MurphyA/hacker-news huggingface dataset:
by ben_w | 2025-05-05 22:16:27+00:00
Generality is a continuous value, not a boolean; turned out that "AGI" was poorly defined, and because of that most people were putting the cut-off threshold in different places.

Likewise for "intelligent", and even "artificial".

So no, ChatGPT can't drive a car*. But it knows more about car repairs, defensive driving, global road features (geoguesser), road signs in every language, and how to design safe roads, than I'm ever likely to.

* It can also run python scripts with machine vision stuff, but sadly that's still not sufficient to drive a car… well, to drive one safety, anyway.
by bluefirebrand | 2025-05-05 22:16:32+00:00
> Fast food workers aren't service-economy workers, they're making burgers back there.

What exactly do you consider the "service industry" if you don't consider food services (like restaurants and fast food) as part of it?

I suspect we have very different ideas of what "service industry" means

> Also see https://www.epi.org/blog/wage-growth-since-1979-has-not-been..

Did you even read the whole thing?

```Dropping “wage stagnation” as a descriptive term for the full post-1979 period doesn’t mean we think the wage problem for American workers has been solved. Wage growth in the post-1979 period has been slow and unequal, largely as a result of intentional policy decisions. This policy-induced wage suppression has stifled growth in living standards and generated inequality. The last five years saw rapid and welcome progress reversing some of these trends—but it will take a long time to heal the previous damage, even if the post-2019 momentum can be sustained, which looks very unlikely at the moment.```

Admitting there is a problem but saying "it isn't stagnation" is just splitting hairs.

"Wage growth has been slow and unequal, but it isn't stagnation!"

"policy-induced wage suppression has stifled growth in living standards and generated inequality" there was wage suppression but it's not stagnation!

What a stupid article.
by johnnyanmac | 2025-05-05 22:16:38+00:00
These projections about bad professor experience is exactly why colleges became so hyperconpetitive. The difference between a competitive (and not even exclusive level like Ivies) and a "semi-competitive" is night and day in terms of rigor, staff talent, and overall environment.

But sure, you're always going to find a few meh or bad professors. And they will stick out as much ad thr great professors
by mcphage | 2025-05-05 22:17:03+00:00
> The City of Chicago's argument was that something of ANY value, no matter how insignificant, would help an attacker exploit their system, and was therefore possible to keep secret under the FOIA law.

I’m glad that argument lost, since it totally subverts the purpose and intention of the FOIA. Any piece of information could be of value to some attacker, but that doesn’t outweigh the need for transparency.
by alganet | 2025-05-05 22:18:14+00:00
I think you actually stand in a "moving enemy" narrative.

Sometimes it's a celebrity, sometimes is a group, sometimes a concept. Spies, commies, AI, feminism. You like to feel like you're the one giving the cards, that you are important. If you fail doing that, you try to retcon it.

I also think you're human, and you're out of "invisible enemies" to wear. I could list all of them. The fact that you're nitpicking small things is not a sign that you are close, instead, it's a sign that you are out of ideas.

Did I make a correct profiling? (rethorical)
by mhuffman | 2025-05-05 22:19:03+00:00
I have heard that theory from some cybersecurity experts online but have never seen it substantiated in any way (by interviewing some scammers, for example) and frankly don't believe it.

The misspellings and grammatical errors (used to?) continue on the fake sites that are created to steal credentials, and the excuses for most of the reasoning regarding emails do not hold there.
by Cyphase | 2025-05-05 22:19:07+00:00
I've been seeing similar scams via PayPal. The scammers apparently add the target email address as a forwarding address on a compromised or created-for-purpose email account. And that bouncer email address is signed up for PayPal. So the scam email is actually from PayPal, bounced through some other inbox. The To name and address is of the bouncer email address PayPal sent it to.

One version involves sending money to someone with the PayPal account (so the target might think it was sent from their own account) with a "note" to the transaction recipient, which the target sees, which says PayPal has detected unusual activity and please call this phone number to request a refund.

