MurphyA/hacker-news huggingface dataset:
by 827a | 2025-08-01 23:58:45+00:00
I wonder if the next phase for leveraging LLMs against large sets of contextual, proprietary data (code repositories & knowledge bases come to mind) is going to look more like smaller models highly (and regularly) trained/fine-tuned against that proprietary data (that is maybe delegated tasks by the ultra-sized internet scale omni-brain models)

If I'm asking Sonnet to agentically make this signin button green: does it really matter that it can also write haikus about the japanese landscape? That links back to your point: We don't have a grip, nearly at all, on how much this crosstalk between problem domains matters. Maybe it actually does matter? But certainly most of it doesn't. B

We're so far from the endgame on these technologies. A part of me really feels like we're wasting too much effort and money on training ASI ultra internet scale models. I'm never going to pay $200+/mo for even a much smarter Claude; what I need is a system that knows my company's code like the back of its hand, knows my company's patterns, technologies, and even business (Jira boards, Google docs, etc), and extrapolates from that. That would be worth thousands a month; but what I'm describing isn't going to be solved by a 195 IQ gigabrain, and it also doesn't feel like we're going to get there with context engineering.
by jazzyjackson | 2025-08-01 23:58:47+00:00
the usage of vibe coding in my experience is towards those folks who run whatever the AI produced and if it does what they expect without throwing errors they ship it. If it throws errors they plug that back into the chatbot until the code stops throwing errors.

The whole point of vibe coding is its working faster than you would on your own. If you're reviewing it carefully and understand how it works, you might as well have written it by hand.
by whockey | 2025-08-01 23:58:51+00:00
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Previous to this I started Plaid (plaid.com), and at Column I'm focused on keeping an extremely lean and experienced team. We're currently 10 experienced engineers that all report to me. We are looking for an ambitious infrastructure, product, and backend engineer (one of each) that wants to build incredible software from first principles.

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Show HN: Voice-First AI Code Review Workspace
by musbemus | 2025-08-01 23:59:18+00:00
Hey HN. We're Mus and Isaac - creators of LightLayer.

We've been outputting a ton more code since using agentic dev tools. It's been great. But we're starting to see a new bottleneck emerge that's no longer writing the actual code: reviewing code.

We’d love to hear from folks here if they’re feeling the inertia of code reviews a lot more these days with the surge in development velocity. For us, it was the reason we decided to pivot what we were working on before, and go full-time on building a workspace aimed at bringing the code review experience up to speed for the AI era.

To be clear: we’re not an auto-commenting PR bot (e.g. CodeRabbit, Greptile, Graphite, etc.). We think those tools are helpful, and can give a solid first-pass at issues for the author to iterate on. But we think human-in-the-loop reviews are here to stay and so we’ve gone with the approach of focussing on empowering reviewers with a consolidated workspace that delivers the context and sounding board they need to review quicker without sacrificing understanding or quality.

We basically brought all of the relevant parts of Github - discussions, file tree nav, diffs, timeline events, etc. into one view that both you and our agent - Lux - can see and work off of in real-time; kind of like a live review session with a senior team member (we actually got inspo from how much quicker reviews went for us in our jobs when we did pull ppl in to do live review sessions). We designed the UI around voice for this reason - to emulate that experience.

Anways, I’ll stop yapping and let y’all try it out - just sign in, and paste in any public URL to any Github PR. Highlight code or click on comments you want Lux to pay attention to and just speak naturally. Right now, Lux will point you to relevant places in the code, explain things, and draft comment copy for you.

This is all definitely still a WIP: Lux still doesn’t have complete context of the entire codebase and there’s some bugs we’re working through wrt conversation flow (please use bug nub if any arise). And there are a ton of other features we’d want to include eventually (MCPs for Slack, Linear, etc., comments in your learned tone) But it’s enough to showcase the experience we’re targetting and hopefully still create some value for those looking for more of a delightful code review experience.

That said, would super appreciate any feedback.

Github (for issues): https://github.com/lightlayer-dev/community Demo: https://app.lightlayer.dev/ Website: https://www.lightlayer.dev/

Happy coding!

P.s we posted here last week pre-launch without reading through the 'rules' for Show HN - sorry!
by tzs | 2025-08-01 23:59:53+00:00
> Also, how the heck is Mr. McGee supposed to come up with the other 67% of this judgment?

He probably can't. Assuming the amount stands on appeal, and assuming that he doesn't have an insurance policy with policy limits high enough to cover it, he'll pay as much as he can out of personal assets and probably have his wages garnished.

He might also be able to declare bankruptcy to get out of some or all of it.

An interesting question is what the plaintiffs can do if they just cannot get anywhere near the amount owed from him.

