simne | 2025-09-06 17:21:04+00:00
> using HLL as a metalanguage for generating low-level code

Unfortunately, this is very long known dead-end, because very few programs written evidence-based, but most just begin their life with first production release, and on some platforms (JVM), more than 90% of developer time spend to refactoring and maintenance of existing code, and many people don't know anything else.

So, templates are not enough to break through this wall, need infrastructure of libraries and debuggers, and may be macros, etc, designed specifically for fp and be at least on par with their imperative counterparts.
by adastra22 | 2025-09-06 17:21:55+00:00
That is half of it. The other half is that AI is tireless about planning. Most waterfall implementations fail from lack of planning, or when done right (think well managed government programs) are significantly delayed compared with agile because the planning process itself takes forever.

AI will happily spend the human equivalent of months getting the planning details right before implementation. It won’t by default, to be sure, but if prompted right it will. So you can go into a waterfall implantation plan with significantly better and more thought out plans.
by mrtksn | 2025-09-06 17:21:59+00:00
I thought this is obvious by now? It's just a show, no one is actually investing such money - this is to spice up the casino and run a news cycle for Trump.

I mean, just check the numbers they are throwing around, there's no such money and Elon Musk even called it out previously in the context of his spat with OpenAI(how much was that $500B on the stargate project?).

Everything is like that, EU is supposed to invest $600B in US but EU's yearly budget is $200B. Qatar is investing $1.2T but their GDP is $200B. Japan to invest in us $550B but they too don't have such money laying around. Saudi's to invest $600B, that's half of their GDP.

This is just part of the show and people figured that Trump likes multiples of $600B, just I wish it wasn't so damaging.
by vouwfietsman | 2025-09-06 17:22:03+00:00
I get that.

The point is that its hard to prevent asymmetry in message versions if you are working with many communicating systems. Lets say four services inter-communicate with some protocol, it is extremely annoying to impose a deployment order where the producer of a message type is the last to upgrade the message schema, as this causes unnecessary dependencies between the release trains of these services. At the same time, one cannot simply say: "I don't know this message version, I will disregard it" because in live systems this will mean the systems go out of sync, data is lost, stuff breaks, etc.

There's probably more issues I haven't mentioned, but long story short: in live, interconnected systems, it becomes important to have intelligent message versioning, i.e: a version number is not enough.
by citizenpaul | 2025-09-06 17:22:17+00:00
Lets not forget that Gabereial Weinburg is a two faced ghoul or wolf in sheep clothing. He has literally said he does not believe people need privacy yet that supposedly is the duckduckgo's main selling point. He has made all kinds of tracking deals with other companies so duckduckgo "is not tracking you" just their partners are.

Most of the controversial stuff he has done is being whitewashed from the internet and is now hard to find.
by oceanplexian | 2025-09-06 17:22:52+00:00
It’s probably not that hard to take the OSS models and fine tune them for CC. Which means with a little bit of reverse engineering and some free time you could get an open source models working perfectly with it.

Claude code router is a good first step. But you also need to MITM CC while it’s running and collect the back and forth for a while. I would do it if I had more free time, surprised someone smart hasn’t already tried.
by vineyardmike | 2025-09-06 17:23:13+00:00
To be fair, when he suggested $600Bn in spend by 2028, it’s obvious they won’t actually be spending that. That would exceed their yearly revenue each year. They just don’t have that money. This feels like less of an indictment of AI spend, and more of the political process of blatant lying for political favor.

For comparison, Google said $250b, Microsoft said $80b, but Apple has said $600bn. Meta currently spends ~$100bn.
by 627467 | 2025-09-06 17:23:16+00:00
What i keep seeing missing for AI-labor replacement discussions is that technology may seem to replace human labor, but it doesn't really replace human accountability.

Organizations many times seem capable to diffuse blame for mistakes within their human beaurocracy but as beaurocracy is reduced with AI, individuals become more exposed.

This alone - in my view - is sufficient counterpressure to fully replace humans in organizations.

Shorter reply: if my AI setup fails I'm the one to blame. If I do a bad job at helping coworkers perform better is the blame fully mine?
by freehorse | 2025-09-06 17:23:25+00:00
> What bothers me about the hot takes is the claim that “all models do is hallucinate.” That collapses the distinction entirely

That is a problem for "Open"AI because they want to sell their products, and because they want to claim that LLMs will scale to superintelligence. Not for others.

