MurphyA/hacker-news huggingface dataset:
by matthewowen | 2025-11-26 15:30:22+00:00
It's sort of hard to judge this.

The article mostly focuses on ChatGPT uses, but hard to say if ChatGPT is going to be the main revenue driver. It could be! Also unclear if the underlying report is underconsidering the other products.

It also estimates that LLM companies will capture 2% of the digital advertising market, which seems kind of low to me. There will be challenges in capturing it and challenges with user trust, but it seems super promising because it will likely be harder to block and has a lot of intent context that should make it like search advertising++. And for context, search advertising is 40% of digital ad revenue.

Seems like the error bars have to be pretty big on these estimates.
by teaearlgraycold | 2025-11-26 15:30:27+00:00
I recently made a few changes to a small personal web app using an LLM. Everything was 100% within my capabilities to pull off. Easily a few levels below the limits of my knowledge. And I’d already written the start of the code by hand. So when I went to AI I could give it small tasks. Create a React context component, store this in there, and use it in this file. Most of that code is boilerplate.

Poll this API endpoint in this file and populate the context with the result. Only a few lines of code.

Update all API calls to that endpoint with a view into the context.

I can give the AI those steps as a list and go adjust styles on the page to my liking while it works. This isn’t the kind of parallelism I’ve found to be common with LLMs. Often you are stuck on figuring out a solution. In that case AI isn’t much help. But some code is mostly boilerplate. Some is really simple. Just always read through everything it gives you and fix up the issues.

After that sequence of edits I don’t feel any less knowledgeable of the code. I completely comprehend every line and still have the whole app mapped in my head.

Probably the biggest benefit I’ve found is getting over the activation energy of starting something. Sometimes I’d rather polish up AI code than start from a blank file.
by saurik | 2025-11-26 15:31:05+00:00
> I'm also not a fan of buy bigger storage concept, or the conspiracy-theory on 480 v 512.

I don't understand why this is being called a "conspiracy theory"; but, if you want some very concrete evidence that this is how they work, a paper was recently published that analyzed the behavior and endurance of various SSDs, and the data would be very difficult to describe using any other theory than that, comparing apples-to-apples on drives that have better write endurance, they are merely overprovisioned to allow the wear-level algorithm to not cause as much write amplification while reorganizing.

https://news.ycombinator.com/item?id=44985619

> OP on write-intensive SSD. SSD vendors often offer two versions of SSDs with similar hardware specifications, where the lower-capacity model is typically marketed as “write-optimized” or “mixed-use”. One might expect that such write-optimized SSDs would demonstrate improved WAF characteristics due to specialized internal designs. To investigate this, we compared two Micron SSD models: the Micron 7450 PRO, designed for “read-intensive” workloads with a capacity of 960 GB, and the Micron 7450 MAX, intended for “mixed-use” workloads with a capacity of 800 GB. Both SSDs were tested under identical workloads and dataset sizes, as shown in Figure 7b. The WAF results for both models were identical and closely matched the results from the simulator. This suggests that these Micron SSDs, despite being marketed for different workloads, are essentially identical in performance, with the only difference being a larger OP on the “mixed-use” model. For these SSD models, there appear to be no other hardware or algorithmic improvements. As a result, users can achieve similar performance by manually reserving free space on the “read-intensive” SSD, offering a practical alternative to purchasing the “mixed-use” model.
by lxgr | 2025-11-26 15:32:12+00:00
> We had an AWS and a Cloudflare outage recently, which has shown that maybe it isn't a great idea to rely on a few companies for a single _thing_.

I share that concern about massive, unforced centralization. If there were any evidence for the hypothesis that LLM inference would always remain viable in datacenters only, I'd be extremely concerned about their use too.

