MurphyA/hacker-news huggingface dataset:
by wakawaka28 | 2025-08-18 15:13:00+00:00
You are proving my point from up above. We both know you can afford $6 to feed yourself for a couple of days. Is that really such a luxury that a software engineer can't afford it? There is so much irony here, it's unreal. If you cry about house prices it's one thing, but saying it's the eggs being so expensive that really seals the deal on you not repaying your loans is completely disingenuous. Nevermind that these loans have no term in the contract saying that you will get any particular quality of life after spending that money... The entitlement reeks. I am halfway in agreement in that I hate how the economy is, but there's no reality in which you deserve to get all that money for free as more cautious people forgo college for backbreaking jobs.
by loudendiff | 2025-08-18 15:13:13+00:00
I am unsure if you are clever enough to know one is unable to prove a negative and so avoided asking the OP to prove that the profits failed to reach the public, or if you are brain dead enough to think asking someone to prove your own point is a valid debate technique.

The OP made it clear that one way the profits failed to reach the public is clear in how so many lost their homes due to foreclosure.

So, whether you can 'prove' that the profits did reach the public it seems obvious that one way they failed to reach the public was in protecting the public from these bad financial contracts.
by surajkrajan | 2025-08-18 15:13:17+00:00
Some technical details - Under the hood, JAIPilot uses IntelliJ’s PSI for code context extraction and wraps Gemini in an agentic retry loop until the generated tests compile. Code here : https://github.com/skrcode/java-auto-unit-tests

Would be very interested to hear if anyone has tried different approaches for reliable AI-generated tests.
by haizhung | 2025-08-18 15:13:38+00:00
Curious to see that no one mentions the drastically rising inequality in western society as the root cause of the housing crises.

What we are seeing to date is a transfer of wealth from the working class, the middle class, and the government to rich people at a rate that is unprecedented in human history. The rich are getting richer at an extremely high rate, and barely any country taxes wealth.

So what you get is multimillionaires and billionaires who get passive income of several million dollars per month. What are they going to do with that money? There is a rule that you should let your money work for you, and so rich people buy: assets, stock, shares.

That’s why the prices of all of these things go up despite living standards falling and falling for ordinary people. We have an asset price inflation, due to the enormous amount of money given to the ultra rich.

Housing prices will never go down unless you tax the rich. Regardless of zoning laws or what not.
by luke-stanley | 2025-08-18 15:13:41+00:00
Yeah, OpenAI do have harmfulness classifiers in ChatGPT that can detect problems in their own responses before it finishes, and learning how confident GPT-5 or the image generator tool call should be about meeting the brief, after it finishes describing the visual concept, might be a task OpenAI could train a classifier on. But reliably predicting ahead of time can be a really hard problem to solve; knowing how successful a complicated tool will be, before it actually starts or finishes the task attempt is tricky.

After gpt-image-1 has produced an image is another helpful intervention point, it can do a better self-review for detecting problems after image generation, but it's still not very thorough. However OpenAI has small teams, they try to keep them small and really focused, and everything is always changing really fast, they probably have gpt-image-2 or something else soon anyway.

In a way, reliable prediction is the main job OpenAI has to solve, and always has been. Some researches say the main way models are trained causes "Entangled Representations", which makes them unreliable. They also suffer from the "Reverse Curse". Maybe when they fix these issues, it might be real AGI and ASI all in one go?
by Benjammer | 2025-08-18 15:13:50+00:00
Why is the "threshold" argument never the first thing mentioned? Do you not understand what I'm saying here? Can you explain why the "code slop" argument is _always_ the first thing that people mention, without discussing this threshold?

Every post like this has a tone like they are describing a new phenomenon caused by AI, but it's just a normal professional code quality problem that has always existed.

Consider the difference between these two:

1. AI allows programmers to write sloppy code and commit things without fully checking/testing their code

2. AI greatly increases the speed at which code can be generated, but doesn't nearly improve as much the speed of reviewing code, so we're making software harder to verify

The second is a more accurate picture of what's happening, but comes off much less sensational in a social media post. When people post the 1st example, I discredit them immediately for trying to fear-monger and bait engagement rather than discussing the real problems with AI programming and how to prevent/solve them.
by mdaniel | 2025-08-18 15:14:02+00:00
Be the change you want to see in the world. Contributing .warc files to Archive.org isn't a gated club. My understanding of calling down the Warrior team is when something is time sensitive and needs to pseudo-ddos the site to get the bytes right now. Unless you know something about the demise of Gamefaqs, you have the rest of your life to archive a page at a time
by clickety_clack | 2025-08-18 15:14:12+00:00
This article doesn’t really seem to have any insight at all into Apple or Amazon’s AI strategies. The result that “Apple and Amazon will miss AI” seems to be a premise of the argument, and the rest of the article doesn’t really seem to even corroborate that.