"Bad" hallucinations come in different forms, and what the article describes is one of them. Not all of them come from complete uncertainty. There are also the cases where the LLM is hallucinating functions in a library, or they reverse cause and effect when summarising a complex article. Stuff like this still happen all the time, even with SOTA models. They do not happen because the model is bad with uncertainty, they have nothing to do with knowledge uncertainty. Esp stuff like producing statements that misinterpret causal relationships within text, imo, reveals exactly the limits of the architectural approach.
by rozab | 2025-09-06 17:23:46+00:00
I recently watched Not Just Bikes' video on the disastrous future side effects of self-driving cars[0]. Of course it made me think about the massive PR push that made us think they were around the corner, but also about the manufactured consent for these technologies in the first place. Right now this kind of discussion is hitting the mainstream with the 'clanker'[1] backlash. I think it's really obvious to a lot of people that the AI push is not organic and is not based around consumer needs, and this manipulation is making people genuinely angry[2] (ok jreg is a performance artist, but just because something is performative doesn't mean it's not real).

[0]: https://youtu.be/040ejWnFkj0?si=7yI3eKkirJdTWPwR [1]: https://en.wikipedia.org/wiki/Clanker [2]: https://youtu.be/RpRRejhgtVI?si=aZUVcsY8VyR_jbBA
by HarHarVeryFunny | 2025-09-06 17:23:55+00:00
I disagree - I just had my non-technical sister staying with me, who said she was creeped out by "AI" and didn't like that it heard her in background while her son was talking to Gemini.

An LLM is, at the end of day, a next-word predictor, trying to predict according to training samples. We all understand that it's the depth/sophistication of context pattern matching that makes "stochastic parrot" an inadequate way to describe an LLM, but conceptually it is still more right than wrong, and is the base level of understanding you need, before beginning to understand why it is inadequate.

I think it's better for a non-technical person to understand "AI" as a stochastic parrot than to have zero understanding and think of it as a black box, or sentient computer, especially if that makes them afraid of it.
by hedora | 2025-09-06 17:23:57+00:00
A BMW i3 weighs about 3000 lbs. They’re mostly fiberglass and have a small battery. The center of gravity is probably comparable to the 911 even though it’s tall and goofy looking (all the weight is in the battery, under the seats).

The tire geometry causes a bit of oversteering, but they generally corner well, etc.
by ozim | 2025-09-06 17:24:59+00:00
Obviously just don’t forget aiming for where we see it now is not where it is and not where it will be in 100 years.

I have never seen anyone writing about us having solid reference points to travel that far in case we can reach those speeds.

If you miss you end up in some empty space you won’t be able to mine anything for fuel to have more shots.
by ozgung | 2025-09-06 17:25:34+00:00
You are right that it is a bold claim but here is a relevant summary: https://en.wikipedia.org/wiki/Stochastic_parrot#Interpretabi...

I think "The Platonic Representation Hypothesis" is also related: https://phillipi.github.io/prh/

Unfortunately, large LLMs like ChatGPT and Claude are blackbox for researchers. They can't probe what is going on inside those things.
by claytongulick | 2025-09-06 17:25:56+00:00
I think (hope?) that the best thing that will come from tye AI hype will be innovations in power creation and delivery.

If the unexpected side effect of building these giant stochastic parrots is that we usher in an age of decentralized, safe nuclear SMRs, it will have been well worth it, whether or not they are actual productivity boosters.
by gruez | 2025-09-06 17:26:15+00:00
>and more of the political process of blatant lying for political favor.

Even that's debatable because he walked back on the number shortly after

>Once the discussion concluded, Zuckerberg leaned over to Trump to privately admit the president had caught him off guard. "I'm sorry I wasn't ready...I wasn't sure what number you wanted to go with," Zuckerberg said in a revealing moment caught on a hot mic.
by maxlin | 2025-09-06 17:27:41+00:00
I think you hit the nail on the head - Obviously when Tesla have saturated the potential of vision, they should bring in LiDAR if it can be reasonably added from a hardware point of view. Their current arguments make this clear - it would be surface-level thinking to add LiDAR and the kitchen sink now, complicating the system's evolution and axing scalability.

But we're far from plateauing on what can be done with vision - Humans can drive quite well with essentially just sight, so we're far from extinguishing what can be done with it.