skysight-inc/HackerNews huggingface dataset:
Sorry I wasn't clear enough, the cheap to validate part is only needed to train a large base model that can handle writing individual functions / fix bugs. Planning a whole project, breaking it down into steps and executing each one is not something that current LLMs struggle at.

Here's a recipe for a human level LLM software engineer:

1. Pretrain an LLM on as much code and text as you can (done already)

2. Fine tune it on synthetic code specific tasks like: (a) given a function, hide the body, make the model implement it and validate that it's functionally equivalent to the target function (output matching), can also have an objective to optimize the runtime of the implementation (b) introduce bugs in existing code and make the LLM fix it, (c) make LLM make up problems, write tests / spec for it, then have it attempt to implement it many times until it comes up with a method that passes the tests, (d-z) a lot of other similar tasks that use linters, parsers, AST modifications, compilers, unit tests, specs validated by LLMs, profilers to check that the produced code is valid

3. Distill this success / failure criteria validator to a value function that can predict probability of success at each token to give immediate reward instead of requiring full roll out, then optimize the LLM on that.

4. At test time use this final LLM to produce multiple versions until one passes the criteria, for the cost of an hour of a software engineer you can have an LLM produce millions of different implementations.

See papers like: https://arxiv.org/abs/2409.15254 or slides from NeurIPS that I mentioned here https://news.ycombinator.com/item?id=42431382
The USA is hardly unique in that regard. Other countries have had similar policy issues with major court decisions causing sweeping policy changes. And how could it be otherwise? When litigants ask the court for a decision, the court has to give an interpretation. Judges can't punt the issue to anyone else, they have to come down on one side or the other.

When a policy issue like abortion ends up in front of the appellate courts it's precisely because the laws are unclear. The legislators did a bad job and wrote vague laws. So the outcome of such cases will always be kind of a toss-up, especially for the most complex cases that make it to the Supreme Court level. Instead of complaining about justices legislating from the bench, voters should insist that Congress write better laws. I understand that sudden changes to established policy can be tremendously disruptive but the anger should be directed at the root cause.
>with a Luddism that somehow actually becomes a rather hilarious attempt at superiority

>The people who usually think LLMs aren't valuable to coders generally work on the most boring, copy/paste prattle.

Here you are doing the same thing, aren't you?

Instead of calling people names, the biggest tell of a weak argument, why don't you explain the type of work you do and how using an LLM is faster than if you coded it yourself and and/or also faster than any current way of doing the same thing.

I'm assuming you are a senior+ level coder.
This is a really uncharitable take.
> But every hero has a fatal flaw. America’s is its sharply increasing addiction to government debt.

A problem so big that even a non-American takes notice.
Agentic workflow is great only for demos without real business cases. Each agent can hallucinate, which will pass this hallucination to another agent. In the end, you have just garbage. But... It's better to be silent, we still need to inflate this bubble.
From the website:

> Modelica is a high-level declarative language for describing mathematical behavior. It is typically applied to engineering systems...

We use Modelica quite a bit in HVAC industry. In my case (controls engineer), I can request FMUs of various components from systems engineers for optimization work. (Functional Mockup Unit (FMU)[1]: stand-alone binary representing a dynamical system that can be driven by another application). My background is in Reinforcement learning/Model predictive control/python. Having a physics-driven model written in a domain-specific language which I can embed into my python workflow [2] is convenient.

I will say, Modelica requires a different perspective from "regular" imperative programming (python/matlab). It is a declarative language: you define equations, variables, constraints for a system, regardless of order. The compiler decides how to run the simulation; which variables to solve first etc.

While OpenModelica[3] has come a long way towards making an open source implementation of the language standard, proprietary applications (Dymola) still have an edge in the industry.

[1]: https://fmi-standard.org/

[2]: https://fmpy.readthedocs.io/en/latest/

[3]: https://openmodelica.org/
Modern communication systems rely on a canonical time source to coordinate the rotation of certificates. A host that cannot determine the time will be denied service, and an attacker who can control the time source can trick hosts into trusting expired certificates.

