MurphyA/hacker-news huggingface dataset:
by derefr | 2026-02-09 19:34:45+00:00
The negative impacts of generative AI are most sharply being felt by "creatives" (artists, writers, musicians, etc), and the consumers in those markets. If the OP here is 1. a programmer 2. who works solely with other programmers and 3. who is "on the grind", mostly just consuming non-fiction blog-post content related to software development these days, rather than paying much attention to what's currently happening to the world of movies/music/literature/etc... then it'd be pretty easy for them to not be exposed very much to anti-LLM sentiment, since that sentiment is entirely occurring in these other fields that might have no relevance to their (professional or personal) life.

"Anti-LLM sentiment" within software development is nearly non-existent. The biggest kind of push-back to LLMs that we see on HN and elsewhere, is effectively just pragmatic skepticism around the effectiveness/utility/ROI of LLMs when employed for specific use-cases. Which isn't "anti-LLM sentiment" any more than skepticism around the ability of junior programmers to complete complex projects is "anti-junior-programmer sentiment."

The difference between the perspectives you find in the creative professions vs in software dev, don't come down to "not getting" or "not understanding"; they really are a question of relative exposure to these pro-LLM vs anti-LLM ideas. Software dev and the creative professions are acting as entirely separate filter-bubbles of conversation here. You can end up entirely on the outside of one or the other of them by accident, and so end up entirely without exposure to one or the other set of ideas/beliefs/memes.

(If you're curious, my own SO actually has this filter-bubble effect from the opposite end, so I can describe what that looks like. She only hears the negative sentiment coming from the creatives she follows, while also having to dodge endless AI slop flooding all the marketplaces and recommendation feeds she previously used to discover new media to consume. And her job is one you do with your hands and specialized domain knowledge; so none of her coworkers use AI for literally anything. [Industry magazines in her field say "AI is revolutionizing her industry" — but they mean ML, not generative AI.] She has no questions that ChatGPT could answer for her. She doesn't have any friends who are productively co-working with AI. She is 100% out-of-touch with pro-LLM sentiment.)
by wilg | 2026-02-09 19:34:57+00:00
Ben Thompson has long been insistent that ChatGPT and other AI tools basically have to have ads and it's been a big mistake they didn't have them sooner. It's an interesting take:

> What I think is clear is they have to build an advertising product, and the reason they have to build an advertising product is any consumer Internet product has to be advertising, because it’s such a beneficial model to everyone involved, and the reason it’s so beneficial is you get to indefinitely and infinitely increase average revenue per user without any worries about price elasticity, because the entire increase in average revenue per user is borne by the advertisers who are paying it willingly because they’re getting a positive return on their investment, and everyone’s using it for free so you can reach the whole world. Then what happens with that is once you get that model going, you have a massive R&D advantage, because you have so much more money coming in than anyone who doesn’t have that cycle or who has to charge users for it.

https://stratechery.com/2026/ads-in-chatgpt-why-openai-needs...

> This point, more than anything else, explains why the company so desperately needs an advertising model. Advertising is the only potential business model that can meaningfully bend the revenue curve such that the company can not just fund its compute but gain leverage on it, for all of the reasons I laid out before: first, advertising increases the breadth of the business, in that you can offer a better product to more people, increasing usage and expanding inventory. Second, advertising increases the depth of the business, in that there is infinite upside in terms of average revenue per user: more usage means more inventory on one hand, and building out the capability for effective targeting and high conversion rates increases the amount that advertisers are willing to pay — even as the cost to the user remains the same (ideally free).

It's valuable to remember that advertisers will pay more per user than users will, and that's hard to beat in a competitive market.

Also, it's fascinating how much people _like_ ads when done properly. Ask normal people about Instagram ads, for example. They find them useful!
by OkayPhysicist | 2026-02-09 19:34:58+00:00
I doubt there are any states that don't currently have fractions in their curricula. The problem isn't standards, it's that large swathes of the country simply don't care about educating their children, as indicated at a societal level by where tax revenue goes, and at the individual level by parental involvement in children's education.

