MurphyA/hacker-news huggingface dataset:
by Mawr | 2025-06-18 08:56:48+00:00
> I've never seen a company suffer financially because of inefficient code

Well, how many companies that went bankrupt because of inefficient code have you looked at? ;) It's hard to see what no longer exists. See Survivorship Bias [1].

Also fun: "More than 10 years ago, Amazon found that every 100ms of latency cost them 1% in sales. In 2006, Google found an extra .5 seconds in search page generation time dropped traffic by 20%. A broker could lose $4 million in revenues per millisecond if their electronic trading platform is 5 milliseconds behind the competition." [2]

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

[2]: https://www.gigaspaces.com/blog/amazon-found-every-100ms-of-...
Show HN: Fixing AI Tool Calling Context Bloat
by Dheerajiitr | 2025-06-18 08:56:53+00:00
LLM agents rely on tool calls — but tool responses are huge.

Gmail, CRMs, and APIs return bloated JSON LLMs choke on large responses You only need 2–3 fields, but frameworks give you zero control

Toolflow is an AI-native framework to fix this:

* Filter tool responses before they hit the LLM * Context modes: `minimal`, `full`, `custom`, or `ai` * Composable TypeScript tool registry

GitHub: [https://github.com/dksingh1997/toolflow](https://github.com/dksingh1997/toolflow)

Would love feedback — especially from those building with LLMs in production.
by rijal028 | 2025-06-18 08:57:22+00:00
Thank you for this incredibly valuable and insightful feedback. You've perfectly articulated the core challenges and long-term viability of the different defensive layers.

I completely agree that the "AI Poison" layer is likely a temporary defense. Your validation of watermarking and especially cryptographic signing as the most robust long-term solutions is a crucial takeaway for me.

And thank you especially for pointing me to the C2PA specification. I was not aware of this standard, and aligning my concept with it is a critical next step. I will be studying this document carefully.

This is exactly the kind of expert feedback I was hoping to get by sharing my work here. I truly appreciate you taking the time.
by mike_hearn | 2025-06-18 08:57:24+00:00
The interesting thing about this is that some syscalls are versioned, even though the syscall interface is internal and private. There's NtLoadKey, NtLoadKey2, NtLoadKey3 and even NtLoadKeyEx.

This kind of versioning on public APIs, I understand, but syscalls are only meant to be invoked by ntdll. Why do they need more than one?
by phito | 2025-06-18 08:59:10+00:00
This is the worst thing ever. I have coworkers who literally cannot string three words together without making a grammar mistake, but recently they've been texting me with more-than-perfect grammar and a vast vocabulary.

These people are trying to fool everyone else making them think they are smarter/more educated than they actually are. They aren't fooling me, I've seen their real writing, I know it's not actually their text and thoughts, it really disgusts me.
by YeGoblynQueenne | 2025-06-18 08:59:24+00:00
>> If you can execute Prolog in a different manner then I'm happy that's the case but I find it hard to believe that's still Prolog. How would the IO come out in the same order?

See my link to SWI-Prolog's implementation of tabling above. Copied here again (third time) for your convenience:

https://www.swi-prolog.org/pldoc/man?section=tabling
by probably_wrong | 2025-06-18 09:00:14+00:00
From https://www.wired.com/story/facebook-whatsapp-merger-europea...

The European Commission has found that Facebook provided “misleading information” about its 2014 takeover of WhatsApp following an investigation into the deal.

The commission’s complaint relates specifically to the sharing of user data between Facebook and WhatsApp. In a submission to the EU made in August 2014, Facebook said it would not be possible to create a reliable automated system for matching users. In August 2016, WhatsApp announced that it would be linking WhatsApp user phone numbers with Facebook user identities.
by account42 | 2025-06-18 09:00:19+00:00
The problem is that there is also tons of services that promised not to enshittify but then changed their minds when they thought that fucking over their users would be more profitable. That includes even Google, look up their early views on ads. Because of this those promises are often (IMO rightfully) ignored as hot air. The only way to ensure that your software doesn't get enshittified is to legally guarantee that you are not dependent on a single vendor for future development - the most effective way to do that is insist on open source software.
by A_D_E_P_T | 2025-06-18 09:00:22+00:00
https://archive.ph/7lvlj

"Up to"

Still, though, as far as I know that kind of hiring bonus is unheard of. Surely Deepseek and Google have shown that the skills of OpenAI employees are not unique, so this must be part of an effort to cripple OpenAI by poaching their best employees.
by moffkalast | 2025-06-18 09:00:23+00:00
They probably did, but still preferred their old way since it took more skill.

