MurphyA/hacker-news huggingface dataset:
by binarymax | 2025-08-08 17:55:09+00:00
Yes. I found this out because I have a small tool I maintain for OpenAI API integration - and my integration test suite triggered this for the streaming case. The non-streaming cases didn't trigger the requirement.

FWIW I am definitely not opting in to this overreach and will use a different provider if necessary. I currently use GPT-4o for some streaming apps I have, but will migrate away from this requirement.
by coffeecoders | 2025-08-08 17:55:10+00:00
To put it bluntly, the current state of AI often comes down to this: describing a problem in plain English (or your local language) vs writing code.

Say, “Give me the stock status of an iPhone 16e 256GB White in San Francisco.”

I still have to provide the API details somewhere — whether it’s via an agent framework (e.g. LangChain) or a custom function making REST calls.

The LLM’s real job in this flow is mostly translating your natural language request into structured parameters and summarizing the API’s response back into something human-readable.
by TZubiri | 2025-08-08 17:55:34+00:00
So wikipedia and wikidata?

This actually happened already and it's part of why llms are so smart, I haven't tested this but I venture a guess that without wikipedia and wikidata and wikipedia clones and stolen articles, LLMs would be quite a lot dumber. You can only get so far with reddit articles and embedded knowledge of basic info on higher order articles.

My guess is when fine tuning and modifying weights, the lowest hanging fruit is to overweigh wikipedia sources and reduce the weight of sources like reddit.
by tossandthrow | 2025-08-08 17:55:34+00:00
First, my comment was overly snarky - I can see the karma counter jumping up and down like a rabbit which is fair.

Personally, I see the central governance responsibility as ensuring a peopsperous society.

This must necessarily include a high level of equality.

Equality can be achieved using capital systems and market economies.

The US is failing hard at being a good country these years.
by tracker1 | 2025-08-08 17:57:10+00:00
I'm more inclined to go with N305/N355 myself for the extra compute (more images/containers). But they're a pretty decent option. I setup a "forbidden router" at a friend's using one. Been working great for his home use... proxmox, opnsense for routing, wireguard, pihole, docker-vm running his AP control software, and a trunas scale VM serving a USB hard drive for home backups.

At home, I'm using a 5900H based mini-pc I bought a few years ago and a synology nas.
by muzani | 2025-08-08 17:58:00+00:00
If you were to objectively rank things, durian would be the best fruit in the world, python would be the best programming language, and the Tesla Model Y is the best car. Everyone has multiple inconsistent opinions on everything because everything is not the same.

Just pick something and use it. AI models are interchangeable. It's not as big a decision as buying a car or even a durian.
by echelon | 2025-08-08 17:58:43+00:00
> This is a massive cope. AI image/video slop is still slop.

Slop content is slop content, AI or not. You don't need an AI to make slop. We've always had films like "The Room", it's just that the financial and time constraints put an upper bound on how much slop was created. AI makes creation more accessible. You've got Reddit for image and video now, essentially.

You are biased by media narratives and slop content you're encountering on social media. I work in the industry and professionals are using AI models in ways you aren't even aware of. I guarantee you can't identify all AI content.

> And if we allow it to take over society, we'll end up with a society that's also slop. Netflixification/marvelization only much much worse..

Auteurs and artists aren't going anywhere. These tools enable the 50,000 annual film students to sustainably find autonomy, where previously there wasn't any.
by mrspence | 2025-08-08 17:59:23+00:00
Hey everyone,

My friend and co-founder just released version 1.0 of Nanocoder, a CLI tool he's been building, to make it easier to locally code agentically, with large language models through Ollama and OpenRouter.

This is all in your terminal, to offer a similar experience to Claude Code and Gemini CLI.

Right now it’s very much MVP stage - works well enough to be useful, but rough around the edges. The goal is to add more features (better context handling, more tools, improved UX), and make it truly awesome for coding work.

I am a big believer in privacy and like Will, I'm a big believer in AI being open and for the people, not locked behind subscriptions or proprietary APIs. That’s why it’s open source and we're hoping to build it as a community.