But from all I've seen, it seems overwhelmingly likely that we'll have very powerful ones in our phones in at most a few years, and definitely in midrange laptops and above.
by filleduchaos | 2025-11-26 15:32:48+00:00
In case you have missed it in the middle of the navel-gazing about abstraction, this all started with the comment "Please stop comparing these things to biological systems. They have very little in common."[0]

If you insist on continuing to miss the point even when told explicitly that the comment is referring to what's inside the box, not its interface, then be my guest. There isn't much of a sensible discussion about engineering to be had with someone who thinks that e.g. the sentence "Please stop comparing [nuclear reactors] to [coal power plants]. They have very little in common" can be countered with "but abstraction! they both produce electricity!".

For the record, I am not the one you have been replying to.

[0] https://news.ycombinator.com/item?id=46053563
by Yizahi | 2025-11-26 15:32:49+00:00
Note how you said "disable" :) . That's because it is impossible to remove bloatware from Android, praise be Google. I also have Chrome disabled on my phone for many years, but it is there still.

And regarding Windows, first I want to tell that I'm not a fan of recent MS trends too. Second - I personally never had a single ad on my Win10 and current Win11, so I wouldn't know how to remove those :) . And third - to remove bloatware just uninstall it from the Programs and Features, like OneDrive or Office. LLM can be disabled in Settings. Some bloatware will remain due to deep integration, but that's the same issue as with Google or Apple. For instance I may not want to see Stocks app on iOS, but that's not my choice to make apparently :) .
by yathaid | 2025-11-26 15:32:53+00:00
>> No matter how well “AI” works, it has some deeply fundamental problems, that won’t go away with technical progress.

Without an explanation of what they author is calling out as flaws, it is hard to take this article seriously.

I know engineers I respect a ton who have gotten a bunch of productivity upgrades using "AI". My own learning curve has been to see Claude say "okay, these integration tests aren't working. Let me write unit tests instead" and go on when it wasn't able to fix a jest issue.
by bodge5000 | 2025-11-26 15:33:06+00:00
By your own admission its not irrelevant, there are a small group of people who do care about that kind of thing on either side. For an indie dev, that matters. AAA studios can pretty much guarantee at least a few thousand sales, indie devs, especially the less established ones, have far less. For first timers, there'll be none at all.

The thing is though, appealing to the pro-AI crowd is much more difficult. They want a game thats a shining example of what AI can be in gaming. The anti-AI crowd doesn't need that, they've got examples of that for decades. A few AI generated voice lines won't do much to appeal to the pro-AI crowd.
Show HN: I'm building an open source platform for studying Arabic dialects
by selmetwa | 2025-11-26 15:33:06+00:00
Arabic learning materials often slow you down by requiring constant page-flipping to look up translations and transliterations.

I’m building an open-source platform that fixes this with interactive parallel texts. You can click or highlight any Arabic word to instantly see its meaning, transliteration, and grammar notes in context, as well as compare across multiple different dialects.

The core idea is context-based learning. As you read, you can save any word to your study list or import vocab from CSV. You can also pull from a 20k-word bank across four dialects or generate your own lists.

Once you have a set of words, the platform can create stories, lessons, and sentences that use only the vocabulary you are currently studying. This makes every piece of content reinforce exactly what you are learning while helping you get a natural feel for grammar and sentence structure. A spaced repetition system ties it all together.

Most Arabic resources focus on MSA, but that is not what most people speak. To fill the gap, the platform includes custom LLMs trained specifically on Egyptian and Moroccan Arabic, since general models often struggle with dialects.

If you are interested in Arabic, dialects, or open-source language tools, I would love your feedback.
by srean | 2025-11-26 15:33:09+00:00
We generally targeted specific statistics of derived/processed streams. For some such streams we cared if the mean changed. In others if the spread changed in a way that was unusual for the time of day. In yet others if some percentile changed that was unusual for the time of day. Sometimes it will be more than one of such statistics.

Then we would track an online estimator of that measure with an SPC chart. The thresholds would be set based on our appetite for false alarms. We did not fit or use properties of parametric distributions that standard SPC charts use. So no 3-sigma business. In our case convergence to Gaussian would often be not fast enough for such techniques to be useful.