Are phones and AI on the opposite ends of some axis where success in one precludes success in the other? Does the use of AI reduce the use of compute and data? I have my own opinions on the topic, but beyond the eye-catching title this article didn’t inform one way or the other.
by klabb3 | 2025-08-18 15:14:22+00:00
Before AI, you needed to trust the recipient and the provider (Gmail, Signal, WhatsApp, discord). You could at least make educated guesses about both for the risk profile. Such as: if someone leaks the code to this repo, it’s likely a collaborator or GitHub.

Today, you invite someone to a private repo and the code gets exfiltrated by a collaborator running whatever AI tool simply by opening their IDE.

Or you send someone an e2ee message on Signal but their AI reads the screen/text to summarize and now that message is exfiltrated.

Yes, I know it’s ”nothing new” ”in principle this could happen because you don’t control the client”. But opsec is also about what happens when well-meaning participants being accomplices in data collection. I used to trust that my friends enough to not share our conversations. Now the default assumption is that text & media on even private messaging will be harvested.

Personally I’m not ever giving keys to the kingdom to a remote data-hungry company, no matter how reputable. I’ll reconsider when local or self-hosted AI is available.
by notyourwork | 2025-08-18 15:14:29+00:00
I can see this. We employ a lot of off shore for what we call support engineering. Things like jdk upgrades or cert updates. It’s grunt work that lets higher paid engineers utilize their time on business value work. As AI continues to grow in scope, it will surely commandeer much of this. Employing a human is more expensive when compared to compute for these tasks at a certain scale.
by taneq | 2025-08-18 15:14:31+00:00
Huh, interesting. I periodically ask Siri "hey siri, are you actually smart yet?" (or variants on this depending on how I feel). So far I've always received a polite "I'm sorry, I don't know how to do that". No worries, you'll get there.

It's funny how the unexpected is way more impressive. I tried out the voice commands on my new car (BYD) and after it correctly interpreted and implemented my request, I politely said "thank you!" (as I always do, it's important to set a good example) and the car responded "you're welcome!". 100% could just have been a lucky setup for a scripted response... but...
by mediumdeviation | 2025-08-18 15:14:32+00:00
There’s some discussion in the specs here https://w3c.github.io/webappsec-secure-contexts/#is-origin-t...

> In particular, the user agent SHOULD treat file URLs as potentially trustworthy.

> User agents which prioritize security over such niceties MAY choose to more strictly assign trust in a way which excludes file.

A potentially trustworthy URL is a secure context: https://html.spec.whatwg.org/multipage/webappapis.html#secur...

So this is a matter of browsers not implementing it, probably because there’s just not a lot of demand for it.
by mdhb | 2025-08-18 15:14:59+00:00
If a person had said the exact same things that Meta went out of their way to write down in their own documentation as “acceptable” they would be charged with solicitation of a minor and it wouldn’t be a close call.

Honestly, people who work at Meta need to feel more consequences of their decision to do so in my opinion. That organisation is without any doubt whatsoever a net negative to society.
by kazanz | 2025-08-18 15:16:17+00:00
I'm going to second the Syself (https://syself.com) recommendation.

We're running our entire PaaS platform (Sherpa.sh) on top of Hetzner with Syself. We are 5x more affordable than Vercel and a big piece of that is because Syself allows us to operate autoscaling k8s clusters without an army of ops engineers.

We tried hetzner-k3s, and many other solutions. But ran into many of these same problems. Syself on the other hand, has solved all the sticky hardware and networking challenges at scale with their own customer operators. Plus they're support is super responsive and helpful.

The one downside, is they don't have a dashboard yet, so you need to be comfortable in the CLI. But I'm sure they are working on it.

I don't think I would manage kubernetes any other way at this point.
by hearsathought | 2025-08-18 15:16:37+00:00
> people have been eating mostly plant based foods in both the Mediterranean and India for thousands of years.

Since when have people of the mediterranean and indian been "mostly plant based" for thousands of years? Most indians eat meat ( and the percentage is increasing as indians become wealthier and can afford meat ). Most people throughout the mediterranean eat meat. Why is it that the vegan community goes out of their way to fetishize cultures and lie about them relentlessly? Just because greeks eat salad doesn't mean they are "mostly plant based".
by infecto | 2025-08-18 15:16:49+00:00
I hear opinions like yours often but I am not sure it’s simple or that the reasons you’re citing are grounded in reality.

What is the alternative, have a state imposed monopoly with a single power company like PGE who I would not see as an ideal operator either. Same can be true for a lot of other similar generators across the company.

You’ll probably bring up the winter storm outage which is inexcusable but their neighbor to the north SPP had very similar failings in being prepared and only faired better because they have interconnects.