If you think this is cool, I’d be grateful for GitHub stars and contributors to help shape where it goes next. Feedback, feature ideas, bug reports - all welcome!

https://github.com/Mote-Software/nanocoder
by ninetyninenine | 2025-08-08 17:59:52+00:00
No AI is impressive because we built a machine that finally understands what we are saying and has a concept of what creativity is. It's rudimentary but it's a milestone for humanity.

It's social media and the endless barrage of generated AI that's creating the illusion that AI isn't impressive. You're inundated everyday with the same crap and is just making it less and less impressive.
by famouswaffles | 2025-08-08 18:00:18+00:00
I'm not a researcher.

I acknowledge Mamba, RWKV, Hyena and the rest but like I said, they fall under the LLM bucket. All these architectures have 7B+ models trained too. That's not no investment. They're not "winning" over transformers because they're not slam dunks, not because no-one is investing in them. They bring improvements in some areas but with detractions that make switching not a straightforward "this is better", which is what you're going to need to divert significant funds from an industry leading approach that is still working.

What happens when you throw away state information vital for a future query ? Humans can just re-attend (re-read that book, re-watch that video etc), Transformers are always re-attending, but SSMs, RWKV ? Too bad. A lossy state is a big deal when you can not re-attend.

Plus some of those improvements are just theoretical. Improved inference-time batching and efficient attention (flash, windowed, hybrid, etc.) have allowed transformers to remain performant over some of these alternatives rendering even the speed advantage moot, or at least not worth switching over. It's not enough to simply match transformers.

>Because I don't understand why you're arguing against that.

I'm not arguing anything. You asked why the disproportionate funding. Non-transformer LLMs aren't actually better than transformers and non-LLM options are non-existent.
by belter | 2025-08-08 18:00:29+00:00
It's Ok. Sam Altman still has five months until the end of the year.

"Sam Altman predicts AGI in 2025" - https://christiankromme.nl/sam-altman-predicts-agi-in-2025/

"Sam Altman says ‘we know how to build AGI’" - https://www.theverge.com/2025/1/6/24337106/sam-altman-says-o...
by cowpig | 2025-08-08 18:01:12+00:00
I was excited by the announcement but then

> Runs in an isolated sandbox Every task runs in a secure, isolated Daytona sandbox.

Oh, so fake open source? Daytona is an AGPL-licensed codebase that doesn't actually open-source the control plane, and the first instruction in the README is to sign up for their service.

> From the "open-swe" README:

Open SWE can be used in multiple ways:

* From the UI. You can create, manage and execute Open SWE tasks from the web application. See the 'From the UI' page in the docs for more information.

* From GitHub. You can start Open SWE tasks directly from GitHub issues simply by adding a label open-swe, or open-swe-auto (adding -auto will cause Open SWE to automatically accept the plan, requiring no intervention from you). For enhanced performance on complex tasks, use open-swe-max or open-swe-max-auto labels which utilize Claude Opus 4.1 for both planning and programming. See the 'From GitHub' page in the docs for more information.

* * *

The "from the UI" links to their hosted web interface. If I cannot run it myself it's fake open-source
by sophacles | 2025-08-08 18:01:17+00:00
> do you need more space than 2TB ?

Yes.

> (excluding things you've downloaded from the internet)

Why on earth would I do that? My storage includes things I downloaded from the internet that are not there anymore/hard to find/now paywalled. If you were thinking the only thing to download from the internet is pirated media - I haven't included that in my >2TB assessment.
by godelski | 2025-08-08 18:01:18+00:00
> exclusively this way.

I think an important part is to recognize that fundamental research is extremely foundational. We often don't recognize the impacts because by the time we see them they have passed through other layers. Maybe in the same way that we forget about the ground existing and being the biggest contributor to Usain Bolt's speed. Can't run if there's no ground.

But to see economic impact, I'll make the bet that a single mathematical work (technically two) had a greater economic impact than all technologies in the last 2 centuries. Calculus. I haven't run the calculations (seems like it'd be hard and I'd definitely need calculus to do them), but I'd be willing to bet that every year Calculus results in a greater economic impact than FAANG, MANGO, or whatever the hot term is these days, does.

