MurphyA/hacker-news huggingface dataset:
by chollida1 | 2025-06-05 18:08:26+00:00
I'd start to worry about OpenAI, from a valuation standpoint. The company has some serious competition now and is arguably no longer the leader.

its going to be interesting to see how easily they can raise more money. Their valuation is already in the $300B range. How much larger can it get given their relatively paltry revenue at the moment and increasingly rising costs for hardware and electricity.

If the next generation of llms needs new data sources, then Facebook and Google seem well positioned there, OpenAI on the other hand seems like its going to lose such race for proprietary data sets as unlike those other two, they don't have another business that generates such data.

When they were the leader in both research and in user facing applications they certainly deserved their lofty valuation.

What is new money coming into OpenAI getting now?

At even a $300B valuation a typical wall street analysts would want to value them at 2x sales which would mean they'd expect OpenAI to have $600B in annual sales to account for this valuation when they go public.

Or at an extremely lofty P/E ratio of say 100 that would be $3B in annual earnings, that analysts would have to expect you to double each year for the next 10ish years looking out, ala AMZN in the 2000s, to justify this valuation.

They seem to have boxed themselves into a corner where it will be painful to go public, assuming they can ever figure out the nonprofit/profit issue their company has.

Congrats to Google here, they have done great work and look like they'll be one of the biggest winners of the AI race.
by nailer | 2025-06-05 18:08:47+00:00
Yep, from https://the-decoder.com/reddit-ends-its-role-as-a-free-ai-tr... :

You must not, and must not allow those acting on your behalf to:

...use the Data APIs to encourage or promote illegal activity or violation of third party rights (including using User Content to train a machine learning or AI model without the express permission of rightsholders in the applicable User Content);
by lxe | 2025-06-05 18:09:48+00:00
Gemini is a good and fast model, but I think the style of code it writes is... amateur / inexperienced. It doesn't make a lot of mistakes typical of an LLM, but rather chooses approaches that are typical of someone who just learned programming. I have to always nudge it to avoid verbosity, keep structure less repetitive, optimize async code, etc. With claude, I rarely have this problem -- it feels more like working with a more experienced developer.
by citizenpaul | 2025-06-05 18:09:52+00:00
>Apparently, I'm wrong enough that there's hundreds of these stores in business.

The stuff in the bins is from amazon returns. Its not a business of its own supply choices. The people that run the stores go to amazon pallet auctions where they buy the stuff unseen and hope to turn a profit on the arbitrage of what they pay vs the worth of the pallet.
by overu589 | 2025-06-05 18:09:55+00:00
“can be” “often”

Delusional.

The karma neg for my thoughtful reply is repugnant.

Arguing with your LLM exhibits how things like “existential being” are ill defined and “they often reflect” is given as a reproachful lecture for exactly my point.

The Truth is a purturbation of existential reality period. There is no other. Ever.

A good math proof has a for instance.

A for instance is a Truth.

Your symbols are delusions.
by Ancapistani | 2025-06-05 18:10:12+00:00
I find it odd that you'd say that.

Everywhere I've ever lived or driven, the vast majority of people use them consistently - at least when appropriate. The most common place I see people not using them is when changing lanes, and then usually only if there's a vehicle in their target lane close enough that it would matter.

Do bad drivers exist? Obviously.

Actually, now that I really think about it, there are two places I've driven where I can recall seeing people merging and turning frequently without signaling: New York and Los Angeles.

In those cases, my guess is that it's partly cultural but predominantly driven by task saturation. When you're operating a vehicle at 80 MPH surrounded by other cars in rush hour traffic on a six-lane highway, sometimes you have to focus on staying alive.

Aviation has a saying that describes this: "Aviate, navigate, communicate". Basically, your first priority is to ensure the immediate safety of your vehicle. After that, you focus on identifying a clear path that doesn't conflict with the path of other vehicles. Only after those things are done do you worry about telling others what's going on. In the air that's the radio; in a car that's your turn signals and horn.