Another involves a "Your ITEM NAME order is on its way" email where the item being ordered is called something like, "Some Company, Inc: Don't recognize the seller? Call us at SOME PHONE NUMBER".

A third is like the second, except it's a "You paid CURRENCY to SELLER" email. This one has the PayPal user's name at the top, so not as convincing perhaps.
by AlexCoventry | 2025-05-05 22:20:07+00:00
If you've only been using AI for a couple of weeks, that's quite likely a factor. AI services have been improving incredibly quickly, and many people have a bad impression of the whole field from a time when it was super promising, but basically unusable. I was pretty dismissive until a couple of months ago, myself.

I think the other reason people are hostile to the field is that they're scared it's going to make them economically redundant, because a tsunami of cheap, skilled labor is now towering over us. It's loss-aversion bias, basically. Many people are more focused on that risk than on the amazing things we're able to do with all that labor.
by Alupis | 2025-05-05 22:20:07+00:00
> Kubernetes is simply too resource-intensive to run on a $10/month VPS with just 1 shared vCPU and 2GB of RAM

I hate sounding like an Oracle shill, but Oracle Cloud's Free Tier is hands-down the most generous. It can support running quite a bit, including a small k8s cluster[1]. Their k8s backplane service is also free.

They'll give you 4 x ARM64 cores and 24GB of ram for free. You can split this into 1-4 nodes, depending on what you want.

[1] https://www.oracle.com/cloud/free/
by ivape | 2025-05-05 22:20:42+00:00
Enterprises have lots of data. They store it somewhere, and there are multiple vendors that provide such "credible" infrastructure for this type of storage. Think of it like, your dad says he's willing to get a dog, but only trusts these-five-animal-shelters and nothing else. That doesn't mean that's correct (that those are the only places to get a dog), it just means that's what he trusts. Databricks is most likely a unicorn because they have successfully sold the idea that they are one of those trusted vendors, like Snowflake.

The truth of the 2010s up until now is that every startup was a massive sales con job. The wealth of this industry is not truly built on incredible tech, but on the audacity of salesmanship. It's a billion-dollar con job. That's one of the reasons I take every ridiculous startup that launches quite seriously, because you have no idea just how audacious their sales people are. They can sell anything.

Your question is very fundamental, and the answer is just as raw and fundamental too. I would love it if some of these sales people actually reform and write tell-alls about how they conned so many large companies in their years of working. This content has got to be out there somewhere.
by Nuzzerino | 2025-05-05 22:20:46+00:00
Text can be a carrier for any type of signal. The problem gets reduced to that of an interface definition. It’s probably not going to be ideal for driving cars, but if the latency, signal quality, and accuracy is within acceptable constraints, what else is stopping it?

This doesn’t imply that it’s ideal for driving cars, but to say that it’s not capable of driving general intelligence is incorrect in my view.
by johnnyanmac | 2025-05-05 22:20:52+00:00
It works for enough that 99% of cheaters are weeded out. Perfection is the enemy of "good enough".

Also, always keep in mind the most underrated kind of cheater: the clearly smart kid who cheats to go from an A- to an A. That level of student can't be "caught" with tests because by all accounts they already know and have even mastered the material. The pressure at that level of competitiveness simply requires zero room for doubt. Not really what the article is about, but some food for thought.
by godelski | 2025-05-05 22:20:54+00:00
Look back at the thread:

- ebiester claimed academia made itself the gatekeeper of credentials - alpinisme suggested that was silly. Employers have autonomy - you asked why MOOC classes don't get the same credentials - I said you missed alpinisme's point. The employer is the one that is deciding those credentials are not equal. I also pointed out how the same is true about different universities. Pointing out that you didn't need to say "MOOC" when "Stanford vs University of Wyoming" also leads to the same conclusion (which makes it weirder to point to academia as a whole instead of the prestigious unis) - you act like I was supposed to have read a reply to a different person while not addressing my point - I double down saying you're barking up the wrong tree. Take the finger and point it at employers - you say you never claimed employers aren't the problem and I'm creating a narrative

Well you're right, you never claimed that. But ebiester did and when alpinisme called bullshit you came to ebiester's defense. Forgive me if I got confused.