It seems almost silly to say this and it is obviously so influential. But things like this fade away into the background the same way we almost never think about the ground beneath our feet.

I have to say this because we're living in a time where people are arguing we shouldn't build roads because cars are the things that get us places. But this is just framing, and poor framing at that. Frankly, part of it is that roads are typically built through public funds and cars through private. It's this way because the road is able to make much higher economic impact by being a public utility rather than a private one. Incidentally, this makes the argument to not build roads self-destructive. It's short sighted. Just like actual roads, research has to be continuously performed. The reality is more akin to those cartoon scenes where a character is laying down the railroad tracks just in front of the speeding train.[0] I guess if you're not Gromit placing down the tracks it is easy to assume they just exist.

But unlike actual roads, research is relatively cheap. Sure, maybe a million mathematicians don't produce anything economically viable for that year and maybe not 20, but one will produce something worth trillions. And they do this at a mathematician's salary! You can hire research mathematicians at least 2 to 1 for a junior SWE. 10 to 1 for a staff SWE. It's just crazy to me that we're arguing we don't have the money for these kinds of things. I mean just look at the impact of Tim Berners Lee and his team. That alone offsets all costs for the foreseeable future. Yet somehow his net worth is in the low millions? I think we really should question this notion that wealth is strongly correlated to impact.

[0] Why does a 10hr version of this exist... https://www.youtube.com/watch?v=fwJHNw9jU_U
by jjfoooo4 | 2025-08-08 18:01:22+00:00
There's certainly a symbiosis blog publishers and small startups wanting to be perceived as influential, and big companies releasing models and wanting favorable coverage.

I heavily discount same day commentary, there's a quid pro quo on early access vs favorable reviews (and yes, folks publishing early commentary aren't explicitly agreeing to write favorable things, but there's obvious bias baked in).

I don't think it's all particularly concerning, you can discount reviews that are coming out so quickly that's it's unlikely the reviewer has really used it very much.
by divan | 2025-08-08 18:01:34+00:00
I just want it to be able to read/edit text files. Coding agents can edit code, but for writing we're limited to copy-pasting dance.

I use projects for research purposes for articles/scripts/etc, and I would love to use chatgpt in voice mode to talk about the article I'm writing. Like "hey, read last paragraph from the article... let's elaborate on topic X... here what I would love to write - x,y,z - please improve the style and read it back to me... nice, add it as a next paragraph."
by Refreeze5224 | 2025-08-08 18:02:13+00:00
The point still stands that people who committed "illegal entry" are the backbone of our society.

This whole immigration crackdown is about racism, not law and order. They would go after the employers of these immigrant if they actually wanted to stop it. Notice how they are considering giving farmers a break for employing "illegals", because they know how dependent our food supply is on them.
by gnabgib | 2025-08-08 18:02:23+00:00
Princeton $250k(tuition) $150k (tuition and expenses), joining:

Harvard $200k(tuition) $100k (tuition and expenses) (82 points, 5 months ago, 106 comments) https://news.ycombinator.com/item?id=43393478

MIT $200k(tuition) $100k (tuition and expenses) (737 points, 9 months ago, 459 comments) https://news.ycombinator.com/item?id=42195895

Albert Einstein College of Medicine free tuition (491 points, 1 year ago, 411 comments) https://news.ycombinator.com/item?id=39516927
by amai | 2025-08-08 18:02:25+00:00
This tax was introduced because in the past some "smart" billionaires moved to Switzerland and by that avoided paying any taxes in Germany at all.

https://de.wikipedia.org/wiki/Wegzugsbesteuerung

So thank your greedy ancestors for that.

In addition it is mentioned in the article above that it is possible to pay this tax over a time period of seven years. So you don't have to pay it all at once.
by ActionHank | 2025-08-08 18:02:37+00:00
"If you are only using your hammer to hammer nails, you're doing it wrong" then goes on to explain how you should use agents.

I would've thought that following the initial argument and the progression to the latest trend we would've ended at use agents and write specs and these several currently popular MCPs.

