MurphyA/hacker-news huggingface dataset:
by a_squirrel | 2025-09-05 16:03:37+00:00
Location: Washington, DC Area. East Coast, United States Remote: I'm open to remote and on-site with no preference

Willing to relocate: Yes

Technologies: Java, Python, JavaScript, Ruby, Ruby on Rails, C++, C, a little bit of React and Angular 2

Résumé/CV: https://1drv.ms/b/c/46d1fdb68a721574/ERkpEotrOltLly0j74zyXdI...

Email: bepotts47@gmail.com

Hello! I'm a software developer with lots of experience in full stack and backend development. I was most recently a developer at SirusXM Radio until I was laid off recently. The languages I've used the most are Java, C++, Ruby ( Ruby on Rails ), Python, and JavaScript. I've also worked over a year in a classified setting and I still hold a security clearance. I'm looking for a junior/entry level software engineer position.

I attended Virginia Tech for three years and studied Computer Science and Math. I got the core CS curriculum completed; the part I didn't complete were the electives. I had to stop attending because I ran out of money.

Due to my current financial situation, unfortunately I'll require a salary position - no equity only.

With all that said, I'm open to having a conversation with anyone. Thanks! :)
by postflopclarity | 2025-09-05 16:03:40+00:00
first and foremost great documentation & design docs cannot be surpassed as a tool to explain and understand code. and that is entirely language agnostic.

more generally, the most important bits of a particular function to understand is

* what should it be called with

* what should it return

* what side effects might it have

and the "what" here refers to properties in a general sense. types are a good shortcut to signify certain named collections of properties (e.g., the `Int` type has arithmetic properties). but there are other ways to express traits, preconditions, postconditions, etc. besides types
by firasd | 2025-09-05 16:03:49+00:00
I wrote this to argue that the GPT-5 rollout backlash wasn't just users hating change, but a rational response to a functional product downgrade.

My thesis is that "personality is utility." The collaborative "vibe" of 4o wasn't a bug; it was a feature that produced better results. OpenAI replaced a transparent creative partner with an opaque, cost-optimized answer engine and was surprised when users revolted.

I've tried to ground this by connecting the emotional Reddit posts to the concrete frustrations of experts who were all complaining about the same loss of agency and transparency, just in different terms. Curious to hear your thoughts.
by calebchiang | 2025-09-05 16:04:26+00:00
Most logo tools are either overpriced, bloated, or require design skills you don’t have. I built LogoPogo to fix that.

With LogoPogo you can:

- Generate clean, modern logos by just describing them in text

- Get 20 logos for $9.99 (instead of paying $20+ for one)

- Edit, download, and access all your logos in one place

It’s perfect for developers, indie hackers, and small businesses who just need a professional logo fast—without hiring a designer.
by jsmith45 | 2025-09-05 16:04:32+00:00
Why would this be? I'm probably missing something.

Don't these LLMs fundamentally work by outputting a vector of all possible tokens and strengths assigned to each, which is sampled via some form of sampler (that typically implements some softmax variant, and then picks a random output form that distribution), which now becomes the newest input token, repeat until some limit is hit, or an end of output token is selected?

I don't see why limiting that sampling to the set of valid tokens to fit a grammar should be harmful vs repeated generation until you get something that fits your grammar. (Assuming identical input to both processes.) This is especially the case if you maintain the relative probability of valid (per grammar) tokens in the restricted sampling. If one lets the relative probabilities change substantially, then I could see that giving worse results.

Now, I could certainly imagine blindsiding the LLM with output restrictions when it is expecting to be able to give a freeform response might give worse results than if one prompts it to give output in that format without restricting it. (Simply because forcing an output that is not natural and not a good fit for training can mean the LLM will struggle with creating good output.) I'd imagine the best results likely come from both textually prompting it to give output in your desired format, plus constraining the output to prevent it from accidentally going off the rails.
by daveguy | 2025-09-05 16:04:35+00:00
The very first transcontinental railroad included telegraph communications infrastructure. [0] The dependence is necessary because it's so critical for safety and scheduling.

