MurphyA/hacker-news huggingface dataset:
by nyrikki | 2025-09-22 19:05:32+00:00
Trying to be helpful here, sorry if it doesn’t map to your field of which I am not familiar.

The _algebra_ you learn in school is elementary algebra, using variables.

In modern math, _algebra_ or _modern_ algebra or _abstract_algebra, is the study of structures over sets with defined operations on the elements of that set.

ADTs are an example of an algebraic structure, specifically called one that converts non-trivial semantic (runtime) properties to trivial ones (T/F).

This post is dealing with the structure in another way.

If you understand magmas, monoids, etc.. that can be helpful.

But the lay description I find useful is the algebra is what _arises_ from that defined set domain and operations.

The key point is studying the structure, which is the algebraic structure, or the algebra. It is basically what pops out, not what you start with, although that is flawed.

Almost all modern math will use that _modern_ meaning of algebra.
by Mistletoe | 2025-09-22 19:05:39+00:00
I think they all know where it is heading and it is massively less money for everyone. Every technical breakthrough doesn't mean more profit for everyone and nor should it. Sometimes it's just a dishwasher or washing machine, something that frees up the bulk of humanity from something that is drudgery. Whether we actually get those benefits from AI remains to be seen.
by mrandish | 2025-09-22 19:05:47+00:00
> Tends not to end well.

I'm no financial guru but this time around the boom/bust cycle, there's a new, additional factor that's concerning. Even though I sold my individual tech company shares a few years ago and diversified all my equity holdings in broad market ETFs like VTI, the so-called "Magnificent 7" tech companies have inflated so much, they now occupy a disproportionate percentage of even broad market ETFs which hold ~5,000 stocks based on their market caps. The obvious issue being their share prices all having a significant component elevated by the same thing - unrealistic AI growth expectations.
by Imustaskforhelp | 2025-09-22 19:06:16+00:00
That quote definitely has some insane survivor bias in it.

Optimists go bankrupt or something and you blame them on their work ethic or something and you discard any of those optimists who didn't really succeed and cherry pick those optimists which went right...

Its a classic survivorship bias.

I am pessimistic in US stocks because they are so concentrated on AI for returns and its definitely a bubble or approaches its territory, there is somewhat no denying about it from what I observe.

Your comment really is just off putting to me because I feel like its just a copium which is going to be inhaled by the new generation and then if we fail which lets be honest failure is a natural part of life, we are gonna blame ourselves and that's just really depressing.

I'd better be right than rich. Maybe my rich definition is something that I can get out of hard work while maybe being pessimist (just enough money to have freedom lol)

I don't want to make billions or hundreds of millions, i don't want to build a vc funded disaster for humanity in the name of shareholders whether its an Ad dystopia or an AI nightmare fuel, I'd rather make a imprint on humanity other than my bank account number but maybe that's me being "optimistic"

Sorry but your comment truly ragebaited me... I have very strong opinions in this regards.
by OptionOfT | 2025-09-22 19:06:33+00:00
> He thinks it is unrealistic to expect lawyers to stop using AI.

I disagree. It worked until now, and using AI is clearly doing more harm than good, especially in situations where you hire an expert to help you.

Remember, a lawyer is someone who actually has passed a bar exam, and with that there is an understanding that whatever they sign, they validate as correct. The fact that they used AI here actually isn't the worst. The fact that they blindly signed it afterwards is a sign that they are unfit to be a lawyer.

We can make the argument that this might be pushed from upper management, but remember, the license is personal. So it's not that they can hide behind such a mandate.

It's the same discussions I'm having with colleagues about using AI to generate code, or to review code. At a certain moment there is pressure to go faster, and stuff gets committed without a human touching it.

Until that software ends up on your glucose pump, or the system used to radiate your brain tumor.
by lacy_tinpot | 2025-09-22 19:06:34+00:00
This is more like reinvesting into the business as it's growing. It's a positive sum loop.

Nvidia makes money by selling to OpenAI. OpenAI makes money by selling a service to users that uses Nvidia. So Nvidia invests in the build out and expansion of the infrastructure that will use Nvidia.

This is a classic positive sum loop.

It's not that different than a company reinvesting revenue in growing the company.
by dcchambers | 2025-09-22 19:07:10+00:00
I feel like we're lucky Nvidia even sells consumer GPUs any more. At this point it's just a distraction to them and takes away resources they could be devoting to higher value hardware.

And the data center-class hardware doesn't do well in a home environment. It's not good for gaming. It runs hot and uses a ton of energy. Not to mention, silicon that is running hot 24/7 for years probably isn't the best thing to own second hand.
by hangonhn | 2025-09-22 19:07:15+00:00
I'm a little surprised by the answers in "Cryptographic Right Answers". Both libsodium and Chacha20-Poly1305 are not FIPS-compliant. "AES-GCM" is but it has important gotchas in regards to the IV and per key data volume. "AES-GCM-SIV" is more resilient but "AES-GCM-SIV" isn't FIPS compliant either but there is a proposal underway to certify it. So the cryptographic right answer is "it depends". FIPS compliance may not matter to some people but it does a lot to others depending on the context.