How to solve that short of charging people with neglect, I've got no idea.
by engelo_b | 2026-02-09 19:35:16+00:00
i'd love to see a safety heatmap layer, but the legal hurdles are probably massive. the second google puts a high risk badge on a specific road segment they open themselves up to lawsuits from local businesses or property owners claiming the algorithm is nuking their traffic or property value. it's probably going to stay in the hands of traffic engineers and underwriters for a long time.
by staplung | 2026-02-09 19:35:22+00:00
This is cool but it seems like it would be liable to drift. I.e. it "knows" the correct time but doesn't have any way to figure out that it's been driving the movement fast or slow by some number of milliseconds. Eventually, that will pile up to the point that it's not any better than running the thing off of batteries.

As the author points out, the cheap quartz mechanism has no way of reporting the position of the hands (other than the hands themselves) and that you have to set the PULSETIME constant by the right number of milliseconds. If you're off by even a millisecond, that's going to accumulate quick enough that it would make a difference over even a single day, wouldn't it?

EDIT: as some have pointed out, the Lavet stepper theoretically accounts for this in that it steps exactly one tick after so many oscillations. That number of oscillations does not change so that's all you need to get right.

However, that basically just kicks the can down the road a bit in that if each step is not exactly 1/60th of a circle or bits wear down or get sticky or you have analog noise in there you will presumably still have a source of biased drift that you won't be able to detect. But maybe those affects are small enough that they don't matter for a wall clock.
by randcraw | 2026-02-09 19:35:55+00:00
If fluid intelligence is based on the ability to recognize new patterns (unsupervised learning) and crystallized intelligence on recognizing known patterns (supervised learning), then more than physiology, age alone may differentiate the two.

Youngsters know no patterns so they can't match new events to known ones. Oldsters know that most seemingly new stuff is not really new, it's just the same old stuff, so they reduce the cost of thinking and reject the noise by adding the new unlabeled event to an existing cluster rather than creating a new noisy one. That's wisdom. But that's also a behavior that will inevitably increase as we age and our clusters establish themselves and prove their worth.

So aren't those two forms of intelligence less about a difference in brain physiology and more about having learned to employ common sense?
by spranab | 2026-02-09 19:35:56+00:00
Hi HN, I built SDF (Structured Data Format), an open protocol that sits between web content and AI agents.

The problem: Every agent that consumes a web page independently fetches HTML, strips boilerplate, extracts entities, and classifies content. A typical page is ~89KB of HTML (~73K tokens). When 100 agents consume the same URL, this extraction happens 100 times with inconsistent results.

What SDF does: Convert once into a schema-validated JSON document (~750 tokens) containing entities, claims, relationships, summaries, and type-specific structured data. Agents consume the pre-extracted representation directly.

Results from production deployment (2,335 documents, 10 content types):

99.2% token reduction from HTML
90% extraction accuracy with fine-tuned 1.5B + 3B model cascade
4.1x faster than monolithic 14B baseline
Downstream experiment: general-purpose 7B model scores 0.739 accuracy from SDF vs 0.352 from raw markdown (p < 0.05)
The pipeline runs locally on consumer hardware (dual RTX 3090 Ti). Fine-tuned models are open on HuggingFace (sdfprotocol/sdf-classify, sdfprotocol/sdf-extract). Protocol spec and JSON schemas are on GitHub.

Protocol spec + schemas: https://github.com/sdfprotocol/sdf
Whitepaper: https://doi.org/10.5281/zenodo.18559223
Models: https://huggingface.co/sdfprotocol
Happy to answer questions about the design decisions, the type system, or the evaluation methodology.
by lelanthran | 2026-02-09 19:35:58+00:00
> What are good alternatives to GitHub for private repos + actions? I'm considering moving my company off of it because of reliablity issues.

Dunno about actions[1], but I've been using a $5/m DO droplet for the last 5 years for my private repo. If it ever runs out of disk space, an additional 100GB of mounted storage is an extra $10/m

I've put something on it (Gitea, I think) that has the web interface for submitting PRs, reviewing them, merging them, etc.

I don't think there is any extra value in paying more to a git hosting SaaS for a single user, than I pay for a DO droplet for (at peak) 20 users.