Texas has had some of the fastest adoption for wind and solar. It is far from perfect but I also think there is benefit to having multiple generation companies supplying to the grid. You have companies with different expertise and perhaps innovation.
by michaelfm1211 | 2025-08-18 15:17:59+00:00
> The data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automation—eliminating business process outsourcing, cutting external agency costs, and streamlining operations.

Makes sense. The people in charge of setting AI initiatives and policies are office people and managers who could be easily replaced by AI, but the people in charge not going to let themselves be replaced. Salesmen and engineers are the hardest to replace, yet they aren't in charge so they get replaced the fastest.
by jmyeet | 2025-08-18 15:18:11+00:00
AI is going to force the issue of having to deal with the inequity in our economic system. And my belief is that this confrontation will be violent and many people are going to die.

The fundamental issue is wealth inequality. The ultimate forms of wealth redistribution are war and revolution. I personally believe we are already beyond the point where electoral politics can solve this issue and a violent resolution is inevitable.

The issue is that there are a handful of people who are incredibly wealthy and are only getting wealthier. The majority of the population is struggling to survive and only getting poorer.

AI and automation will be used to further displace working people to eke out a tiny percentage increase in profits, which will furhter this inequality as people can no longer afford to live. Plus those still working will have their wages suppressed.

Offshored work originally dsiplaced local workers and created a bunch of problems. AI and automation is a rising tide at this point. Many in tech considered themselves immune to such trends, being highly technical and educated professionals. Those people are in for a very rude shock and it'll happen sooner than they think.

Our politics is divided by those who want to blame marginalized groups (eg immigrants, trans people, "woke" liberals) for declining material conditions (and thus we get Brownshirts and concentration camps) and the other side who wants to defend the neoliberal status quo in the name of institutional norms.

It's about economics, material conditions and, dare I say it, the workers relationship to the means of production.
by lan321 | 2025-08-18 15:18:35+00:00
It takes forever to make a beautiful diagram, but the usual flow is that you have your presentation for the base idea, and then when the questions come, you can all grab a marker and start making a mess on the boards around the room. We also have one in the dev room, which is nice for smaller topics.

It's not meant to be the actual documentation, and it makes sense to me since you don't want to write the actual documentation during the discussion with multiple highly paid devs and managers. Just take a photo at the end, and it's saved for when you make the documentation.
by brantmv | 2025-08-18 15:18:43+00:00
Mathematicians are afraid of higher order tensors because they are unruly monsters.

There's a whole workshop of useful matrix tools. Decompositions, spectral theory, etc. These tools really break down when you generalize them to k-tensors. Even basic concepts like rank become sticky. (Iirc, the set of 3-tensors of tensor rank ≤k is not even topologically closed in general. Terrifying.) If you hand me some random 5-tensor, it's quite difficult to begin to understand it without somehow turning it into a matrix first by flattening or slicing or whatever.

Don't get me wrong. People work with these things. They do their best. But in general, mathematicians are afraid of higher order tensors. You should be too.
by agloe_dreams | 2025-08-18 15:19:36+00:00
Nobody actually wants half the useless tools companies are coming up with because most of the solutions are not really novel. They are just wrapping an LLM.

It's kinda like what I realized with the meta Ray-Bans: I can have these things on my face, they can tell me the answer to virtually any question in 10 seconds or less.

But I, as a human, rarely have questions to ask. When you walk in to your local grocery store - you generally know what you want and where to find it. A ton of companies are just gluing LLM text boxes into apps and then scratching their heads when people don't use them.

Why?

Because the customer wasn't the user - it was their boss and shareholders. It was all done to make someone else think 'woah, they are following the trend!'.

The core issue with generative AI is that it all works best when focused in a narrow sense. There is like one or two really clever uses I've seen - disappointingly, one of them was Jira. The internal jargon dictionary tool was legitimately impressive. Will it make any more money? Probably not.
by morkalork | 2025-08-18 15:20:04+00:00
In my experience is that LLMs get you 80%of the way to a solution almost immediately but that last 20% when it comes to missing knowledge, data, or accuracy is a complete tar pit and will wreck adoption. Especially since many vendors are selling products that are wrappers and provide generic, non-customised solutions. I hear the same from others doing trials with various AI tools as well.
by ModernMech | 2025-08-18 15:20:16+00:00
> But to hear 95% of these efforts don't have a demonstrable effect is just wild.

Why tho? You used AI to make some software, but did you use AI to achieve rapid revenue acceleration?