I remember some old quote about how people used to ask their parents and grandparents questions, got answers that were just as likely to be bullshit and then believed that for the rest of their life because they had no alternative info to go on. You had to invest so much time to turn a library upside down and search through books to find what you needed, if they even had the right book.

Search engines solved that part, but you still needed to know what to search for and study the subject a little first. LLMs solve the final hurdle of going from the dumbest possible wrongly posed question to directly knowing exactly what to search for in seconds. If this doesn't result in a knowledge explosion I don't know what will.
by latexr | 2025-06-18 09:01:59+00:00
I agree that reads like a fluff meaningless sentence on the level of a high school student trying to reach the minimum word count, but to give it some benefit of the doubt, it does say “a country known for”, not “a country which has”. Most countries aren’t known for their traditions and cultural heritage. Ask a few random people to tell you about Japan VS, say, Estonia.
by consumer451 | 2025-06-18 09:02:17+00:00
Just to be a bit more clear, this was a while ago. The answer in gp was to the question: "hey, I am not an ads guy, but my friend asked me to look at his account, and he had no geo restriction set. Why did 60% of his clicks for 'barn wedding venue east tennesse' come from Malaysia? Why would so many people from there see that, and click on in it?"

The bragging wasn't about their lawyers' ability in court, it was about their lawyers' ability to draft Terms and Conditions such that they could not be caught in a lie.

And yes, not Meta in this story, but come on.
by tim333 | 2025-06-18 09:02:36+00:00
>both engines would have had to fail immediately at almost exactly the same time. That's an imaginable scenario...

Not only imaginable but similar has happened on a 787:

>An ANA 787 had an unexpected dual engine shutdown after landing on January 17, 2019, activated by a system called the TCMA (Thrust Control Malfunction Accommodation), intended to shutdown runaway engines on the ground. Its logic should only activate it on the ground with weight on wheels if it senses the thrust lever is at idle but the engine is not (from https://www.reddit.com/r/aviation/comments/1ld9yb8/air_india...)

I'm guessing something like that - a system screw up of some sort.
by hajhatten | 2025-06-18 09:04:14+00:00
There's a time and place for everything, and an escalation of tooling/environmental context for me.

1. Printing vars in unit tests may be the fastest first approach. If i know where the bug may be.

2. When that fails i usually bring in debuggers to unit tests.

3. When these aren't helping, you need debuggers on the entire binary.

4. Still stuck? Use a debugger in production.
by gchadwick | 2025-06-18 09:05:10+00:00
I wonder if they ever taped this out and did some device characterization?

The devil really is in the details with things like this. 1 in 10 million events which may be hard to trigger in a detailed analogue simulation can occur many times per second when you run it in silicon and make it effectively useless.

Still very cool to have enough open source tooling and a PDK so this can even be attempted as a piece of open source design work!
by cyberax | 2025-06-18 09:06:08+00:00
OK, let's see. You're a plant, so you have photosynthesis. It allows you to tap around 5W (averaged out) per square meter of foliage by just AFK-ing. Your major need: water, you have to evaporate it for the photosynthesis to work. But it's not a problem in your habitat, there's plenty of water available.

You also need nitrogen, phosphorus, and other nutrients, but comparatively little of them. Nitrogen is the toughest one. This is the one that you can easily get from animals, though. So you can evolve a complicated mechanism to trap small animals and digest them for nutrients. It also provides you with a bit of energy, but it's completely immaterial compared to photosynthesis, so you don't even bother evolving all the complicated protein-to-glucose pathways.

Now, you want to grow bigger. How would you do it? Energy is not an issue, the photosynthesis provides plenty of it. But you need to trap more or bigger animals, and that's an issue. There just aren't that many of them, and you can't just get away with simple traps anymore.
by rsynnott | 2025-06-18 09:06:41+00:00
The markets seem to like it, so if you go "we're going AI-first!" every six months, you'll get a little stock price boost. Actually _doing_ anything, naturally, is entirely optional.