The US congressional committee that recommended construction of the railroad was called the "Select Committee on the Pacific Railroad and Telegraph".

So it seems very early it was decided that no, rail transit systems should not be built without communications/publishing infrastructure.

[0] https://en.wikipedia.org/wiki/First_transcontinental_railroa...
by catgary | 2025-09-05 16:04:53+00:00
I agree with you that writing kernels isn’t necessarily the most important thing for most ML devs. I think an MLIR-first workflow with robust support for the StableHLO and LinAlg dialects is the best path forward for ML/array programming, so on one hand I do applaud what Mojo is doing.

But I’m much more interested in how MLIR opens the door to “JAX in <x>”. I think Julia is moving in that direction with Reactant.jl, and I think there’s a Rust project doing something similar (I think burn.dev may be using ONNX has an even higher-level IR). In my ideal world, I would be able to write an ML model and training loop in some highly verified language and call it from Python/Rust for training.
by dannyphantom | 2025-09-05 16:05:05+00:00
There is a silly scene in a movie called ‘Liar Liar’ that I used to love as a kid about the importance of not delaying a visit; the underlying plot is that Fletcher (Jim Carrey) is unable to is lie following his son making a birthday wish.

Fletcher: Your honor, would the court be willing to grant me a short bathroom break?

Judge: Can't it wait?

Fletcher: Yes it can. But I've heard that if you hold it you could damage the prostate gland, making it very difficult to get an erection, or even become aroused!

Judge: Is that true?

Fletcher: It has to be!

Judge: In that case I'd better take a quick break myself.
by gcanyon | 2025-09-05 16:05:17+00:00
> conservatives… claim[ing] Wikipedia has strayed from its neutrality principle by making judgments about the reliability of sources. Instead, … it should present all views equally, including things “many Republicans believe,”

That is some 1984-level “War is Peace, Freedom is Slavery, Ignorance is Strength" argument. If those “news” sources want people to stop calling them liars, they should stop lying.
by sgerenser | 2025-09-05 16:05:29+00:00
Well, apparently the market disagrees. Futures are now pointing to a 100% chance of at least a 25 basis point cut at the next meeting, and the chance of a 50 basis point cut went from 0 to 11.6%: https://www.cmegroup.com/markets/interest-rates/cme-fedwatch...
by jitl | 2025-09-05 16:05:31+00:00
Not widely used but I like Typical's approach

https://github.com/stepchowfun/typical

> Typical offers a new solution ("asymmetric" fields) to the classic problem of how to safely add or remove fields in record types without breaking compatibility. The concept of asymmetric fields also solves the dual problem of how to preserve compatibility when adding or removing cases in sum types.
by dathinab | 2025-09-05 16:05:36+00:00
There can be interesting differences, I'm not sure which of them still apply but some I ran into:

- podman having a more consistent CLI API/more parameters (but I think docker did at least partially catch up)

- user-ns container allow mounting the context instead of copying it, this means that if you somehow end up with a huge build context user-ns build can be _way_ faster then "classical" docker builds (might also apply to rootless docker, idk.). We ran into that when that one person in the team using Mac+Docker asked if we can do something about the unbearable slow docker build times (no one else on the team experienced :/)

- docker implicitly always has the docker Hub as configured as source which resolves "unqualified", this might not be true for your podman default setup so some scripts etc. which should work with both might fail (but it's easy to fix, preferable always qualify your images as there are increasingly more image hosts, in worst add docker hub in the config file).

- "podman compose" supports some less feature, this might seem like a huge issue but compose doesn't seem the best choice for deploying software and if I look how it turned out in dev setups the moment things became larger/more complicated I came to the conclusion that docker/podman compose is one of the easy to start with then get trapped in a high complexity/maintenance cost "bad" corner technologies. But I'm still looking for alternatives.

- podman sometimes missing some resource management features, but also docker sometimes does have differences in how it effectively enforces them not just between version but also with the same version between OSes, this had lead to issues before where docker-rootless kills a container and docker on Mac doesn't because on Mac it didn't notice spikes in resource usage (in that specific case).
by pizlonator | 2025-09-05 16:05:59+00:00
Yeah totally, if you're in those kinds of environments, then I agree that a GC is a bad choice of tech.