I guess my rant is it to arrive at the point that no one knows what the "correct" way to use them is yet. A hammer has many uses.
by recipe19 | 2025-08-08 18:02:40+00:00
Sort of, but if the objective is to get hired for a hardware design job, I think that even the font aside, the overall aesthetics of the PCB aren't great. There are several places where component text overlaps other markings, some components are slightly offset from others for no reason, the pattern of stitching vias is pretty chaotic... I think it's actually the software part of it that's most worthwhile.
by annoyingnoob | 2025-08-08 18:04:48+00:00
I love infrastructure. I run my own services at home too, and have for many years. But to be honest, the older I get the less fun it is to deal with issues that come up from time to time.

At some point you'll need to upgrade hardware and software, you get to do the exercise over again. There will always be lessons learned and its get better each time. Its still work.
by godelski | 2025-08-08 18:05:08+00:00
Along those lines, I also want something that will correct me if I am wrong. The same way a human would or even the same way Google does because typing in something wrong usually has enough terms to get me to the right thing, though usually takes a bit longer. I definitely don't want something that will just go along with me when I'm wrong and reinforce a misconception. When I'm wrong I want to be corrected sooner than later, that's the only way to be less wrong.
by Quarrelsome | 2025-08-08 18:05:26+00:00
we have to accept that the vast majority of people don't think like us. They don't think its complete garbage because they can't look hard enough to appreciate that fidelity.

While it might be better if everyone thought like us and wanted things to be _fundamentally_ good, most people don't, and most people money >> less people money and the difference in scale is vast. We could try to build a little fief where we get to set the rules but network effects are against us. If anything our best shot is to try to reverse the centralisation of the internet because that's a big cause of enshittification.
by mattkrick | 2025-08-08 18:05:30+00:00
I want to believe, and I promise I'm not trying to be a luddite here. Has anyone with decent (5+ years) experience built a non-trivial new feature in a production codebase quicker by letting AI write it?

Agents are great at familiarizing me with a new codebase. They're great at debugging because even when they're wrong, they get me thinking about the problem differently so I ultimately get the right solution quicker. I love using it like a super-powered search tool and writing single functions or SQL queries about the size of a unit test. However, reviewing a junior's code ALWAYS takes more time than writing it myself, and I feel like AI quality is typically at the junior level. When it comes to authorship, either I'm prompting it wrong, or the emperor just isn't wearing clothes. How can I become a believer?
by quantdev1 | 2025-08-08 18:05:51+00:00
> I think something people really misunderstand about these tools is that for them to be useful outside of very general, basic contexts, you have to already know the problem you want to solve, and the gist of how to solve it - and then you have to provide that as context to the LLM.

Politely need to disagree with this.

Quick example. I'm wrapping up a project where I built an options back-tester from scratch.

The thing is, before starting this, I had zero experience or knowledge with:

1. Python (knew it was a language, but that's it)

2. Financial microstructure (couldn't have told you what an option was - let alone puts/calls/greeks/etc)

3. Docker, PostgreSQL, git, etc.

4. Cursor/IDE/CLIs

5. SWE principles/practices

This project used or touched every single one of these.

There were countless (majority?) of situations where I didn't know how to define the problem or how to articulate the solution.

It came down to interrogating AI at multiple levels (using multiple models at times).
by jandrese | 2025-08-08 18:05:57+00:00
No names is not the biggest problem. You just have to come up with a name. The problem is when things have multiple names, or even worse when people disagree on what names are appropriate for something. The world rarely allows you to neatly categorize large datasets. There are always outliers.

For example, you have a set of balls and you want to sort them by color. Where does orange stop and red begin? What about striped balls or ones with logos printed on them? What if it is a hypercolor ball that changes based on heat? It gets messy very fast.
by binarymax | 2025-08-08 18:06:28+00:00
I've seen that, but I've also seen (from both sides) a total lack of understanding on what to do that consultants came in to help. I am/have been a search relevance consultant for years - I've seen lots of teams just without a clue how to make things better, and we did. I've also been on the other side where for the life of us we could not decide how to price a product, and had pricing consultants come in and get us out of our paralysis.
by placardloop | 2025-08-08 18:06:37+00:00
This feels like you’re applying absolutes to a massive industry with wildly varying standards for peer review and work product.