----------------------

[1] Tried using Jenkins, but alas, a $5/m DO droplet is insufficient to run Jenkins. I mashed up shell scripts + Makefiles in a loop, with a `sleep 60` between iterations.
by tyre | 2026-02-09 19:36:10+00:00
It’s difficult to believe that they’ll keep privacy guarantees. Some of the most valuable types of targeting are lookalike audiences or following up from other ads elsewhere.

How would OAI allow them to target without access to de-anonymized data?

Buyers will want to exclude existing customers, which requires the same.

The product managers will have explicit KPIs tied to conversion. At some point, like at Google, this will break. It has to or OAI can’t grow into its current valuation, let alone any future one.
by c7b | 2026-02-09 19:36:25+00:00
> and the best monetization plans is ads.... Again?

Several of the biggest companies today are fueled by ads, and OpenAI has the perfect ad vehicle. What else were you expecting?

That's why local LLMs are important, and to preserve the current open weight models, because those are likely still untainted by ads. It won't be long until ad recommendations are directly baked into the weights of open models.
by liuliu | 2026-02-09 19:36:45+00:00
I agree. It is either ads, or Anthropic way (which is: you are too poor to use our ChatBot). There is no other way to pay the > $1 trillion per year CapEx for building these chat bots.

Would there be other way? Sure, it could be government-funded, like our public school system. But it is not possible in current political climate.

Money doesn't grow on trees, and tokens cost a lot of money. There will be divide into people who can afford these tokens and people who cannot. I feel it is better to have ways to let people who cannot afford these tokens to have some ways to try it.
by 3acctforcom | 2026-02-09 19:36:45+00:00
Honestly, this is HN and founders should pay attention to this. People don't want to host their own shit, they want a one-click easy switch. All of these alternatives have baggage.

This is your chance to start Bluesky for discord. A competently built, VC backed competitor to exploit a misstep only caused by government overreach due to their colossal market share. 26 million daily active users is a nice guaranteed market to start whittling away at, with an effective marketing campaign to drive a wedge between "little gamers, and big corporate enshittification."
by throwaway5752 | 2026-02-09 19:36:57+00:00
This is Microsoft. They forced a move to Azure, and then prioritized AI workfloads higher. I'm sure the traing read workloads on GH are nontrivial.

They literally have the golden goose, the training stream of all software development, dependencies, trending tool usage.

In an age of model providers trying train their models and keep them current, the value of GitHub should easily be in the high tens of billions or more. The CEO of Microsoft should be directly involved at this point, their franchise at risk on multiple fronts now. Windows 11 is extremely bad. GitHub going to lose their foundational role in modern development shortly, and early indications are that they hitched their wagon to the wrong foundational model provider.
by anonym00se1 | 2026-02-09 19:37:16+00:00
In case anyone was wondering what the Apple Car would have looked like inside, it would have been roughly this.

As an Apple Car™ it makes sense, but as a Ferrari it's incredibly soulless and oversimplified. This Ive design aesthetic (Dieter Rams' aesthetic really) is fine on consumer electronics where you want the device to disappear and give way to the display, but on something as emotional as a vehicle (Ferrari especially), this design falls flat.

I do hope some of the design details work their way through the industry (e.g. using glass instead of gloss black plastic, convex glass to add depth to digital gauges), but I hope the rest of it stays as a one-off experiment demonstrating the hubris and one-dimensionality of a top designer.
by 63 | 2026-02-09 19:37:18+00:00
I have no problem with experienced senior devs using agents to write good code faster. What I have a problem with is inexperienced "vibecoders" who don't care to learn and instead use agents to write awful buggy code that will make the product harder to build on even for the agents. It used to be that lack of a basic understanding of the system was a barrier for people, but now it's not, so we're flooded with code written by imperfect models conducted by people who don't know good from bad.
by crawshaw | 2026-02-09 19:37:42+00:00
Hi, author here. I mean the piece of code that calls the model and executes the tool calls. My colleague Philip calls it “9 lines of code”: https://sketch.dev/blog/agent-loop

We have built two of them now, and clearly the state of the art here can be improved. But it is hard to push too much on this while the models keep improving.
by crazygringo | 2026-02-09 19:37:57+00:00
Hilarious you found that reference.