Since good timekeeping keeps everything else on the rails, having an on-prem stratum 1 server keeps more of your own critical infrastructure under your control.
To borrow another quote:

Plans are nothing, but planning is everything.

The process of building a plan builds the institutional knowledge you need to iterate when inevitably the original plan doesn’t work.
When a stakeholder comes back 6 months after project launch complaining about missing/incorrect features, I can't use throwaway code to prove the project was built to spec.
Expands beyond that really, people assume they need more than they do.

A TV stuffed with features sounds great even if they'd prefer a TV that does the bare minimum but takes less than a minute to start up

An SUV because of the one time every year or two where they may need a bigger vehicle (and would be better off renting a van)

A smartphone they can't use with one hand that doesn't fit in their pocket
As soon as we admit to ourselves that agent is just another word for context isolation among coordinated llm tasks.

Will agents still matter once models do a better job paying complete attention to large contexts?
The definition of agent is blurry. I prefer to avoid that term because it does not mean anything in particular. These are implemented as chat completion API calls + parsing + interpretation.
ERVs are not expensive, 1500 USD will get you a decent whole house unit. The installation is the expensive part, which this project doesn't change.
Yeah, a single `body { max-width: 50em }` is not going to change any of that, and actually makes it more accessible to a wider audience. The entire point of typography and formatting is to make text more accessible. Lack of layout is the antithesis of that.

Then there's the separate issue of overlong paragraphs, which is simply a sign of poor writing (again making the text less accessible), unless you're trying to argue that the use of fewer <p> tags makes the page faster to load and render?

Now, I do wish that browsers had saner default styles, so one wouldn't need even that single line of CSS, but that's not the world we live in, and for whatever backwards-compatibility reason we're stuck with how things were in 1995.
Modelica can absolutely be used for this, but there may not be a readily-available model created already. A generic stepper motor model is available here:

https://ie.utcluj.ro/files/acta/2003/Number%202/Paper08_Mora...

Operationalizing this into a Modelica model is pretty straightforward. Did not look for a driver model, but a driver model would be a lot more important in modern times. I am guessing that not many people would simulate this fidelity of stepping dynamics as a "first cut", and anyone who does is likely to also have a detailed driver model. Demand for this model in a standard library is likely quite small.
Well, "networking events" at least tend to be forced socialization of people basically looking for jobs as opposed to something more organic. Less true of meetups although they mostly never checked a lot of boxes for me either.
How does that matter to someone else asking questions?

I can’t even imagine a scenario where it would matter, other than if you got to control whether other users can click the reply button or not.

Edit: You may choose to ignore, deflect, or just leave, but the questions, and the button, will still be there regardless.
Resale value is probably a better metric, if it's $130 new and $100 second hand while the other one is $100 new and sub-$50 second hand that'll be a fairly good sign that it at least works.

It's still not 100% but it'd at least mean you're going to be out less money in the end if it's a dud for you.
It's certainly funny how popular "Defund the" is when it ends with, "[agency with a track record of actually providing service and value to both individual Americans and the country as a whole]" instead of "police". Turns out, conservatism is selective when it comes to preservation of institutions. One guess what the qualifier is.
Chinese national living in China, I am openly anti-CCP, I don't like Xi. I can write a thesis on this, but let's just cut to the bones -

12 years in power, Xi led China to become the largest industrialised nation on earth with its industrial output larger than the G7 combined, Xi led China to be in leading roles in ALL emerging sectors, e.g. mobile internet, renewable energy, Evs, AI etc when the entire EU and Japan just gave up.

What that 6 times bankruptcy Trump managed to achieve? Trump should be nice to Xi, as Xi is the only statesman of Trump's time, Trump is just a reality show host getting into a renewed season of his show.
Have definitely someone say, "well I tried Drizzle because the creators are good at shitposting on X."