I was a consultant for years at a Big4 and I can personally attest to a lot of the stuff I was producing as a 22 year old going straight to the client leadership with zero oversight or review from my higher ups. Whether something got extensive quality checks was dependent on the type of work, notoriety of the client, and of course personal management styles of the partners involved.

In several of my projects, nobody on the team had experience with a particular topic, including the senior management, but the client was all told we did. The juniors on the project were then expected to put together product and deliver it, and none of it was reviewed by the higher ups (not like they had any expertise in it to provide feedback anyway).
by libraryofbabel | 2025-08-08 18:06:43+00:00
Yeah, agree that the benchmarks don't really seem to reflect the community consensus. I wonder if part of it is the better symbiosis between the agent (Claude Code) and the Opus and Sonnet models it uses, which supposedly are fine-tuned on Claude Code tool calls? But agree, there is probably some additional secret sauce in the training, perhaps to do with RL on multi-step problems...
by whateveracct | 2025-08-08 18:07:26+00:00
That's why it's not the only option. It's a benefit not a restriction. The powers that be saw an opportunity for insurers to cover less and insurees to leverage that into a different benefit. It's all just about shifting risk around and taking a little off the top.

It's a nice incremental addition to the existing system. Way more feasible than changing the system.
by Animats | 2025-08-08 18:07:26+00:00
> We're seeing the opposite. Instead, all the competing models are basically converging on the same benchmark performance numbers...

That question is really important. Comments on that? Maybe LLMs are asymptotically approaching some fundamental limit for that technology.

What goes on inside an LLM hasn't changed much in years. More data and more compute is thrown at that little kernel that makes it all go. Additional gimmicks are added around the core algorithm. But there's not much progress down at the bottom. There's no reaching into the net and extracting a reliable "don't know". Is there an upper limit to what that architecture can do? AGI may not be reachable by this route.

Maybe someone will find a way around that limit. The field has way too much money, too much visibility, and too many people. The technology works, although it has limits.
by gen220 | 2025-08-08 18:07:55+00:00
I forget where I read this, but it's impossible to get it out of my mind after I heard it!

"Consulting is a job laundering program. We use the allure of travel points, prestige, and a six figure income to match some of our country's best and brightest minds to work on capitalism's most banal problems."

What 21 year old Stanford grad would want to work in the back office of a paper mill in Ohio? Sure, sure, but if we told them, instead, they were working for a Big 4 Consulting firm? :)
by vineyardmike | 2025-08-08 18:08:25+00:00
> At the moment it feels like most people "reviewing" models depends on their believes and agenda, and there are no objective ways to evaluate and compare models

I think you’ll always have some disagreement generally in life, but especially for things like this. Code has a level of subjectivity. Good variable names, correct amount of abstraction, verbosity, over complexity, etc are at least partially opinions. That makes benchmarking something subjective tough. Furthermore, LLMs aren’t deterministic, and sometimes you just get a bad seed in the RNG.

Not only that, but the harness and prompt used to guide the model make a difference. Claude responds to the word “ultrathink”, but if GPT-5 uses “think harder”, then what should be in the prompt?

Anecdotally, I’ve had the best luck with agentic coding when using Claude Code with Sonnet. Better than Sonnet with other tools, and better than Claude Code with other models. But I mostly use Go and Dart and I aggressively manage the context. I’ve found GPTs can’t write zig at all, but Gemini can, but they can both write python excellently. All that said, if I didn’t like an answer, I’d prompt again, but liked the answer, never tried again with a different model to see if I’d like it even more. So it’s hard to know what could’ve been.

I’ve used a ton of models and harnesses. Cursor is good too, and I’ve been impressed with more models in cursor. I don’t get the hype of Qwen though because I’ve found it makes lots of small(er) changes in a loop, and that’s noisy and expensive. Gemini is also very smart but worse at following my instructions, but I never took the time to experiment with prompting.