I think it's obvious that's in reference to poorly written code. Or at least horrifically underdocumented/undercommented code.

There's a reason coders are constantly given the advice to write code for a future reader, not just the compiler/interpreter.

If I got code like Joel describes for a code review, I'm sending it back asking for it to be clearly commented.
by wtfHN26 | 2026-02-09 19:38:21+00:00
It's sad that OpenAI talking about developing AGI.

But the only revenue model that they still can come up with is Ads.

For all the advancement we have made in technology from the 90s web, social networks, mobile apps, ,AI Chat bots - the business model that almost all of them will eventually resort to is Ads.

We need some new breakthroughs in monetization side of things.
by cgh | 2026-02-09 19:38:27+00:00
This comment on the article sums it up for me, at least in part:

“Nobody knows how the whole system works, but at least everybody should know the part of the system they are contributing to.

Being an engineer I am used to be expert of the very layer of the stack I work on, knowing something of the adjacent layers, mostly ignoring how the rest work.

Now that LLMs write my very code, what is the part that I’m supposed to master? I think the table is still shifting and everybody is failing to grasp where it will stabilize. Analogies with past shifts aren’t helping either.‘
by pontussw | 2026-02-09 19:38:27+00:00
Working on a little "passion project" that has ended up consuming a lot of weekends now, but it's been a lot of fun.

I've been building https://photoweather.app because I never end up having time to look at weather forecasts, which means I also don't go out with my camera enough since outdoor photography is quite a weather dependent activity.. so I'm trying to turn this around by having the app tell me when and where I could be photographing instead.

It's a bit of a challenge for sure, weather forecasts are not always the most reliable, not to mention learning enough about weather to forecast photographic opportunities.. but it's also been really enjoyable to finally build something real and something that I myself actually use all the time.
by nathan_douglas | 2026-02-09 19:38:33+00:00
Bitwit: Learn CS, logic, and math theory (_not_ DSA) with spaced repetition: https://bit-wit.com/

I was hit by a big wave of depression last year. That crisis gave me a couple of periods of hyperfocus, and I thought I might as well use them to try to improve my mind and my ability to reason.

I haven't had good results learning certain subjects, like CS/math, with Anki or other flash card systems. The only thing that ever seemed to work for me was doing a lot of problems with pencil and paper. But without problems exercising those tools or techniques, they tended to just evaporate from my mind.

So my idea was to combine spaced repetition and problem presentation, and create a system for generating problems and validating their solutions randomly and parametrically. So successive presentations of the same card would present a different problem... and the overall effect would hopefully be that you learn the invariants that each card is trying to present, instead of memorizing some combination of variables and values. Sort of MathAcademy but for CS.

I _think_ it's feature-complete at this point, though I'm still working on validating and publishing cards (and there are a couple of things I wanna do to improve security). I'm pretty early in the dogfooding process, and I'm still the only person using it, and there are definitely bugs. But if anyone would like to try it out, I'd be delighted to hear your feedback (email in profile, also on site). Just maybe go a little easy on me right now, lol :/

The Boolean Logic and Lambda Calculus subjects are free forever, and the first topic of each other subject is also free, so if you're intrigued you can use it for quite some time (literally months) before even needing to provide an email address. No need to pay for anything.
by greggoB | 2026-02-09 19:38:45+00:00
> From a legal perspective, the Lai judgment reflects the institutional professionalism of Hong Kong's courts. The proceedings were conducted in accordance with established judicial practice, with extensive evidence presented, tested and assessed under the criminal standard of proof beyond reasonable doubt. The judgment, running more than 800 pages, was published in full, demonstrating the court's commitment to transparency and reasoned decision-making.