Regardless, it still doesn't change the fact that the employers have complete autonomy. They can make whatever rules they want. There's no use to pointing at academia because ultimately they have no say. Do they want to be the credential keepers, yeah! Which also means they'll be happy to be the ones being yelled at if the result is that employers keep using them as credential makers.

Ultimately academia is about prestige. Ultimately it's about far more than "the product" (the credential). But who decides what credential is best? The fucking employers. No one is holding a gun to their head. There's no front door or back door dealings.

You have concluded that since academia benefits from the employers selecting them as credential makers that they are the problem, or a meaningful part. The issue is, if you take away academia, the problem doesn't get resolved. Nor does it improve. Arguably, it becomes more noisy until employers converge onto some other arbitrary credential
by EdwinFeinberg | 2025-05-05 22:21:03+00:00
Hey guys i’ve been building a spiritual AI that lets you talk to a Rabbi, Pastor, Imam, or Monk (more to come). Not to debate religion, but to offer calm, wise, and nonjudgmental perspectives when you're searching for meaning, struggling, or just curious. Like many people in our generation, I’ve felt both drawn to and disconnected from religion. I built this because I wanted a way to reconnect with the wisdom religion offers without the dogma. I wanted to be able to ask deep, hard questions and get responses that feel thoughtful, grounded, and diverse. There is no account needed, no preaching; just a way to have a conversation with the best of what these traditions offer. Looking forward to your thoughts and critiques!
by wkat4242 | 2025-05-05 22:21:32+00:00
Yeah DoH was a solution to a really niche US-only problem where their laws provided the ability for providers to sell their users' DNS logs. In normal countries with privacy protections this isn't a thing anyway.

In this model, DoH is only a bad thing because it evades local DNS control.

I know that apps can always roll their own or even hardcode servers, but I hate the way that DoH was seen as some kind of saviour even though it adds zero benefit to European users and only adds negatives.
by dayvigo | 2025-05-05 22:22:15+00:00
There's also an argument that developers of new software, including libraries, should consider making an earnest attempt to do The Right Thing instead of re-implementing old, flawed designs and APIs for familiarity's sake. We have enough regression to the mean already.

The more LLMs are entrenched and required, the less we're able to do The Right Thing in the future. Time will be frozen, and we'll be stuck with the current mean forever. LLMs are notoriously bad at understanding anything that isn't mappable in some way to pre-existing constructs.

> for no especially good reason

That's a major qualifier.
by aeternum | 2025-05-05 22:22:48+00:00
Remember however that their charter specifies: "If a value-aligned, safety-conscious project comes close to building AGI before we do, we commit to stop competing with and start assisting this project"

It does have some weasel words around value-aligned and safety-conscious which they can always argue but this could get interesting because they've basically agreed not to compete. A fairly insane thing to do in retrospect.
by lossolo | 2025-05-05 22:22:51+00:00
> AGI is already here

Last time I checked, in an Anthropic paper, they asked the model to count something. They examined the logits and a graph showing how it arrived at the answer. Then they asked the model to explain its reasoning, and it gave a completely different explanation, because that was the most statistically probable response to the question. Does that seem like AGI to you?
by beAbU | 2025-05-05 22:23:43+00:00
I'd say its about 50/50 for me encountering testimonials that come accross as clearly fake. These are most easy to spot where the seller is hyper local, but the reviews are from obviously not local-sounding names. But then I do come accross testimonials that appear legit, and they do help with my buying decisions.

I would often rely on a Google review of the seller to determine whether or not it's an outright scam, and for hobby related stuff I might rely on forums where fellow forum goers might recommend a specific product/service.