Expect this to repeat until the markets choose a new favourite thing (I'm betting on "quantum"; it's getting a lot of press lately and is nicely vague.)
by isoprophlex | 2025-06-18 09:07:23+00:00
I swear I'm not making this up; a guy at my current client needed to join two CSV files. A one off thing for some business request. He wrote a REST api in Java, where you get the merged csv after POSTing your inputs.

I must scream but I'm in a vacuum. Everyone is fine with this.

(Also it takes a few seconds to process a 500 line test file and runs for ten minutes on the real 20k line input.)
by anonymousiam | 2025-06-18 09:07:42+00:00
One of my places uses Frontier FiOS (soon to become Verizon again). They have zero support for IPv6, and it isn't even on their roadmap.

I use a static HE (Hurricane Electric) IPv6 tunnel there, and it works great.

The only issue is that YouTube thinks the IPv6 block is commercial or an AI dev scraping their content, so I can't look at videos unless I'm logged in to YouTube.
by Yizahi | 2025-06-18 09:07:50+00:00
Author seems to conflate features unique to X11 with "useful" features or "desirable by many" features. I would try to project minimally, but the long list he provides is not that, at least for some significant number of users, or maybe even for majority (I suspect it is).

While on the other hand he conveniently ignores that a majority of users do need stuff like working HiDpi scaling, multimonitor use with different scalings, general monitor stability in all scenarios (plug and play from laptop, sleep/hibernate, go to 3D gaming and back to desktop etc.) and other stuff used daily by most users. And which is very brittle or even missing in X-11.

For professional use, I can live with Linux without graphical server at all. But for entertainment or creative arts use, monitor "just working per spec" is way more important than those thin client X-11 features inherited from mainframes and mostly unused.
by tasn | 2025-06-18 09:09:14+00:00
I think this is true for the very simple cases, for example and obviously bad picture vs. a good one.

I don't think this is necessarily true for more complex tasks, especially not in areas that require deep evaluation. For example, reviewing 5 non-trivial PRs is probably harder and more time consuming than writing it yourself.

The reason why it works well for images and short stories is because the filter you are applying is "I like it, vs. I don't like it", rather than "it's good vs. it's not good".
by v5v3 | 2025-06-18 09:09:51+00:00
He said "none of our best people have left" which means some are leaving.

And OpenAi probably had to renegotiate with those with a $100m offer so their costs went up.

Suppose it is karma for Zuckerberg, Meta have abused privacy so much many dislike them and won't work for them out of principle.
by hyperman1 | 2025-06-18 09:10:01+00:00
I think it goes deeper. There is a certain level of slowness that causes pain to users. When that level is hit, market forces cause attention to software efficiency.

Hardware efficiency just gives more room for software to bloat. The pain level is a human factor and stays the same.

So time to adapt Wirths law: Software gets slower >exactly as much< as hardware gets faster
by rsynnott | 2025-06-18 09:11:56+00:00
> I have over $100k in Tesla puts.

I mean, if this were a _normal_ company, that would make sense. But it's Tesla, so it's a very dangerous game, because Tesla's stock price is at best only peripherally related to Tesla's business. You're in great risk of Musk posting a meme or having another child with a silly name or whatever, thus pushing up the stock price 10%.
by khazhoux | 2025-06-18 09:12:00+00:00
> i really tire of people always asking for studies for obvious things.

I actually agree with you on this!

But... I have very very good directional sense, and as far as I can tell it's innate. My whole life I've been able to remember pathing and maintain proper orientation. I don't think this has anything to do with lack of navigation aids (online or otherwise) during formative years.

But I'm talking about geospatial sense within the brain. If your point is that people no longer learn and improve the skill of map-reading then yes that should be self-evident.
by writebetterc | 2025-06-18 09:12:21+00:00
>10 minutes for linking? The only projects I've touched which have had those kinds of link times have been behemoths like Chromium. That must absolutely suck to work with.

I don't know the exact amounts of time per phase, but you might change a header file and that will of course hurt you a lot more than 1 translation unit.