A handful of states have "joint and several liability" for most torts. If this had been in one of those states the way damages work when there are multiple defendants is:

• Each defendant is fully responsible for all damages

• The plaintiff can not collect more than the total damage award

In such a state the plaintiffs could simply ask Tesla for the entire $329 million and Tesla would have to pay. Tesla would then have a claim for $220 million against McGee.

Of course McGee probably can't come up with that, so McGee still ends up in bankruptcy, but instead of plaintiffs being shortchanged by $220 million it would be Tesla getting shortchanged.

The idea behind joint and several liability is that in situations like there where someone has to be screwed it shouldn't be the innocent plaintiff.

Many other states have "modified joint and several liability". In those states rather than each defendant being fully responsible, only defendants whose share of the fault exceeds some threshold (often 50%) are fully responsible.

For example suppose there are three plaintiffs whose fault shares are 60%, 30%, and 10%. In a pure joint and several liability state plaintiff could collect from whichever are most able to come up with the money. If that's the 10% one they could demand 100% from them and leave it to that defendant to try to get reimbursed from the others.

In a modified joint and several liability state with a 50% threshold the most the plaintiff can ask from the 30% and 10% defendants is 30% and 10% respectively. They could ask the 60% defendant for 100% instead. If the 60% defendant is the deep pockets defendant that works out fine for the plaintiff, but if it is the 10% one and the other two are poor then the plaintiff is the one that gets screwed.

Finally there are some states that have gotten rid of joint and several liability, including Florida in 2006. In those states plaintiff can only collect from each defendant bases on their share of fault. Tesla pays their 33%, McGee pays whatever tiny amount he can, and the plaintiff is screwed.
by makeitdouble | 2025-08-02 00:00:05+00:00
It works in most trivial cases, so I'm assuming it's widely done irl.

Imagine building some small app that reads external config file. You personally only care about yaml files, but your avid users ask for official json support as well because of a few of their files.

It's not high priority, but as you remember the old saying, json is just a subset, so you try a bunch of files, confirm it works well enough, and decide to pipe JSON files to your yaml parser as well. Done and done.

And it's not so big block of code or anything that jumps at the users, the dev just happens to share a parser between formats.
by zabzonk | 2025-08-02 00:00:13+00:00
I flew in a Comet 4 from Athens to Nicosia in Cyprus a couple of times when I was a kid, back in the 1960s. I must admit it felt to me a bit like getting into a Victorian railway carriage after getting off the then very modern Trident from Heathrow to Athens, but that may have been down to Olympic Airways.
by zahlman | 2025-08-02 00:00:35+00:00
Another technique I've seen is to hide or overwrite the name of the class, such that client code only knows about the instance (and is expected to use it directly rather than doing any kind of access or instantiation). Of course, this doesn't give you lazy initialization unless you lazily import the module, at which point you would definitely be better off just using the module object directly.

There's also code out there which replaces the cached module object with a class instance in top-level code! This is especially used to work around the prior lack of module-level `__getattr__` (and `__dir__`), added in 3.7 (https://peps.python.org/pep-0562/). But you might still need it if for some reason you want to hook into the lower-level `__getattribute__`. And Andrew Moffat's `sh` package still does this (https://github.com/amoffat/sh/blob/develop/sh.py#L3635) even though it now only declares support for 3.8 and above. (Perhaps there was simply no clear reason to change it.)
by dizlexic | 2025-08-02 00:01:13+00:00
I'm guessing you only started to pay attention to the right in 2014.

Everything really changed with the bailouts then the tea party movement. The republicans went from big business, lower taxes, exclusively to populism.

The dems are going through a similar bend currently and probably would have happened sooner if they hadn't undermined their voters nomination of Bernie in 2015.

The republicans (love um or hate them) didn't change the rules to scuttle Trump. One party is listening to their base the other is trying to control them (and imo is imploding because of it). I'm honestly a bit of a neo con so there isn't a place for me in a populist republican party. I'll just keep throwing votes at Chase Oliver / similar outsiders until we have a return to sanity.
by reactordev | 2025-08-02 00:02:13+00:00
Yes, because just 4 years later, everyone was high. It was the precursor to the green rush. Denver weathered the storm because we had an economic tsunami on our hands and it was going to come crashing at the ballot box. Well, it broke through. There was a huge influx of people from more expensive metros coming to Denver at that time. Then the housing went through the roof. Statistically it happened everywhere but I was in Denver trying to buy and being outbid by people with cash buying their 4th home.
by Leftium | 2025-08-02 00:04:06+00:00
Best Realtime Sync Engine (2024): https://robotist.com/realtime-sync-engine

Theo Browne (T3) detailed the different methods he used to sync user data for https://t3.chat: https://youtu.be/3gVBjTMS8FE

He looked into several solutions like https://zero.rocicorp.dev, but decided to roll his own.