I say that even though, as you noticed in another reply, I worked on research to try to make GC suitable for exactly those environments. I had some cool demos, and a lot of ideas in FUGC come from that. But I would not recommend you use GC in those environments!

There is a way to engineer Fil-C to not rely on GC. InvisiCaps would work with isoheaps (what those embedded dudes would just call "object pools"). So, if we wanted to make a Fil-C-for-flight-software then that's what it would look like, and honestly it might even be super cool
by somewhereoutth | 2025-09-05 16:06:00+00:00
Completely not true and in fact dangerously (willfully?) misleading.

Housing is much more complicated than supply and demand - for a start houses are not fungible. Local conditions are extremely important.

A lot of high house prices is due to financial engineering - for example long mortgage periods at low interest rates. Just one of many mechanisms to make the rich richer by making the poor poorer. Any momentary affordability benefit is soaked up by higher prices, and those mortgages have to be paid off for longer with much higher total payments.

High house prices are also caused by demand elasticity - things like AirBnB, 2nd, 3rd, 4th homes for the super rich, and housing as a place to park funny money (regardless of whether the house is actually being used to home people) mean that normal people can't compete with this non-home demand.

We could go on.
by troyvit | 2025-09-05 16:06:12+00:00
Here's another chart that shows just basic tariff revenue:

https://www.politico.com/interactives/2025/trump-tariff-inco...

It shows about $100 billion in tariff revenue growth since May, '25. Interestingly your chart shows an overall growth of $232 billion in the same date range. IOW if both charts are right the slight majority of overall supply is coming from somewhere other than tariffs (though tariffs are adding a lot). I wonder where that money is coming from?
by rimunroe | 2025-09-05 16:06:25+00:00
I'm just a frontend developer so most of my exposure is just as an API consumer and not someone working on the service side of things. That said:

A few years ago I moved to a large company where protobufs were the standard way APIs were defined. When I first started working with the generated TypeScript code, I was confused as to why almost all fields on generated object types were marked as optional. I assumed it was due to the way people were choosing to define the API at first, but then I learned this was an intentional design choice on the part of protobufs.

We ended up having to write our own code to parse the responses from the "helpfully" generated TypeScript client's responses. This meant we had to also handle rejecting nonsensical responses where an actually required field wasn't present, which is exactly the sort of thing I'd want generated clients to do. I would expect having to do some transformation myself, but not to that degree. The generated client was essentially useless to us, and the protocol's looseness offered no discernible benefit over any other API format I've used.

I imagine some of my other complaints could be solved with better codegen tools, but I think fundamentally the looseness of the type system is a fatal issue for me.
by iamdelirium | 2025-09-05 16:06:26+00:00
Yeah, oneOf fields can be repeated but you can just wrap them in a message. It's not as pretty but I've never had any issues with this.

The fact that the author is arguing for making all messages required means they don't understand the reasoning for why all fields are optional. This breaks systems (there are are postmortems outlining this) then there are proto mismatches .
by HankStallone | 2025-09-05 16:06:33+00:00
I get the impression that they're just too lazy or incompetent, or in too big a hurry, to put some sensible logic in their scrapers. Maybe they have an LLM write the scraper and don't bother to ask for anything more than "Make a web scraper that gets all the files it can as fast as it can."

The last one I blocked was hitting my site 24 times/second, and a lot of them were the same CSS file over and over.
by bjt | 2025-09-05 16:06:37+00:00
In the beginning, Docker DID have "standalone mode" where it would launch just one container as a child process. That was actually an easier way to manage the mounts and cgroups necessary to stand up a container. I made a ticket to bring it back after they removed it, and it was closed with a wontfix. The cynic in me says it was done more for commercial reasons (they wanted a more full featured daemon on the server doing things they could charge for) as opposed to just being a little shim that just did one thing.
by sega_sai | 2025-09-05 16:06:51+00:00
I completely disagree. As a scientist who does a lot of coding, the modern LLM tools give me ability to code something which previously I could not afford, because I simply did not have time for it. Now if I have an idea, I may be able to test it in an hour of tinkering with claude/gemini. I could technically still code it myself, but in some cases that would require maybe a day of work -- and I simply don't have that.
by inerte | 2025-09-05 16:07:10+00:00
Most software projects don't even do A/B tests. A lot of them don't need, it's just what someone wants to ship. Another set can't even get to the sample size required.