That's the 2nd paragraph in the article. In my experience, articles that have to go to this extent to really convince the reader that the court is so above rapproach have an agenda. And gee, coming from a CCP state media outlet, I wonder what that agenda could be...
by possiblelion | 2026-02-09 19:38:46+00:00
AskUCP – UCP protocol explorer showing all products on Shopify (https://askucp.com/)

On January 11th, Google and Shopify announced the Universal Commerce Protocol (ucp.dev). It's an open standard that lets any application query products across e-commerce platforms without needing APIs, integrations, or middlemen.
AskUCP is one of the first applications built on it.

Right now, if you want to buy something online, you have to know which store sells it. You go to Amazon, or you go to a Shopify store, or you go to Etsy. Each one has its own search, its own interface, its own checkout. The experience is fragmented because the infrastructure is siloed.

UCP changes this at the protocol level. If products are described in a standard format, any application can discover them. You don't need permission from each platform. You don't need to build integrations. Anybody or any AI agent just querys the protocol.

AskUCP is designed to be a single pane of glass into online commerce. You search once, and you see products from across the ecosystem. Currently, that means the entire Shopify catalog. As more platforms adopt UCP, their products become explorable too. Eventually, it should be everything.

This is a proof of concept. It's early, and there are rough edges. Let me know what you think, refinements, ideas etc etc.
by tyre | 2026-02-09 19:38:50+00:00
Or they view it as a differentiator and focus on a different segment. As I understand it, this is what Anthropic is doing:

1. Focus on businesses and developers

2. Make money on productivity and API platform

Enterprises are particularly sensitive about their data being farmed (e.g. note that paid Google accounts don’t have their emails used for ads.)

Keeping that trust is not a differentiator and existentially important to Anthropic.
by rockskon | 2026-02-09 19:38:52+00:00
You're right! Sometimes even the right-here-right-now claims of AI capabilities are horseshit too with people in actuality remotely controlling the product.

It's not common for present-capabilities to be lied about too. But it does happen!

And the smallest presence are the users who don't work in the AI industry but rave about AI. I know of...two....people who fit that bill. A lead developer at a cybersecurity firm and someone who works heavily in statistics and data analytics. Both of which are very senior people in their fields who can articulate exactly what they're looking for without much left to interpretation.
by rahimnathwani | 2026-02-09 19:39:08+00:00
An agent harness is what enables the user to seamlessly interact with both a model and tool calls. Claude Code is an agent harness.

┌────────────────────────────┐
│ User │
└──────────────┬─────────────┘
│
▼
┌────────────────────────────┐
│ Agent Harness │
│ (software interface) │
└──────┬──────────────┬──────┘
│ │
▼ ▼
┌────────────┐ ┌────────────┐
│ Models │ │ Tools │
└────────────┘ └────────────┘

Here's an example of a harness with less code: https://github.com/badlogic/pi-mono/blob/fdcd9ab783104285764...
by blampack | 2026-02-09 19:39:33+00:00
I'm working on https://videoreject.com

Video Reject is a platform for people to buy/sell physical media. Like Reverb but for physical media.

I love movies and wanted an excuse build something in that world. Its not necessarily groundbreaking, but I think it could build a nice community of folks with the same interests.

We're getting ready to launch, but in the meantime, we have a waitlist up.
by ajbt200128 | 2026-02-09 19:40:45+00:00
> we decide which ad to show by matching ads submitted by advertisers with the topic of your conversation, your past chats, and past interactions with ads.

> [...]

> Advertisers do not have access to your chats, chat history, memories, or personal details.

Going to hazard a guess that OpenAI is using LLMs to read convos and decide which ads you should see? Hopefully that's isolated and locked down. I can easily see that machinery turning from "what ad should we show this user" to "is this user doing something bad/a protected class etc.". Also terrifying to think that it may be the advertisers asking the questions to decide what ads to show...
by unsnap_biceps | 2026-02-09 19:40:54+00:00
I tried cooking with a Vision Pro. It was nice to throw up the recipe above the prep area, hovering, so I could prep and check off without messing up a book or print a copy just for single use.

I also liked throwing up a timer above each pot so it was simple to glance at the stove and see how long each pot had on it.

But the Vision Pro is bulky, hot, and heavy. I wouldn't try it again. I could imagine giving it another go with glasses, but I wouldn't be using the AI part of it.