He finally decided to let Convex handle sync for him:

- https://youtu.be/xFVh9beupwo

- https://youtu.be/gZ4Tdwz1L7k
by gsf_emergency_2 | 2025-08-02 00:04:19+00:00
"raw data" is from EIA (a veritable rabbit hole!)

>EIA publishes hourly operational data across the United States electricity grid, including demand, net generation of electricity from various sources (such as coal, natural gas, solar), CO2 emissions, import/export to other regions, and many more. The complete details of the EIA-930 data is available here: https://www.eia.gov/electricity/gridmonitor/about. Furthermore, we obtained the solar capacities of each year and each region from EIA (https://www.eia.gov/electricity/data/state/) and had stored the information in the file solar_capacity_factor.csv. (2023-07-01)
by no_wizard | 2025-08-02 00:05:16+00:00
Neat project, and I think erlang (or its offshoots, like elixir) are great candidates for this sort of thing.

That said, I take issue with this:

>is great for creating data flows that actually describe concurrent processing, it is just a shame the NodeJS is single threaded

Its not really true, there are `worker_threads`[0] as well as a cluster process module[1] for multi processing.

The nodejs runtime has really come a long way here. Though, it is true that by default, its single threaded, and one could argue, and I'd agree with it, that its much easier to do multi process / multi threaded work on the BEAM since it was built with this in mind from the get go.

Never the less, its not so true that NodeJS is limited to a single thread!

[0]: https://nodejs.org/api/worker_threads.html

[1]: https://nodejs.org/api/cluster.html
by brendoelfrendo | 2025-08-02 00:05:20+00:00
It's not hard to understand, but I think there's a compelling argument to be made that the "daily AND weekly" limits is surely user hostile and differing limits across different pricing tiers can make it harder to tell at a glance what you actually need. It's not that Cerebrus has a feature worth advertising, it's that everyone else has introduced an anti-feature that has become the norm.
by zahlman | 2025-08-02 00:05:53+00:00
> Ad infinitum

The result of module import is cached (which is also what makes it valid to use a module as a singleton); you do not pay this price repeatedly. Imports can also be deferred; `import` is an ordinary statement in Python which takes effect at runtime rather than compile time.

Modules that are slow to import are usually slow because of speculatively importing a large tree of sub-modules. Otherwise it's because there's actual work being done in the top-level code, which is generally unavoidable.

(Requests is "only" around a .1s import on my 11-year-old hardware. But yes, that is still pretty big; several times as long as the Python interpreter plus the default modules imported automatically at startup.)
by kmeisthax | 2025-08-02 00:06:49+00:00
> Oddly, maybe even with less effort than shutting it down would take.

Google has a number of internal processes that effectively make it impossible to run legacy code without an engineering team just to integrate breaking upstream API changes, of which there are many. Imagine Google as an OS, and every few years you need to upgrade from, say, Google 8 to Google 9, and there's zero API or ABI stability so you have to rewrite every app built on Google. Everyone is on an upgrade treadmill. And you can't decide not to get on that treadmill either because everything built at Google is expected to launch at scale on Google's shitty[0]-ass infrastructure.

[0] In the same sense that Intel's EDA tools were absolutely fantastic when they made them and are holding the company back now
by BoorishBears | 2025-08-02 00:08:27+00:00
I've done a lot of post training and data collection for post-training

I think if you're not OpenAI/Anthropic sized (in which case you can do better) you're not going to get much value out of it

It's hard to usefully post-train on wildly varied inputs, and post-training is all most people can afford.

There's too much noise to improve things unless you do a bunch of cleaning and filtering that's also somewhat expensive.

If you constrain the task (for example, use past generations from your own product) you get much further along though.

I've thought about building a Chrome plugin to do something useful for ChatGPT web users doing a task relevant to what my product does, then letting them opt into sharing their logs.

That's probably a bit more tenable for most users since they're getting value, and if your extension can do something like produce prompts for ChatGPT, you'll get data that actually overlaps with what you're doing.
by decimalenough | 2025-08-02 00:09:03+00:00
I saw the title, got ready to post about my own criminal monkey misadventures, and realized it's the same place (Uluwatu Temple). However, the story underplays an important element: it's actually a triangular syndicate of crime, and humans are very much part of the picture.

First, the monkey steals something of value from a tourist and (the missing bit) they run inside the temple buildings, which are off-limits to tourists.

Second, a friendly temple priest or caretaker (the mentioned "monkey handlers"), who is allowed inside, fences the loot by exchanging it for something a monkey values, like a tasty banana.

Third, the relieved tourist gets their belongings back and generously tips the caretaker.
by JonChesterfield | 2025-08-02 00:09:38+00:00
Doubtful. JSON has javascript semantics all over it. TOML I've had to look up and seems vaguely fine as such things go, but doesn't have schemas.