But fine, let's take the subset of features / projects that can be tested or somehow validated. In my experience (having worked for 13+ years on companies that prefer to A/B almost everything), more than half of the tests fail. People initially might think the solution is to have better ideas, cook them more, do better analysis. That's usually wrong. I've seen PHDs with 20+ years of experience in a given industry (Search) launch experiments and they still fail.

The solution is to have some sort of "just enough" analysis like user studies, intuition, and business needs, and launch as fast and as many as you can. Therefore, development speed is A bottleneck (there's no Silver Bullet so it's not THE bottleneck).
by nfriedly | 2025-09-05 16:07:10+00:00
It's only officially rated for PCIe gen 2 speeds, but you can bump it up to gen 3 speed with a configuration flag.

I've done that for both of mine, combined with ~$15 256GB SSDs off of ebay, and I haven't had any trouble. It's noticeably faster, and probably a little more reliable than a microSD.
by Aurornis | 2025-09-05 16:07:19+00:00
I think the mistake is the trend of trying to treat it like a mini computer. If you buy a Pi, stick an old SD card in it, plug it into an old USB charger you have lying around, and connect it to the network it's great for people learning how to use Linux, command line, and SSH.

You can connect things to the headers and experiment with it as originally intended.

In my opinion, it doesn't make sense to try to treat it like a mini desktop computer. Like you said, it's very expensive to add on all of the accessories: High power adapter, M.2 hat, SSD, special HDMI cables, and a case for cooling. By the time you're done, you've spent as much as a cheap x86 computer that would outperform it and come with none of the software quirks.

Just because you can outfit it will all of those things doesn't mean most people should. If you really want a mini computer, get a mini computer.
by flail | 2025-09-05 16:07:24+00:00
I wouldn't discuss with that part, although there are definitely limits to how big a chunk of a big product a single brain can really grasp technically. And when the number of people involved in "grasping" grows, so does the coordination/communication tax. I digress, though.

We could go with that perception, however, only if we assume that whatever is in the backlog is actually the right thing to build. If we knew that every feature has value to the customers and (even better) they are sorted from the most valuable to the least valuable one.

In reality, many features have negative value, i.e., they hurt performance, customer satisfaction, any key metric a company employs.

The big question: can we check some of these before we actually develop a fully-fledged feature? The answer, very often, is positive. And if we follow up with an inquiry about how to validate such ideas without development, we will find a way more often than not.

Teresa Torres' Continuous Discovery Habits is an entire book about that :)

One of her recurring patterns is the Opportunity Solution Tree, which is a way of navigating across all the possible experiments to focus on the right ones (and ignore, i.e., not develop, all the rest).
by perihelions | 2025-09-05 16:07:26+00:00
> "One of the agents can be heard telling workers they had a search warrant for the entire site and asked that construction “be ceased immediately.”"

It's a $7.6 billion factory that produces exclusively electric vehicles, employs "1,400+" (ultimately 8,500 [b]) and is claimed as the "largest economic project in Georgia history". By way of background—here's the wiki,

[a] https://en.wikipedia.org/wiki/Hyundai_Motor_Group_Metaplant_...

And (lots) more background from IEEE Spectrum (someone had recently posted to HN),

[b] https://spectrum.ieee.org/hyundai-metaplant-georgia ("Hyundai’s Metaplant Seeks Hard-Working Robots")
by OutOfHere | 2025-09-05 16:07:59+00:00
I have an appropriate stool, and have used and compared it over a lengthy period. The subjective benefit over time is not 90%; it is about 30%. When squatting, there is no risk of falling if one has normal balance and is not unwell. It is not for the inattentive person. It takes weeks or months of use to realize its pelvic benefits.