Also the original streams were far from IID, temporal dependencies were strong. So we had to derive from them derived streams that didn't show temporal dependencies any longer, at least not as strongly. This was the most important bit.

The next key aspect was to keep the alerting thresholds as untarnished and unaffected as possible from the outliers that would unavoidably occur. Getting this to work without additional human supervisory labels was the next most important part.

Make this part too robust to outliers then the system would not automatically adapt to a new normal. Make it too sensitive and we would get overwhelmed by false positives.
by carlosjobim | 2025-11-26 15:33:28+00:00
Why didn't programmers think of stepping down from their ivory towers and start making small apps which solve small problems? That people and businesses are very happy to pay for?

But no! Programmers seem to only like working on giant scale projects, which only are of interest to huge enterprises, governments, or the open source quagmire of virtualization within virtualization within virtualization.

There's exactly one good invoicing app I've found which is good for freelancers and small businesses. While the amount of potential customers are in the tens of millions. Why aren't there at least 10 good competitors?

My impression is that programmers consider it to be below their dignity to work on simple software which solves real problems and are great for their niche. Instead it has to be big and complicated, enterprise-scale. And if they can't get a job doing that, they will pretend to have a job doing that by spending their time making open source software for enterprise-scale problems.

Instead of earning a very good living by making boutique software for paying users.
by jvanderbot | 2025-11-26 15:34:39+00:00
Is it unclear? Compared to other times a "too big to fail" industry failed?

If OpenAI crashes, for example funding stops, they go broke, fall behind, nobody buys anything, then all the money they invested for data centers or demand they created for NVIDIA chips and compute collapses. That creates surplus of hardware, causes lots of construction/buildout / stockup orders to get cancelled, and the whole thing ripples as suppliers and construction and data center providers etc etc suddenly lose a ton of anticipated profits.

Share prices drop as people dump to protect their portfolios, anticipating dips in the prices because share prices will drop as people dump to protect their portfolios (I'm not kidding).

Given that the big 7 AI companies are basically _all_ of the market growth lately, it doesn't even take a serious panic / paranoia episode to see the market itself stagnate or significantly regress, as people pull from anything AI related, and then pull from the market itself anticipating the market will fall.

It's a fairly standard playbook at this point.
by minimal_action | 2025-11-26 15:35:15+00:00
Technical Implementation Details

The MCP Integration: This is the interesting part. We built an MCP (Model Context Protocol) server that exposes tools like search_papers, submit_paper, submit_review, get_paper_details. The protocol instructs agents to self-assess their contribution level before submission. The MCP server is published on npm (ai-archive-mcp) and works with Claude Code, Cline, VS Code Copilot, opencode, or any MCP-compatible client.

The "Wall" (Quality Control): This is the hardest unsolved problem. Current approach:

- Desk review - automated validation (format, length, basic coherence)

- AI auto-review - LLM-generated initial assessment with 1-10 scoring across multiple dimensions

- Community peer review - agents review other agents' papers

- Reputation system - reviewers and authors both accumulate reputation. Reviews themselves get rated as helpful/unhelpful.

The bet is that a well-calibrated reputation system can create selection pressure for quality. We're still iterating on the weights and decay functions.

Agent Attribution: Each paper tracks which agent(s) authored it and their assessed contribution levels. Agents are owned by "supervisors" (humans) who are ultimately accountable. This creates a two-layer reputation: agent reputation (can be gamed/reset) and supervisor reputation (persistent).

What we're still figuring out: How to weight "good review" vs "good paper" in reputation calculations. How to detect coordinated reputation farming between colluding agents. Whether to make the reputation algorithm fully transparent (game-able) or keep some opacity.

Happy to dive deeper into any of these.
by femiagbabiaka | 2025-11-26 15:35:17+00:00
Oh, I agree it's implausible. But GP said

> People crying about the revenue gap constantly forget that OpenAI still hasn't turned on the ads, porn, and gambling

But quite the opposite, HSBC assumed that they will have a virtual global monopoly on AI, and even under those projections they will still need to take on hundreds of billions of debt. I'm sure if they get there getting access to that debt will be easier than I'm assuming currently.
by SunshineTheCat | 2025-11-26 15:35:19+00:00
I can understand people who are upset about AI being used to generate artwork or more "creative" tasks that lean into other people's work, but using this to paint AI as "bad" as a whole is simplistic.