Here's the Wikipedia article talking about this in the context of aviation: https://en.wikipedia.org/wiki/Airmanship#Principles

If task saturation is actually what's happening here, then I would expect to see turn signal usage decrease as traffic density and speed increase. I bet, given the access to data like live traffic cameras that we have today and the current generation of multimodal generative AI models, I could whip up at least a first pass at measuring this without much time investment.

Great. Now I have yet another project :P
by CamperBob2 | 2025-06-05 18:10:16+00:00
We will all make a lot more money and a lot more progress by storing, organizing, presenting, and processing knowledge as effectively as possible.

Copyright is not a natural right by any measure; it's something we pulled out of our asses a couple hundred years ago in response to a need that existed at the time. To the extent copyright interferes with progress, as it appears to have sworn to do, it has to go.

Sorry. Don't shoot the messenger.
by diggan | 2025-06-05 18:10:18+00:00
> they will slowly become out of date and useless

Models released today are already useful for a bunch of stuff, maybe over the course of 100 year they could be considered "out of date", but they don't exactly bitrot by themselves because they sit on a disk, not sure why'd they suddenly "expire" or whatever you try to hint at.

And even over the course of 100 year, people will continue the machine learning science, regardless if it's legal or not, the potential benefits (for a select few) seems to be too good for people to ignore, which is why the current bubble is happening in the first place.
by fragmede | 2025-06-05 18:10:24+00:00
With ChatGPT Codex connected to GitHub it's pretty neat. From my phone I throw some tasks at it and go about my day and then check in with it later. After giving it some time, I come back and look at what it's done and kick off some more or look at diffs and create PRs right from my phone. It's fairly limited in what can be done from the phone so you'll need to have a laptop for anything more involved than eg spelling errors, but it's a very interesting view of the future.
by EvanAnderson | 2025-06-05 18:10:26+00:00
> The masses will always stay in the walled garden. It's where they want to be and they don't even realize there are walls. It is just what is for them.

The walls should have open doors, though, versus prison bars. Physical switches on devices (much like older Chromebook devices had) used to opt out of the walled garden should be mandated by consumer protection regulations.
by oneplane | 2025-06-05 18:10:35+00:00
TL;DR: profit (direct and/or indirect).

I don't know if they do, but I do know the universal answer to all of it: because that's what makes the big bucks. While there will always be inefficiencies and weird situations, multinationals that stick around for a long time and make lots of money do so because there are a bunch of people working there who have to figure out how to make money and keep making that money.
by brucefalck | 2025-06-05 18:10:42+00:00
There's a moment every engineer experiences when they realize the internet is held together with duct tape and good intentions. At Halcyon, our goal is to help make energy information more accessible and useful. That means, as a first step, we need to systematically and reliably discover, collect, and ingest that information from all its (many, many) different sources. As we marched to 50 state public utility commissions (PUCs), Halcyon’s engineering team has lived this duct-tape moment Groundhog Day-style for the last six+ months.
by LegionMammal978 | 2025-06-05 18:10:46+00:00
I think it's supposed to be safe in Ada by default? As far as I can tell, basic allocated objects cannot be deallocated without an "unchecked" operation, and access objects created from "aliased" declarations are subject to scoping rules [0]. (If you want to know the full details, go figure out however "accessibility levels" are supposed to work [1].) It should preclude functions from returning access objects without a "prefix'Unchecked_Access" operation. I'm not sure how SPARK's borrowing system is tied into all of this.

[0] https://www.adaic.org/resources/add_content/docs/craft/html/...

[1] http://www.ada-auth.org/standards/22rm/html/RM-3-10-2.html
by reify | 2025-06-05 18:11:09+00:00
there has never been Autonomy and Freedom, not from google, ever.

I have never ever used a fully loaded android phone with all the spying, surveillance apps and play services, amazon, facecrook, whatshit, running.

why on earth do muppets insist that they cannot live a life without google and the rest.

I have installed the latest AOSP on all my phones, including family aand friends.

I currently have a motorola edge 20 pro with android 15 installed. and my very old oneplus 5T also has android 15 installed.

all my family and friends have either lineage or E/os installed.

I dont see the problem here. I hear no complaints.

fool me once, More fool anyone who thinks google, facecrook and whatshit is their friend.