So basically for me personally I would prefer independent 3rd party ratings/reviews/recommendations, but at this point I'm even a bit allergic to things like trustpilot, as I fear for incentives that are profit aligned rather than customer trust aligned.
by int_19h | 2025-05-05 22:24:10+00:00
And the benefits derived from that. When the consequence for the elites of losing the fight for political power is being targeted personally, imprisoned, or even killed, it makes them cling to power using much more brutal and violent means to avoid this fate, which means more repression for the average folk as well - no dissent can be tolerated. In a modern liberal democracy, they know that they can lose an election cycle without losing their head.

This is why things are so concerning in US - we've already lost this benefit, even though the elections are still genuinely free for now. I don't think they will remain so for long now that the stakes for their losers are so high.
by JadeNB | 2025-05-05 22:24:55+00:00
> "Almost all" in math can mean "except at every integer or fraction" :)

I am a mathematician, but, even so, I think that this is one of those instances where we have to admit that we have mangled everyday terminology when appropriating it, and so non-measure theoretic users should just ignore our definition. (Similarly with "group," where, at the risk of sounding tongue-in-cheek because it's so obvious, if I were trying to analyze how people usually understand its everyday meaning I wouldn't include the requirement that every element have an inverse.)
by axus | 2025-05-05 22:25:06+00:00
I felt the writer implied open source code was a bad/insecure thing, since they downloaded a zip file from some WordPress upload folder. I'm guessing the code was being made available to companies that "legally" obtained TM-SGNL.

His repo, not theirs: https://github.com/micahflee/TM-SGNL-Android/commits/master/

He points out that "You must license the entire work, as a whole, under this License to anyone who comes into possession of a copy."
by strken | 2025-05-05 22:25:07+00:00
Do you...not understand that the class on ethics in software development was completely pointless because it was neutered by a university administration that was too afraid to commit to any real ethical position?

I thought I was pretty clear when I told you I got marked down for taking the stance that one should not commit crimes when asked to by one's boss.

The problem isn't that I was asked to produce an essay as part of the process of teaching me about ethics. The problem is that the entire class was pointless busywork taught by lecturers who weren't particularly ethical and who failed to teach any of us about ethics. ChatGPT could have done the entire thing and the class would still have failed to leave me with anything other than lingering resentment.
by metalman | 2025-05-05 22:25:43+00:00
"partner in self~inquiry" eh? That is impossible. The self is a solo ride.Any inner voice speaks, unbiden. Introspection by definition, rejects all externalialitys. That said, there is another practice that may be a better fit for what you are describing, and in certain cultures the ultimate expression of this is for one person to put there head on anothers shoulder, as a litteral expression of the idea of I see what you see, which is what friends do for each other, sometimes after great effort, to not just understand something together, but to understand it in the same way. Or you go the hard route, and ride the beast alone, and know, what you know. And then there is the test by fire, but even then and forever, to see a truth is one thing, to hold it is another, but to wake up some other day and have it gone and not know, is still possible, so in a way, it is best to know nothing :)
by woodruffw | 2025-05-05 22:25:45+00:00
You'll note that this case caused exactly the kind of outcome I'm talking about: Pollard was an anomaly (to my knowledge, the only recorded case of a US citizen spying for a US ally) whose activities caused a massive intelligence break between US and Israel that lasted for years and probably did more damage than "good" it served for Israel's intelligence apparatus[1]. That kind of lesson is hard-learned and probably not forgotten, regardless of the fact that Pollard is a poster-boy in Israel's version of a culture war.

[1]: https://www.thedailybeast.com/israeli-spies-arent-exactly-re...
by triceratops | 2025-05-05 22:25:50+00:00
According to your link and this comment https://news.ycombinator.com/item?id=43899406 Google's scanning project was ruled fair use because it was "transformative" and didn't harm the market for the works. It allowed searching within books that was otherwise impossible at the time, but by not providing the full text of the books it didn't meaningfully reduce sales.

Someone photocopying a book to read on the toilet (and leave the original on their nightstand) isn't engaging in transformative use. They're also harming the market for the work because if they hadn't made this photocopy, they would've had to buy a second copy of the book to get the same benefit.
by -__---____-ZXyw | 2025-05-05 22:27:05+00:00
It seems no discussion of LLMs on HN these days is complete without a commenter wryly observing how that one specific issue someone is pointing to with an LLM is also, funnily enough, an issue they've seen with humans. The implication always seems to be that this somehow bolsters the idea that LLMs are therefore in some sense and to some degree human-like.