That you used AI to build software seems tangential to whether it can increase revenues. Over the years, we've seen many technologies that didn't deliver on promises of rapidly increasing revenues despite being useful for creating software (cough OOP cough), so this new one failing to live up to expectations isn't surprising. Actually given the history of technologies that over promise and under deliver on massive hype, disappointment should be the null hypothesis.
by mdaniel | 2025-08-18 15:20:21+00:00
> AWS I know manufactures its own CPUs, but I don't know if they're working on or already have an AI accelerator

I believe those are the Inferentia: https://aws.amazon.com/ai/machine-learning/inferentia/

> AWS Inferentia chips are designed by AWS to deliver high performance at the lowest cost in Amazon EC2 for your deep learning (DL) and generative AI inference applications

but I don't know this second if they're supported by the major frameworks, or what

I also didn't recall about https://aws.amazon.com/ai/machine-learning/trainium/ until I was looking up that page, so it seems they're trying to have a competitor to the TPUs just naming them dumb, because AWS

> AWS Trainium chips are a family of AI chips purpose built by AWS for AI training and inference to deliver high performance while reducing costs.
by softwaredam | 2025-08-18 15:20:43+00:00
To me this seems more than a side project. Really well done.

Nowadays, Hetzner has many Kubernetes providers. One that I really like is Syself.com. They provide production-ready Kubernetes including self-healing, bare-metal support, OIDC integration and many more.

As a cloud and migration expert, I have evaluated them and they turned out to perform very well.
by kelseyfrog | 2025-08-18 15:21:53+00:00
Structured output generally gives a nice performance boost, so I agree.

Specifically, I'd love to see widespread structured output support for context free grammars. You get a few here and there - vLLM for example. Most LLMs as a service only support JSON output which is better than nothing but doesn't cover this case at all.

Something with semantic analysis - scope informed output, would be a cherry on the top, but while technically possible, I don't see arriving anytime soon. But hey - maybe an opportunity for product differentiation.
by cholantesh | 2025-08-18 15:21:58+00:00
They can be, but given how many times Israel's made the assertion only to go "oopsie doodle, our multibillion dollar intelligence apparatus made a boo-boo and it turns out that there actually was not an installation under this civilian infrastructure", this isn't as robust a premise as you think it is. Anyway, the quality of evidence seems to suffice for doctors, NGOs, human rights watchdogs, practically anyone who isn't an Israeli official or an apologist thereof, probably something worth considering.
by dkarl | 2025-08-18 15:22:22+00:00
> SMILE... is severely more expensive

This is the first I've heard of this. In my area it seems comparable in price, within 1.5x the cost of LASIK. Considering how relatively cheap it is (a couple months' rent, or a fraction of the price of a car, to correct your vision for decades) I've never seen cost mentioned as reason to choose one over the other.
by gus_massa | 2025-08-18 15:22:24+00:00
Nice, but when I double click I get too many sparkles for my laptop. The animation went at 2fps. Perhaps you can try to detect how fast is the computer and adjust the amount of graphics.

Anti feature request: I'm too interested in Physics, so I expect a delay of the sound after the explosion. But if you implement that, everyone else will complain :(
by toss1 | 2025-08-18 15:22:54+00:00
I hope Kristopher Kortright stays well. He's done great work here.

But it seems a major OpSec flaw to allow one's identity to be publicized after cracking into the wartime systems of a genocidally aggressive state known for epidemic levels of "window cancer" and killing people on other nations territory using exotic and non-exotic means (polonium tes, nerve agents, or just dozens of bullets and running over with at truck, all well-publicized Russian murders)...
by brettgriffin | 2025-08-18 15:23:21+00:00
> Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don’t learn from or adapt to workflows, Challapally explained.

Maybe I misunderstood this, but I took this to mean that people inside enterprises are struggling using tools like ChatGPT. They do point out that perhaps the tools are being deployed in the wrong areas:

> The data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automation—eliminating business process outsourcing, cutting external agency costs, and streamlining operations.

But I've seen some amazing automation does in sales and marketing that directly affected sales efficiency and reduced sales and marketing expenses.
by lucasluitjes | 2025-08-18 15:23:29+00:00
> I have recently written security-sensitive code using Opus 4. I of course reviewed every line and made lots of both manual and prompt-based revisions.

> Cloudflare apparently did something similar recently.

Sure, LLMs don't magically remove your ability to audit code. But the way they're currently being used, do they make the average dev more or less likely to introduce vulnerabilities?

By the way, a cursory look [0] revealed a number of security issues with that Cloudflare OAuth library. None directly exploitable, but not something you want in your most security-critical code either.

[0] https://neilmadden.blog/2025/06/06/a-look-at-cloudflares-ai-...
by jacquesm | 2025-08-18 15:23:33+00:00
That's interesting. I won't be trying them though, I hate frames, it is bad enough with frameless but frames really spoil it for me. One brand in particular that I've found makes glasses that are almost invisible to me when I'm wearing them and that's the one that I've stuck with for the last couple of years. If the tech described here comes to general availability I'll be super happy.