Autonomy for me, MEANS, self regulation. this is severely absent in the lives of the modern human being.
by TimorousBestie | 2025-06-05 18:11:14+00:00
I don’t think standard humans measure enough data to check the mass balance of their body’s system. I seem to remember an episode of CSI where that kind of behavior was used as evidence of an eating disorder.

Joking aside, being overweight is mostly about body density, not mass. Few people get upset about having too much lean muscle or the food inputs needed get there; that is a different set of health risks.

Whether your body converts incoming calories to muscle or fat or whatever else does actually depend (to some variable extent) on genetics, along with many other factors. Glossing this as “breaking the laws of physics” is a straw man.
Ask HN: What tools are you using for AI evals? Everything feels half-baked
by fazlerocks | 2025-06-05 18:11:53+00:00
We're running LLMs in production for content generation, customer support, and code review assistance. Been trying to build a proper evaluation pipeline for months but every tool we've tested has significant limitations.

What we've evaluated:

- OpenAI's Evals framework: Works well for benchmarking but challenging for custom use cases. Configuration through YAML files can be complex and extending functionality requires diving deep into their codebase. Primarily designed for batch processing rather than real-time monitoring.

- LangSmith: Strong tracing capabilities but eval features feel secondary to their observability focus. Pricing starts at $0.50 per 1k traces after the free tier, which adds up quickly with high volume. UI can be slow with larger datasets.

- Weights & Biases: Powerful platform but designed primarily for traditional ML experiment tracking. Setup is complex and requires significant ML expertise. Our product team struggles to use it effectively.

- Humanloop: Clean interface focused on prompt versioning with basic evaluation capabilities. Limited eval types available and pricing is steep for the feature set.

- Braintrust: Interesting approach to evaluation but feels like an early-stage product. Documentation is sparse and integration options are limited.

What we actually need: - Real-time eval monitoring (not just batch) - Custom eval functions that don't require PhD-level setup - Human-in-the-loop workflows for subjective tasks - Cost tracking per model/prompt - Integration with our existing observability stack - Something our product team can actually use

Current solution:

Custom scripts + monitoring dashboards for basic metrics. Weekly manual reviews in spreadsheets. It works but doesn't scale and we miss edge cases.

Has anyone found tools that handle production LLM evaluation well? Are we expecting too much or is the tooling genuinely immature? Especially interested in hearing from teams without dedicated ML engineers.
by evereverever | 2025-06-05 18:12:01+00:00
I was really impressed when I took a trip to England and it recognized european birds. At one point it said there was a Rose-ringed Parakeet which seemed totally wrong, but then we saw a bunch of them in Hyde park a couple days later.

The iOS app did seem to lock up when trying to download the region packs though. I should find out where to file a bug!
by gus_massa | 2025-06-05 18:12:39+00:00
I agree, for example Pepsin[1] that is the protein inside the stomach that split proteins has Cysteine [2]

> Pepsin forms three between the sulfur atoms of cysteine residues in the peptide chain which hold important roles in the folding of the protein and stabilizing the two domains

[1] https://en.wikipedia.org/wiki/Pepsin

[2] https://biology.kenyon.edu/BMB/jsmol2021/Cat_Marko/index.htm...
by Ancapistani | 2025-06-05 18:12:59+00:00
That's a great point!

Between that and the implementation of momentary signal activation - when you push the stalk just a bit, but not enough to "click" into place and stay there; it blinks ~3 times and stops - you have a nice carrot/stick pair.

It's annoying when the warning goes off when you change lanes without signaling AND it's easier to signal because you only have to tap the stalk once instead of twice.
by hansvm | 2025-06-05 18:13:15+00:00
The normal claim is a bit weaker, that under caloric restriction the body situationally reacts by doing a lot less work. You also see reports of reduced cognitive abilities and whatnot, consistent with lower energy expenditures.

I think those reports are overblown, especially with little mismeasurements on the order of 1Tbsp of butter or the fact that many foods have labeled calories 20% less than the actual caloric content, all of that combined with thinking that exercise is more impactful than it actually is (especially weight training), but the core claims aren't totally ludicrous at face value.
by soulofmischief | 2025-06-05 18:13:30+00:00
Why should it be a default? Can you prove that training a model on data you wrote is not fair use?