Humans not being infallible superintelligences does not mean that the thing that LLMs are doing is the same thing we do when we think, create, reason, etc. I would like to imagine that most serious people who use LLMs know this, but sometimes it's hard to be sure.

Is there a name for the "humans stupid --> LLMs smart" fallacy?
by kmacdough | 2025-05-05 22:27:16+00:00
>In the big picture, I think there aren't many hockey sticks/exponentials left in LLMs to discover. That is not true about other AI/ML.

We do appear to be hitting a cap on the current generation of auto-regressive LLMs, but this isn't a surprise to anyone on the frontier. The leaked conversations between Ilya, Sam and Elon from the early OpenAI days acknowledge they didn't have a clue as to architecture, only that scale was the key to making experiments even possible. No one expected this generation of LLMs to make it nearly this far. There's a general feeling of "quiet before the storm" in the industry, in anticipation of an architecture/training breakthrough, with a focus on more agentic, RL-centric training methods. But it's going to take a while for anyone to prove out an architecture sufficiently, train it at scale to be competitive with SOTA LLMs and perform enough post training, validation and red-teamint to be comfortable releasing to the public.

Current LLMs are years and hundreds of millions of dollars of training in. That's a very high bar for a new architecture, even if it significantly improves on LLMs.
by JadeNB | 2025-05-05 22:27:24+00:00
> I hate “one in a million” because its meaning depends on how many times you’re rolling the die!

I'd argue that it doesn't depend on that at all. That is, its meaning is the same whether you're performing the trial once, a million times, ten million times, or whatever. It's rather whether the implication is "the possibility may be disregarded" or "this should be expected to happen occasionally" that depends on how many times you're performing the trial.
by thamer | 2025-05-05 22:27:24+00:00
Does Dia support configuring voices now? I looked at it when it was first released, and you could only specify [S1] [S2] for the speakers, but not how they would sound.

There was also a very prominent issue where the voices would be sped up if the text was over a few sentences long; the longer the text, the faster it was spoken. One suggestion was to split the conversation into chunks with only one or two "turns" per speaker, but then you'd hear two voices then two more, then two more… with no way to configure any of it.

Dia looked cool on the surface when it was released, but it was only a demo for now and not at all usable for any real use case, even for a personal app. I'm sure they'll get to these issues eventually, but most comments I've seen so far recommending it are from people who have not actually used it or they would know of these major limitations.
by krackers | 2025-05-05 22:29:58+00:00
I can't tell if this is part of the bit, but is it intentional that your comment itself follows the classic chatgpt-ese structure of

<praise>

<elaboration>

<follow-up>

Assuming that the comment is truly written by a human, have you spent enough time with chatgpt that its cadence has been backpropagated into your mind?
by simonw | 2025-05-05 22:30:31+00:00
Maybe a partial solution here would be to offer some kind of "domain locking" option?

Allow sites that are heavy targets of this kind of scam - like ticketmaster - to add a "AdSense: locked" line to their robots.txt (or similar) - if that line is present then advertisers have to go through an additional domain verification step in order to place an ad.
by necovek | 2025-05-05 22:31:10+00:00
You seem to be arguing a point I never made: I never claimed LLMs are "dangerous", nor that crappy code only comes out of LLMs. They are just a tool, and I agree it is the responsibility of the developer wielding them to produce good work with (or without) them — this was never disputed.

I don't have any issue with someone using an LLM but I have not observed any efficiency gain from those who do — that's my entire point, and the biggest selling point for using coding assistants. I've either seen them produce "crappy code" faster (which, ultimately, they could do by hand as well), or be slower than doing their work "manually".

At the same time, I disagree about teams producing lousy PRs being mismanaged by definition: there are circumstances where doing that is warranted (LLM or no LLM), as long as the long term direction is improving (less crappy code over time). There are plenty of nuances there too.