> Eh, not really. Working with a binary where all variables are optimized out and all operators are inlined is hell.

Yeah, but sometimes that's life. Reading the assembly and what not to figure things out.

>That must absolutely suck to work with.

Well, you know, I also get to work on something approximately as exciting as Chromium.
by perihelions | 2025-06-18 09:13:35+00:00
Landspace, 10 km — https://www.youtube.com/watch?v=8dNFknayVDU

Deep Blue, several km, hard landing — https://www.youtube.com/watch?v=H-g26Zt15lo

iSpace, 0.3 km — https://www.youtube.com/watch?v=NKCH9ElmmZA

CASC, 12 km — https://www.youtube.com/watch?v=55iVjGuf_sE (their 75 km attempt in January failed, and doesn't have a public video)

Space Epoch, 2.5 km, hard landing — https://www.youtube.com/watch?v=eTQK1kDpbw4
by lmm | 2025-06-18 09:14:20+00:00
> I’m not sure why you think it’s the sound itself rather than the word/meaning.

If you're objecting to the very presence of the word then you're objecting to the word itself rather than the meaning being conveyed. There's a huge difference between e.g. describing a slur versus directing it at an individual, and just counting the number of times the slur is written obliterates that distinction.
by jacobgkau | 2025-06-18 09:17:40+00:00
The entire premise of my first reply to you was that your hyperbole invalidated your position. If either of us diverted the conversation, it was you.

One of your replies to me included the statement "the LLM probably won't succeed for the API in question no matter how many iterations you try and it's best to move on" (i.e. don't do the work or don't use AI to do it). Yet you continue to repeat that it's my (and everyone else's) lack of understanding that's somehow the problem, not conceding that AI being unable to perform certain tasks is a valid point of skepticism.

> This word soup doesn't get to redefine the word opposite,

You're the one trying to redefine the word "opposite" to mean "any two things that aren't identical."
by animal531 | 2025-06-18 09:19:03+00:00
I agree on the HDR blinding you, its mostly just a gimmick. Where it works is in for example Diablo 4 when there is something really shiny lying on the ground, which makes it pop out.

Other games like Senua did actually manage to pull off an amazing sun/scene though. Because its slower they can use it to accentuate, for example you walk around a corner and go from the darkness into full on sunlight which is blinding, but then falls off so as to become bearable.
by rsynnott | 2025-06-18 09:19:47+00:00
I mean, the point is, someone betting against Theranos in this way, if it were a public company, would almost certainly have lost money (unless their timing was _perfect_). Enron would be a better example (as it was public); a lot of people, even before Enron's downfall, were fairly sure that Enron was dodgy, but trading on that belief would have been extremely dangerous, because it might take _years_ to come unstuck, and shorts (or puts) ain't free.
by mort96 | 2025-06-18 09:19:54+00:00
> I don't know the exact amounts of time per phase, but you might change a header file and that will of course hurt you a lot more than 1 translation unit.

Yeah, which is why I was talking about source files. I was surprised that changing 1 source file (meaning re-compiling that one source file and then re-linking the project) takes 10 minutes. If you're changing header files then yeah it's gonna take longer.
by pu_pe | 2025-06-18 09:20:01+00:00
Raising the bar for salaries to be so high creates a huge moat for all these massive companies. Meta and OpenAI can afford to pay $100M for 10-20 top employees, but that would consume the entire initial funding round for startups such as Superintelligence from Ilya Sustskever, who raised $2 billion.
by oersted | 2025-06-18 09:20:18+00:00
They are world-class engineers of course, but it's always been clear OpenAI's core-advantage was simply the access to massive amounts capital without much expectation of a return on investment.

The ML methods they use have always been quite standard, they have been open about that. They just had the gall (or vision) to burn way more money than anyone else on scaling them up. The scale itself carries its own serious engineering challenges of course, but frankly they are not doing anything that any top-of-class CS post-grad couldn't replicate with enough budget.