I do not understand that at all, but maybe my reality is just substantially less mediated by "the conversation" that I don't get it. (Drizzle is fine BTW)
Sounds like your kid deserves a shoutout on dailystfu.com

In case it needs to be said, I'm kidding.
I’ve found the ai summarizer helpful for parsing my boyfriend’s drunk and or stoned emo texting.
Keisler book is excellent.
You don’t find the LM based spelling and word suggestions much better than the old ones?
All US states except Rhode Island and Hawai'i elect county sheriffs. There's nothing wrong with this, it is inherently a political office. Sheriffs are part of the executive branch and have no real judicial role.
You'd probably have to define agents first. What large / mega caps call agents is LLM + RAG + API Calls to read data and trigger jobs. And there are plenty of those online
Interesting! To me 80% hitrate sounds actually pretty good and awesome if it actually improves productivity, though understandably not something that could be left on it's own devices.

I had no idea about Make.com or n8n, they seem interesting. Thanks for the tip! Will check them out.
The world doesn’t elect US presidents. We are referring to the relationship of non-US citizen to US elected officials. The intra US selection of officials doesn’t matter in this context of who sits on a higher moral horse.
The JS community has no sense of quality. The community doesn't value things that are well abstracted or work well. I dread every moment I have to work in JS because everything is so badly done.
I wonder if some of those words might be terms-of-art, written with a specialist rather than a generalist audience in mind.
The first link for “Modelica Language” includes tutorials and examples. Five seconds of clicking around got me to:

> Let us consider an extremely simple differential equation:

x = (1-X)

Looking at this equation, we see there is only one variable, x

This equation can be represented in Modelica as follows:

model FirstOrder
Real x;
equation
der(x) = 1-x;
end FirstOrder;

This code starts with the keyword model which is used to indicate the start of the model definition.

The model keyword is followed by the model name, FirstOrder. This, in turn, is followed by a declaration of all the variables we are interested in.

[et cetera]
As someone who is a curious outsider to Modelica, it piqued my interest a few years ago when I found out that this language lets you write equations more directly than most other programming languages. Take the ideal gas law, for example, PV = nRT, which has 5 identifiers. In most programming languages, you'd have to keep only one variable to the left, that is assigned to, e.g. T=PV/nR, and a similar set of equations if you want to determine any of the other variables, given the rest. In Modelica, the same equation, expressed as you would in natural math, works for determining the unknown, based on the knowns.

https://mbe.modelica.university/behavior/equations/electrica...

I don't know much beyond this.
Same, it was something I played with maybe for 10 minutes, then forgot about.

Glad my iPhone 14 Pro isn't supported.
Yes, although -

My bull case is not that I particularly like their reforms, but that they demonstrate that substantive rather than incremental changes are possible at all.

Also perhaps that they rip out things that are supposedly doing something useful but sufficiently terrible at it they're not meaningfully helping, such that somebody not-them can later at least attempt to introduce a replacement that does.

Or: The vetocracy problem is very much real and reducing that could, in the medium to long term, be a huge win on net even if the things they do having reduced it in the short term are absolutely not the kind I would like to see either.
I think the original title is clickbait and the editorialization here is superior - I agree it would be better with a "slightly" or "may" or "is associated with", but that feels like picking nits.
We may need to temper our expectations. Those point clouds are "too clean".

Not exactly what you get in the real world, even with plenty of cleanup.
Decades of user interface research and design disagree with you. A handful of inline CSS rules would immediately make the content far more accessible and scannable across multiple platforms.

I am a huge proponent of minimalism. But minimalism doesn't mean doing nothing. It means doing a lot with a little.
To figure out what topics ChatGPT users are likely searching for, I’d start by using proxy data sources like Google Trends or keyword research tools like SEMrush or Ahrefs. These tools can give you a decent idea of popular search topics around LLMs, AI assistants, or conversational tools—stuff that might overlap with what people ask ChatGPT. I’d also keep an eye on forums like Reddit or Quora, or even Twitter, where people tend to discuss these tools a lot. Spotting recurring questions or themes there could help you get a sense of what users are after.