XML grows on you. XSL transforms are _probably_ not a good idea but they also kind of grow on you. It turns into html rather easily as well.
by sabakhoj | 2025-08-02 00:10:01+00:00
> The central finding is that a 15% increase in solar generation across the U.S. is associated with an annual reduction of 8.54 million metric tons (MMT) of CO2, a significant step toward national climate goals.

Whoa, that's really cool.

You can see the paper along with figures & regional breakdowns here: https://openpaper.ai/paper/share/1d0c6956-4820-4ee2-ac1e-12c...
by quickthrowman | 2025-08-02 00:11:09+00:00
To add, grid-scale batteries do make sense if you have a ton of cheap land. Most facilities that need backup power aren’t in areas with lots of cheap available land for battery installations.

The kind of backup power needs that hospitals, data centers, and other critical facilities have (multiple MWH per hour at minimum for large facilities) and the durations they need to operate for, combined with the land prices in the areas where they are situated, make battery backup for critical power needs uneconomical due to the space needed with current battery energy density.
by mekoka | 2025-08-02 00:11:44+00:00
If the language is limited to only single and shallow inheritance, then super() becomes a syntactic convenience that saves everyone the burden of spelling out the inheriting class. But in Python, even if your code emulates these constraints, you lose in clarity from using super() because someone reading your source has to wonder if or why it was specifically needed, since its main purpose is to resolve the kinds of conflicts that arise in complex inheritance scenarios (diamond, problematic cycles, and such). So, to need it is to make your code complicated. To not need it while using it, is to lose in clarity.
by zahlman | 2025-08-02 00:11:47+00:00
Python test frameworks generally do mocking by monkey-patching, and they take care of it for you. This does not generally require global state, either in the form of module-level variables or singletons. It works by doing things like replacing the attributes of an existing class or module object. (Python takes "everything is an object" seriously, so a module is an object whose attributes are the functions, classes and other global variables of the corresponding file's code, roughly speaking. It is not simply reflected as such through a reflection API, like in Java; it is directly represented with an object. This is the sort of benefit dynamic typing gets you, along with the object-qua-dictionary-of-attributes model.)
by hackernudes | 2025-08-02 00:13:11+00:00
Google is famously a monorepo and is basically the gold standard of CI/CD.

What does happen is APIs are constantly upgraded and rewritten and deprecated. Eventually projects using the deprecated APIs need to be upgraded or dropped. I don't really understand why developers LOVE to deprecate shit that has users but it's a fact of life.

Second hand info about Google only so take it with a grain of salt.
by StellarScience | 2025-08-02 00:14:07+00:00
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Technologies: Mostly C++23, Qt 6.9, CMake, git, OpenGL, CUDA, Boost, Jenkins. Windows and Linux, msvc/gcc/clang/clangcl. AI/ML and other projects use Python, some use Java or Javascript/Typescript/React.

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by zahlman | 2025-08-02 00:14:24+00:00
When I first heard the term "dependency injection", I spent quite a bit of time trying to understand it. And then when I was pretty sure I had grasped it, I felt even more confused. "Isn't that just... passing an argument to a function instead of having the function access the information from global state? ... Isn't that normally what the function should do?"
by quantified | 2025-08-02 00:14:47+00:00
Are we seeing the explosion of jobs created by AI? When it reduces the costs of doing X for everyone, for values of X that involve some aspects of cognition, it may make some things more convenient. But what does it enable that you'd pay money to someone else for as opposed to just do it yourself? My AI-enhanced human travel agent would be competing with my AI travel agent, but my AI travel agent will be cheaper.
by bravesoul2 | 2025-08-02 00:15:08+00:00
I don't know. I might do that depending on $country. Person A's idiotic comment shouldn't punish the actual parent. So I would only call police if it is helpful. I have called police when I found a kid before. while I was in the phone I found the parents so said all good. I think the cop was relieved! But this is not in the US.
by coderatlarge | 2025-08-02 00:15:44+00:00
fair point - yes this is a biochemistry lab but her part is specifically to do with analysis of lab data collected from someone’s specific experiment. so she’s learning practical things having to do with actually doing new science in a real environment though she’ll need to generalize a bit in her mind (hopefully correctly but then developing intuition and imagination matters too) to the pure chemistry aspect of it. she’s generally excited to meet actual professionals in their day-to-day work who have specific performance expectations of her and who really care that her part is done correctly and can be thoroughly audited and verified for accuracy. this time she’s not getting her hands on actual lab instruments and things like that (she does that at school and hopefully in next summer’s internship if she can can get one and is still interested by then); but she’s seeing how data comes from each of those physical world manipulations and what is done with it afterwards.