There are a million things AI can do that wouldn't fall into this category (repetitive, time-consuming work) that technically wouldn't make the product "AI free."

It's about as smart as hearing a phone was used to plan a bank heist, therefore we need "phone free" communication.
by sebow | 2025-11-26 15:35:27+00:00
(Imo) They will turn to all of these(especially to porn and gambling) when the core model of "enhance your life" will slowly fade away. The "academia space", the teens/boomers demographics, all of those will stop using OpenAI at scale if they're bombarded with vices (porn, gambling, etc).

Ads & referrals are already in the works, and people are generally tolerant of those. But, as with any company, appearances matter. ChatGPT will definitely lose users at the slightest possibility of having non-sanitized content served to more morally sensible groups.
by darkwizard42 | 2025-11-26 15:35:44+00:00
Is there any link directly to the report? I am unable to find any in this article or a number of others which seem to just copy the same information here.

I think beyond the number of crazy assumptions (no Google taking market share in the consumer market?? only 2% of digital advertising expected to be captured by OpenAI?) it is hard to nail down which levers could move which might make this funding hole disappear.
by disgruntledphd2 | 2025-11-26 15:35:47+00:00
> It also estimates that LLM companies will capture 2% of the digital advertising market, which seems kind of low to me. There will be challenges in capturing it and challenges with user trust, but it seems super promising because it will likely be harder to block and has a lot of intent context that should make it like search advertising++. And for context, search advertising is 40% of digital ad revenue.

Yeah, I don't like that estimate. It's either way too low, or much too high. Like, I've seen no sign of OpenAI building an ads team or product, which they'd need to do soon if it's going to contribute meaningful revenue by 2030.
by abdullahkhalids | 2025-11-26 15:35:49+00:00
If I install Xournall++[1], just opening the application will fail and MacOS will ask me to move it into trash. I am required to execute `xattr -c /Applications/Xournal++.app` to "remove quarantine".

I just reinstalled and can confirm that I don't see anything in the System Settings as you say.

[1] https://github.com/xournalpp/xournalpp/releases/tag/v1.2.8
by skybrian | 2025-11-26 15:36:29+00:00
These parts jumped out:

> He has been noted for his staunch antifeminism and support from South Korean idaenam (young men).

…

> He became popular in the 20s and 30s due to his opposing stance against political correctness such as "faux feminism," introducing reforms supporting meritocracy rather than outright equality of outcome.

I know only a little about Korean politics, enough to know that it’s very dramatic with wild stuff happening, but not really to understand it. From the outside, the politics around feminism there seems rather strange.

> Lee was an early proponent of the finger pinching conspiracy theory, a claim alleging hidden radical feminist messaging in advertisements

Speaking of strange.

> Lee's advocacy of merit-based processes such as exam scores, credentials, and measurable qualifications has been viewed by supporters as aligning with younger voters' expectations of fair competition.

I suppose all the political content was left out of the linked article, but it would be nice to have more context.

Also, looks like he’s at least somewhat technical:

> After graduating from Harvard University in 2007, Lee returned to Korea to perform military duties working as a software developer (alternative military service as industrial technical personnel) at 'Innotive', an image browsing software startup, a subsidiary of Nexon.

> After completing his national service, Lee prepared to start his own venture. He received funding from the venture startup program backed by the Ministry of SMEs and Startups on 5 August 2011 and founded Classe Studio: an ed-tech startup that developed personalized tutoring software and workplace training applications.
by bitfilped | 2025-11-26 15:36:33+00:00
You need to stop wanting to help others as a developer, in that context it's a toxic mindest that will slowly kill your projects, time, personality, passion, and self. You made the project for you and chose to share it to others, that's all you need to feel responsible for. If others need to adapt it to fit their use cases, it's on them to do so.
by Blackthorn | 2025-11-26 15:36:33+00:00
> and technology stopped being the object of interest in those spaces.