Another option would be to look into Chrome extensions made for ChatGPT. Some of these plugins might collect anonymized data, and their descriptions or user reviews could hint at common patterns. That said, to get anything really useful, you’d probably need to either reach out to the authors of those extensions or create your own. If you go the second route, you could build an extension that improves the ChatGPT experience in some way while (with consent, obviously) gathering anonymized data on user queries and interactions. Just make sure it’s privacy-compliant and adds actual value to the user—otherwise, no one’s gonna use it!
https://archive.is/mZcao
It's not in the US strategic interests for China to control the most popular social media (aka propaganda) site, so from a realpolitik perspective this makes a ton of sense. Reliance on a foreign power for things that are so prevalent is a risk, and it's not like the US is incapable on a technical level of producing a TikTok alternative - it's "only" popular because of network effects.

FWIW I mostly agree that your take seemed to be a likely outcome if Harris had been elected, but I literally have no idea what the new administration will do.
$3 trillion dollar company. What are they doing with the money? I'm baffled they could still be putting out anything less than exceptional quality.
I would welcome DOGE focusing on how much velocity it will increase and how many lines of bad policy it will remove. Likewise, cutting inefficient people should instead be replacing them.

It is so hard to make progress within gov, so focusing on firing and demoralizing makes the environment even more afraid to move, and inefficiency even more of a self-fulfilling prophecy.

As a counterpoint, I'm happy for the pro-AI discussions as these systems have been difficult to move forward. Many senior people are working to figure out how to legally do it, so dictates cutting red tape for them, not headcount, is welcome, and would let them focus on the project phases they actually want to do.

We work with multiple groups at the federal level, and while some people our peers interact with I do wish were out of the way, those are a minority, and more of a symptom. The ultimate problem is the procedures being tasked, the underlying mandates & regulations driving them, and lack of ability to succeed despite these. Imagine if your IT department was largely run by lawyers who fear jail time for any sign of malpractice because that's what the law says and they've built up defensive practices over the years as different situations came up. Of course the default is 'no'! The solution is not to stop having an IT department, but to fix the policy problems and rotate leadership for the new culture.
This read to me as if someone asked a LLM to create a facebook urban legend about a bad programmer and prompted it with a couple bullet points.

If it contained the words “you’ll never believe what happened next…” they would be completely at-home.
Communicating with the drones is nearly impossible.
Editable files! A project might have tens of files in it and you’ll find yourself having to toggle which ones are in the active set. It’s maddening!
> ChatGPT thinks 9.11 > 9.9

I've confirmed this asked chatgpt:
9.11 > 9.9 true or false?

True because .11 is greater than .9
As a side note, while I know of several language model based systems that have been deployed in companies, some companies don't want to talk about it:

1. Its still perceived as an issue of competitive advantage

2. There is a serious concern about backlash. The public's response to finding out that companies have used AI has often not been good (or even reasonable) -- particularly if there was worker replacement related to it.

It's a bit more complicated with "agents" as there are 4 or 5 competing definitions for what that actually means. No one is really sure what an 'agentic' system is right now.
There's a lot of work showing that we can reliably get to or above human level performance on tasks where it's easy to sample at scale and the solution is cheap to verify.
In the early wild-west days of ecommerce a friend working as a tester at a well known British supermarket discovered that the backend card-validation logic on their payment form was essentially "return true" ... good thing the volumes were miniscule I guess?
This trope was a slight exaggeration then and is basically false now. It exists in the modern world mostly to validate purchasing decisions of the middle class.

In an industrial world where most things made in volume are quite cheap relative to incomes quantifiable results per dollar plateau very quickly and beyond that you're mostly for emotion, brand, signaling, etc.