It's certainly hard, but it's really not that special from an engineering standpoint. What is absolutely unprecedented is the social engineering and political acumen that allowed them to take such risks with so much money, walking that tightrope of mad ambition combined with good scientific discipline to make sure the money wouldn't be completely wasted, and the vision for what was required to make LLMs actually commercially useful (instruction tuning, "safety/censoring"...). But frankly, I really think most of the the engineers themselves are fungible, and I say this as an engineer myself.
by blips | 2025-06-18 09:20:58+00:00
"We believe computers should work for people, and dream of a future where computing, like cooking or word processing, is available to everyone."

generic...

"with live updating — all for free. LLMs ar..." also see a fair few of these long dashes (18x) which is either a tell tail of you've used ChatGPT to generate the text or you've started writing like the AI.

I havn't thought about it that hard yet but i don't really like consuming AI generated content at all as soon as i see signs of it part of my brain turns off. And no slight to the creator, I have as much interest in writing this kind of copy as any developer would i'd imagine.
by dan-robertson | 2025-06-18 09:22:57+00:00
Lots of people working for AI labs have other AI labs they could work for, so their decisions will be made based on differences of remuneration, expected work/role, location, and employer culture/mission.

The claim above is that OpenAI loses to other labs on most of the metrics (obviously depends on the person) and so many researchers have gone there based on higher compensation.
by noelwelsh | 2025-06-18 09:23:33+00:00
A few thoughts:

* A Singapore based company, according to LinkedIn. There doesn't seem to be much of a barrier to entry to building a very good LLM.

* Open weight models + the development of Strix Halo / Ryzen AI Max makes me optimistic that running great LLMs locally will be relatively cheap in a few years.
by vivzkestrel | 2025-06-18 09:23:38+00:00
This may probably be off topic a bit for your project but you in a good place to do this You could add an AI model that does the following things

- I paste a picture of a scene and it can tell me which movie it is from

- I paste a picture of a few actors/actresses from any movie and it can tell me exactly who that actor/actress is

- I don't think any existing API does this
by ben_w | 2025-06-18 09:24:28+00:00
> "with live updating — all for free. LLMs ar..." also see a fair few of these long dashes (18x) which is either a tell tail of you've used ChatGPT to generate the text or you've started writing like the AI.

It's also my IRL writing style for the last 10-15 years :P

That said:

> I havn't thought about it that hard yet but i don't really like consuming AI generated content at all as soon as i see signs of it part of my brain turns off.

Likewise.

At least, when someone else did the prompting — I do like what LLMs can output, but when LLM answers are sufficient I prefer to cut out the middle-man and ask the LLM directly myself.
by wkat4242 | 2025-06-18 09:25:08+00:00
It's more like passive resistance, not active. I just won't bother constantly moving to alternatives unless they are substantially better.

If everyone starts using signal I'll go along. But they won't so they're isn't any point. I'll still need WhatsApp so they'll keep tracking me. Signal also has poorer group chats (no subtopics for example) which I use a lot.

And if they get big quickly they'll run out of funds and will have to make similar decisions. They're not going to continue being funded by big tech bros like Brian Acton's 50M$ if their costs balloon. For me to actively promote it and use it without a big userbase, it will have to be so open that I can run my own server, like email. I do run matrix for that reason. I like ownership of my services and I'd rather contribute to the network than donating.

Ps: if he really wanted to help accessible safe communications he shouldn't have sold WhatsApp.

I see more in solutions to thwart their tracking. Such as using a matrix bridge, which I do. I do the same with search, I use a meta-search engine to remove tracking and ads. I can also customise it to my wishes that way.
by ChocolateGod | 2025-06-18 09:25:16+00:00
> Like why wasn't SurfaceFlinger got adapted for both

IIRC SurfaceFlinger is tightly tied to Binder which is an Android only kernel IPC, didn't work with the standard Mesa stack and wasn't designed for multiple windows with multiple displays.

Wouldn't be surprised though if eventually Android swaps to Wayland as Google wants to merge it with ChromeOS. Since talking to the compositor is abstracted away to the platform APIs, I don't see it as big of a hurdle as X11 to Wayland was.
by thunspa | 2025-06-18 09:25:37+00:00
Or learning to actually code. I can't see why I would ever learn to use these kinds of tools.

As a developer, I can just make it myself. Now with LLMs, if it's very simple and bounded, I can just vibe most of it with very little to lose.

As a lay person, I don't see what the TAM for this is. Who will spend the time to learn how to drag and drop an application?