The risk of falling is highest when getting off the seat, at which time it helps to have a support to hold.

The correct solution would of course be to remove this toilet altogether, replacing it with a squat toilet.

The noted actions are not something that anyone will typically do until they feel they're out of options, but then it's a potential option.
by sfn42 | 2025-09-05 16:09:14+00:00
The mistake was not answering the question. There would have been nothing wrong with expanding your answer with notes about how you might avoid having a million items in an array in the first place, but the question was how do you sort it when you have it and you should answer the question you're asked before answering questions nobody asked.

It has nothing to do with language of engineering, and everything to do with him not answering the simple question he was asked. And then he goes on to complain that interviewers value complexity right after the story about how he fumbled a simple question by overcomplicating his answer to the point that it didn't even answer the given question at all.
by nimbius | 2025-09-05 16:09:19+00:00
The bart is basically the crowning achievement of US public transit. As for the solutions coming from everyone's favourite bay Aryan Elon Musk, they are...somewhat lacking.

You're probably not going to believe this but the Hyperloop in Las Vegas:

- is now just "the loop."

- only has 8 stops

- doesnt go to the airport

- most stations are unprotected park benches in the desert sun

- vehicles arent driverless

- speeds are 26 miles per hour instead of 155

- it can take up to 20 minutes for a ride to show up

- it does not go to or from the airport.

- it only runs for 11 hours a day at some stations.

- cost taxpayers fifty-three million dollars.
by ants_everywhere | 2025-09-05 16:10:04+00:00
> Maintain a separate type that describes the data you actually want, and ensure that the two evolve simultaneously.

I don't actually want to do this, because then you have N + 1 implementations of each data type, where N = number of programming languages touching the data, and + 1 for the proto implementation.

What I personally want to do is use a language-agnostic IDL to describe the types that my programs use. Within Google you can even do things like just store them in the database.

The practical alternative is to use JSON everywhere, possibly with some additional tooling to generate code from a JSON schema. JSON is IMO not as nice to work with. The fact that it's also slower probably doesn't matter to most codebases.
by xg15 | 2025-09-05 16:10:31+00:00
If both claims are true - unemployment rate is only 0.3% above the target AND unemployment rate is the highest in 4 years - then the only logical conclusions can be that either the unemployment rate has been exceptionally stable in the last years (or there was too little unemployment?), or 0.3% is in fact a significant deviation despite the number appearing small.
by zacfire | 2025-09-05 16:10:33+00:00
This is an analysis of a rare, in-depth interview with Yang Zhilin, the founder of China's Moonshot AI (Kimi). The piece focuses on his unconventional, philosophical approach to building an AGI company amidst intense market competition.

One of the most interesting takeaways is his management philosophy, where he explicitly states he tries to run his organization using principles from Reinforcement Learning (defining rewards and letting the team explore) rather than Supervised Fine-Tuning (giving direct, rigid instructions). He sees it as a way to foster innovation under pressure.

The article translates key excerpts and contrasts his long-term, philosophical vision with the company's short-term market challenges (stalled growth, price wars). Curious to hear the HN community's thoughts on applying RL concepts to team management and the viability of such a long-term vision in a hyper-competitive environment.
by bbkane | 2025-09-05 16:10:46+00:00
I see your point but I wouldn't let the perfect be the enemy of the good.

If I just want to run a random Docker container, I'm grateful I can get at least "some security" without paying as much in setup/debugging/performance.

Of course, ideally I wouldn't have to choose and the thing that runs the container would be able to run it perfectly securely without me having to know that. But I appreciate any movement in that direction, even if it's not perfect.
by jcranmer | 2025-09-05 16:11:03+00:00
> Just because it uses the same rail gauge as intercity freight doesn't require it to run on the same set of tracks.

We're talking about BART, which uses a track gauge of 5'6" instead of the standard US rail gauge of 4'8.5". They can't run on the same tracks.

(Actually, this is generally true even for those systems that do use 4'8.5" gauge track--I suspect that the standard US freight car envelope doesn't actually fit on most subway systems.)