People default to cheap not because they're stupid but because "buy the cheapest thing that will work" delivers very good results when applied to all of one's purchasing. It's the index fund of personal finance. You can do better with specialist knowledge or techniques but that doesn't scale.
They specifically compare to client-side least-loaded with Po2C in section 5.2/figure 7.
Accessible to whom? I work in a field that uses things like Modelica and it reads just fine to me.
You are totally correct - I was thinking of 'picture messages' which this could send. I was only a little jealous of the 3210 as i thought it was quite ugly really, but the 3310 seemed a heap better, especially with the blue led (which is what sold me on the 8250).
pen and paper for the win!
I recently gave a talk on this topic though it was more focused on code-based CAD, and with extra emphasis on Rust because it was at a Rust meetup. But very similar vibes overall, I think there will be many software engineers picking up CAD and 3D printing in the near future.

https://youtu.be/0wn7vUmWQgg
Running NetBSD on IBM ThinkPad 380Z
The few things I’ve tried on my iPad which supports Apple Intelligence haven’t worked so the fact that’s there’s a rollout of isolated features that is not clear to the user doesn’t help. I tried some of the stuff I saw in commercials and it failed miserably ha
It's all HTTP/1.1 at the application layer, still. The HTTP/2 and HTTP/3 are mostly a binary encoding scheme (to use on top of good old TLS on top of TCP) and a different transport protocol (on top of UDP instead of TCP), respectively, but their goal is to carry good old HTTP/1.1 messages around.
Uniweather.js: Get weather data directly from national weather services
Show HN: Source to Prompt- Turn your code into an LLM prompt with more features
Your Source to Prompt-- Turn your code into an LLM prompt, but with way more features!

I just made this useful tool as a single html file that lets you easily turn your coding projects into targeted single text files for use in LLM prompts for AI-aided development.

Unlike the many other existing competing projects-- to name just a few:

1. [files-to-prompt](https://github.com/simonw/files-to-prompt)
2. [repo2txt](https://repo2txt.simplebasedomain.com/)
3. [code2prompt](https://github.com/mufeedvh/code2prompt)
4. [repomix](https://github.com/yamadashy/repomix)
5. [ingest](https://github.com/sammcj/ingest)
6. [1filellm](https://github.com/jimmc414/1filellm)
7. [repo2file](https://github.com/artkulak/repo2file)

...there are some real advantages to this one that make it stand out:

* It's a single html file that you download to your local machine-- that's it! just open in a modern browser like chrome and you can use it securely.

* Because it's locally hosted, with no requirements like python or anything else, it's very quick to get it running on any machine, and because it's local, you can use it on your own private repos without worrying about using a github authorization token or similar annoyance.

* You don't even need to be working with a repo at all, it works just as well with a regular folder of code files.

Also, I added tons of quality of life improvements that were major pain points for me personally:

These include laboriously re-selecting the same or very similar subset of files over and over again; now you can save a preset (either to localStorage in the browser or exported and saved as a JSON file) and dramatically speed this up. There are also a few other features to speed up the file selection process, such as quick string based filtering on file names, and common quick selection patterns (such as "select all React files").

It also keeps track of the total size in KB and lines of text that have been selected in a handy tally section which is always visible in the upper right corner, so you always know when you are reaching the maximum of the context window of whatever model you're working with. Based on my experience, I added in warnings for GPT4o and o1 and also Claude3.5 Sonnet.

Before the listing of the files and their contents, it also automatically includes the hierarchical file/folder structure of the files you select, and next to each one, shows the size in KB and the number of lines, which helps give the model context about which files are the most important.

I also added the ability to minify the code so you can cram more into the context window. Similarly, you can also strip out code comments, and it will tell you how much space this saved.

You can also specify a "preamble" that you can save and quickly edit, as well as a "goal" where you specify what you're trying to accomplish. All of this can be included in your saved presets to save you time.

I hope you find it useful!