We're already seeing precedent that it might be.

https://www.ecjlaw.com/ecj-blog/kadrey-v-meta-the-first-majo...

The openness of the internet is a good thing, but it doesn't come without a cost. And the moment we have to pay that cost, we don't get to suddenly go, "well, openness turned out to be a mistake, let's close it all up and create a regulatory, bureaucratic nightmare". This is the tradeoff. Freedom for me, and thee.
by demosthanos | 2025-06-05 18:13:50+00:00
And who's going to put GrapheneOS on an ordinary person's phone in the first place?

The Web installer [0] is not really approachable to a normal Android user. The instructions are dense, loaded up with warnings about dozens of edge cases that are discussed in jargon that would intimidate even relatively tech-savvy users:

What's USB passthrough? Did I install my browser through Flatpak or Snap? How would I know? Did I need to understand the paragraph explaining in detail how carrier models lock users in? There's a bunch of stuff in there about Linux... do I need Linux? What's a sha256 hash and do I need to care?

It's not that this is impossible for non-IT-folks to grasp, but there's no chance that my parents are installing this on their phone.

[0] https://grapheneos.org/install/web
by jdefr89 | 2025-06-05 18:14:09+00:00
Alright folks.. To qualify myself. I am a vulnerability Researcher @ MIT. My day to day research concerns embedded hardware/software security. Some of my current/past endeavors involve AI/ML integration and understanding just how useful it actually is for finding/exploiting vulnerabilities. Just last week my lab hosted a conference that included MIT folks and the outsiders we invite. One talk was on the current state of AI/LLM. To keep things short, this article is sensationalized and overstates the utility of AI/ML on finding actual novel vulnerabilities. As it currently stands, LLMs cannot even reliably find bugs other less sophisticated tools could have found in much less time. Binary Exploitation is a great place for illustrating the wall you’ll hit using LLMs hoping for a 0day. While LLMs can help with things like setting up fuzzers or maybe giving you a place to start manual analysis, their utility kind of stops there. They cannot reliably catch memory corruption bugs that a basic fuzzers or sanitizers could have found within seconds. This makes sense for that class of bugs. LLMs are fuzzy logic and these issues aren’t reliably found with that paradigm. That’s the whole reason we have fuzzers; they find subtle bugs worth triaging. You’ve seen how well LLMs count, it’s no surprise they might miss many of the same things a humans would but fuzzers wouldn’t (think UaF, OOB, etc). All the other tools you see written for script kiddies yield the same amount of false positives they could have gotten with other tools that already exist.. I can go on and on but I am on shuttle, typing on small phone. TLDR: Article is trying to say LLMs are super hackers already and that’s simply false. They definitely have allure for script kiddies. In the future this might change. LLMs time saving aspects are definitely worth checking out for static binary analysis. Binary Ninja with Sidekick saves a lot of time! But again. You still need to double check important things!
by DanMcInerney | 2025-06-05 18:14:11+00:00
I too write automated offensive tooling. We actually wrote a project, vulnhuntr, that found the first autonomously-discovered 0day using AI. Feed it a GitHub repo and it tracks down user input from source to sink and analyzes for web-based vulnerabilities. Agree this article is incredibly cringy and standard best practices in network and development security will use the same AI efficiency gains to keep up (more or less).

What bothers me the most about this article is that the tools that attackers use to do stuff like find 0days in code are the same tools that defenders can use to find the 0day first and fix it. It's not like offensive tooling is being developed in a vacuum and the world is ending as "armies of script kiddies" will suddenly drain every bank account in the world. Automated defense and code analysis is improving at a similar rate as automated offense.

In this awful article's defense though, I would argue that red team will always have an advantage over blue team because blue team is by definition reactionary. So as tech continues it's exponential advancements, the advantage gap for the top 1% red teamers is likely to scale accordingly.
by alcroito | 2025-06-05 18:14:55+00:00
I wish PURL proposed something sensible or at least usable for tracking C / C++ native libraries, that are NOT hosted on a registry like conan.io, or one of the linux distro registries, but is still (self-)hosted somewhere online.