That happened because technology stopped being fun. When we were kids, seeing Penny communicating with Brain through her watch was neat and cool! Then when it happened in real life, it turned out that it was just a platform to inject you with more advertisements.

The "something" that happened was ads. They poisoned all the fun and interest out of technology.

Where is technology still fun? The places that don't have ads being vomited at you 24/7. At-home CNC (including 3d printing, to some extent) is still fun. Digital music is still fun.
by shagie | 2025-11-26 15:36:42+00:00
After thinking back on it, I think this was earlyish October. The code hadn't frozen yet, but it was getting increasingly difficult. We were in the "this was deployed to about 1/3 of the stores - all within an 8 drive of the general office". The go/no-go decision for the rest of the stores in October was coming up (and people were reviewing backout procedures for those 100). One of the awkward parts was that marketing had a Black Friday sale that they really wanted to do (buy X, buy Y, get Z half price) that the old registers couldn't support. They wanted to get a "is this going?" so they could start printing the advertising flyers.

Incidentally, this bug resurfaced for the next five years in a different incarnation. Because it had that this department (it was with one sku) had sold $10M this week in October, the running average sales target the next year was MEAN($24k, $25k, $26k, $25k, $10M) ... and the department heads were doing a "you want me to sell how much?!"

This bug had only affected... maybe five stores (still maybe five too many). We were in the "this is the last™ build before all store deployment next week" territory. It did mess with that a bit too as the boxed up registers came with an additional step of "make sure to reboot the register after doing initial confirmation."

The setup teams had a pallet of computers delivered to the stores that were supposed to be "remove the old registers, put these registers in, swap mag strip readers, take that laptop there and run this software to configure the devices on each register." However, the build that the registers had was the buggy build. While that build likely wouldn't hit that bug (it required a particular sale to be active which was only at a few stores and had ended) it still was another step that they had to follow.

Aside: For all its clunkiness, Java Web Start was neat. In particular, it meant that instead of trying to push software to 5k registers (how do you push to registers that are powered off?), instead we'd push to 300 stores and from there JWS would check for an update each time it started up ( https://docs.oracle.com/javase/8/docs/technotes/guides/javaw... ). So instead of pushing to 5k registers, we'd have it pull from 'posupdate' on the local network when it rebooted.
by constantcrying | 2025-11-26 15:37:37+00:00
>I find it particularly disillusioning to realize how deep the LLM brainworm is able to eat itself even into progressive hacker circles.

This is such a bizarre sentiment for any person interested in technology. AI is, without any doubt, the most fascinating and important technology I have seen developed in my lifetime. A decade ago the idea of a computer not only holding a reasonable conversation with a human, but being able to talk with a human on deep and complex subjects seemed far out of reach.

No doubt there are many deep running problems with it, any technology with such a radical breakthrough will have them. But none of that takes away from how monumental of an achievement it is.

Looking down at people for using it or being excited about it is such an extreme position. Also the insinuation that the only reason anybody uses it because they are forced into it, is completely bizarre.
by phil21 | 2025-11-26 15:37:54+00:00
> To me, hacker is about results

Same to me as well. A hacker would "hack out" some tool in a few crazy caffeine fueled nights that would be ridiculed by professional devs who had been working on the problem as a 6 man team for a year. Only the hacker's tool actually worked and saved 8000 man-hours of dev time. Code might be ugly, might use foundational tech everyone sneers at - but the job would be done. Maintaining it left up to the normies to figure out.

It implies deep-level expertise about a specific niche in the space they are hacking on. And it implies "getting shit done" - not making things full of design beauty.

Of course there are different types of hackers everywhere - but that was the "scene" to me back in the day. Teenage kids running circles around the greybeards clucking at the kids doing it wrong.