For libraries that are hosted on `github`, there's at least the github type.

But there is no official `gitlab` or `git` type, and i've read comments that even the `github` type is considered a mistake.

One example of such a library could be a Qt or KDE / Plasma library.

They are hosted on their own forges, https://code.qt.io/ and https://invent.kde.org respectively.

So to the more knowledgeable people out there, what is the PURL way of identifying a C++ library like that?

Is `generic` type + vcs_url qualifier really the only way?

Right now it seems impossible to track vulnerabilities for such libraries with OSS / open tools, because none of the open tools or databases support a custom type or registry or ecosystem.

For example none of services here support some custom C++ ecosystem (putting aside conan):

https://docs.dependencytrack.org/analysis-types/known-vulner...

Same for https://docs.dependencytrack.org/datasources/osv/
by dragonwriter | 2025-06-05 18:15:21+00:00
> It can be just anonymised search history in this case.

Depending on the exact issues in the case, a court might allow that (more likely, it would allow only turning over anonymized data in discovery, if the issues were such that that there was no clear need for more) but generally the obligation to preserve evidence does not include the right to edit evidence or replace it with reduced-information substitutes.
by righthand | 2025-06-05 18:15:30+00:00
The internet isn’t Twitter, people aren’t advocating for censoring the internet, they’re advocating for censoring a person on a digital service platform. If you don’t think you’d see people advocating for censorship on HackerNews then you don’t understand what HN platform is, because bans, downvotes, flagging, etc are all types of censorship.

If you don’t like the platform censoring you, go somewhere else or do what Elon did and buy the platform and change the rules for yourself.
by rglover | 2025-06-05 18:15:32+00:00
And every single one has a power switch.

I get the general "too many variables" argument, but the idea that humans have no means of stopping any of these apps/systems/algorithms/etc if they get "out of control" (a farce in itself as it's a chat bot) is ridiculous.

It's very interesting to see how badly people want to be living in and being an active participant in a sci-fi flick. I think that's far more concerning than the AI itself.
by jorvi | 2025-06-05 18:15:48+00:00
What's most annoying about Gemini 2.5 is that it is obnoxiously verbose compared to Opus 4. Both in explaining the code it wrote and the amount of lines it writes and comments it adds, to the point where the output is often 2-3x more than Opus 4.

You can obviously alleviate this by asking it to be more concise but even then it bleeds through sometimes.
by Ajedi32 | 2025-06-05 18:15:53+00:00
This is why "do whatever the heck I want with it" ought to apply to software, not just hardware. This is one thing I think Richard Stallman got right, all the way back in 1988:

> the freedom to change a program, so that you can control it instead of it controlling you; for this, the source code must be made available to you.

We're a long way from that ideal today. Software controls us all the time. Usually that just leads to anti-consumer annoyances like lock screen ads or DLC seat heaters. But when the one controlling the software that controls you is a communist government...

Not sure what the short term practical solution to this is though.
by Spivak | 2025-06-05 18:16:28+00:00
I mean to be fair it is related to a current open case but the order is pretty ridiculous on its surface. It's feels different when the company and the employees thereof have to retain their own comms and documents, and that company must do the same for 3rd parties who are related but not actually involved in the lawsuit is a bit of a stretch.

Why the NYT cares about a random ChatGPT user bypassing their paywall when an archive.ph link is posted on every thread is beyond me.
by cyberax | 2025-06-05 18:16:58+00:00
Eating a snake might not kill a predator outright.

And higher predators (like mammals) also have food preferences. They don't always eat stuff indiscriminately, so predators that don't _like_ snakes will preferentially survive. Eventually, this can get established as a genetic trait.

Or as a behavioral one, if parents don't teach cubs to hunt snakes.
by bytefactory | 2025-06-05 18:19:56+00:00
> I think AGI, if possible, will require a architecture that runs continuously and 'experiences' time passing

Then you'll be happy to know that this is exactly what DeepMind/Google are focusing on as the next evolution of LLMs :)

https://storage.googleapis.com/deepmind-media/Era-of-Experie...

David Silver and Richard Sutton are both highly influential figures with very impressive credentials.