I think the safe answer is AES-GCM using envelope encryption?
by amoshebb | 2025-09-22 19:07:26+00:00
His website makes him look like the owner of a law firm, although I think it's just him? I'm not expecting the same number, but... california issues bigger fines for watering lawns or buying illegal fireworks. For a lawyer, a fine order of magnitude smaller than "hiring a paralegal" is less "historic" and more "cost of doing business, don't get caught"
by raincole | 2025-09-22 19:07:59+00:00
First of all, it's not 'textbook round tripping' at all. The parent commenter is dead wrong but HNers upvote when they see "AI is a bubble."

Textbook round tripping is like: OpenAI buys GPUs from Nvidia. And the only reason it buys these GPUs is to resell it back to Nvidia, or just do nothing. It doesn't make it round tripping just because OpenAI is taking investment and buying stuff from Nvidia at the same time.

Unless you really believe OpenAI has no intention to use these GPUs for other purposes (like training GPT-6. I know, a crazy idea: OpenAI will train and release a model), it's not round tripping.
by burnte | 2025-09-22 19:08:06+00:00
It's the same thing with tiny tax cuts. No business person is saying, "I'd love to hire 30 more people to fulfil customer orders, but I need a 2% reduction in my top marginal income tax rate to be able to afford that!" No one pays wages out of their post-tax personal income. Either you have the incoming business to support hiring more people or you don't. If you do, then those wages and employee taxes go in your "costs" column and is a legit business expense you wouldn't pay taxes on.

Yes a tax environment can be oppressive and make hiring unattractive, but that's not what is relevant to those "cut taxes and I'll hire more people" debates. It's pure nonsense. A drop from 42% to 40% top marginal tax rate is not going to kick off a hiring boom.
by hu3 | 2025-09-22 19:08:15+00:00
If you are starting your career and panic reading such list, that would take years to learn, if even. Don't worry.

Most of these items are more like nice to know than should know.

Yeah it would be great if every software developer knew everything. But I doubt even the repository owner know all that is listed.

My best advice to newcomers is get your hands dirty and stay away from endless hours of courses, YouTube videos and "awesome lists".
by Existenceispain | 2025-09-22 19:08:21+00:00
The refusal of doctors to prescribe antibiotics is mind boggling. I had an issue for 7 years that finally resolved from some generic antibiotics. Tons of suffering.

Yet hundreds of tons of antibiotics are just given to animals/livestock like candy.

At one point I was considering buying fish antibiotics because you can buy that by the pound at the pet food store.
by sunrunner | 2025-09-22 19:08:35+00:00
> Especially since representing a dict already has 2 ways,

And lists.

> Pythonic

Pythonic in the way that Python's 'There should be one...' is expressed through the existence of tuples, named tuples, dataclasses, regular classes and attrs (not part of the standard library but it seems to be as much of a goto as requests is)? ;)
by JKCalhoun | 2025-09-22 19:08:41+00:00
I've begun a "Choose Your Own Adventure" story that's more a philosophical argument (or art?). There are a lot of paths through the story but they all converge to the same ending.

It's something I have believed and have especially reflected on when my mother died a couple years ago. I have wondered for some time whether she could have been happier had "x" happened instead of "y".

She had such a bad childhood that I contemplated what it would be like to clone her and raised her as my daughter. How different might her life be if she had a healthy, happy family.

But I keep coming to the conclusion that she was an inherently unhappy person and, that while plenty of life-events may have made things worse for her, in the end I think perhaps she was "fated" to be unhappy after all.

So the idea was a "Choose your own adventure" where you more or less end up in the same place regardless. Maybe a bit wealthier, maybe with 2 instead of 3 kids — but the fundamentals were already "cast".

(And anyway, upon further reflection I came to see how much my oldest daughter is more or less my mom. We raised her as best we can and yet shades of my mom's "genetics" are clearly there.)
by donatj | 2025-09-22 19:09:02+00:00
My friends job of late has basically become reviewing AI-generated slop his non-technical boss is generating that mostly seems to work and proving why it's not production-ready.

Last week he was telling me about a PR he'd received. It should have been a simple additional CRUD endpoint, but instead it was a 2,000+ loc rats nest adding hooks that manually manipulated their cache system to make it appear to be working without actually working.

He spent most of his day explaining why this shouldn't be merged.

More and more I think Brandolini's law applies directly to AI-generated code

> The amount of [mental] energy needed to refute ~bullshit~ [AI slop] is an order of magnitude bigger than that needed to produce it.
by cubefox | 2025-09-22 19:09:10+00:00
To the people who are calling this evidence of a bubble: There is no credible indication that AI in general is a bubble, even if not all investments will make sense in retrospect. Quite the opposite, the progress in the field over the last few years is staggering. AI systems are becoming superhuman at more and more tasks. It's only a question of time till AI will outperform us at everything.
by ngrilly | 2025-09-22 19:09:41+00:00
I'm familiar with zod.infer but I'm not sure how to use it to produce an interface that would be compatible with RpcStub and RpcTarget, like MyApi in the example in your post:

// Shared interface declaration: interface MyApi { hello(name: string): Promise<string>; } // On the client: let api: RpcStub<MyApi> = newWebSocketRpcSession("wss://example.com/api"); // On the server: class MyApiServer extends RpcTarget implements MyApi { hello(name) { return `Hello, ${name}!` } }
by binarymax | 2025-09-22 19:09:46+00:00
But is OpenAI recouping this? I remember seeing reports a year ago that it was in the realm of $700M/mo in inference costs for them - are they earning that now?

Of course the strategy of taking a loss and reinvesting - but I don't see how OpenAI is making enough money to pay for all this, now or in the future.
by maxenglander | 2025-09-22 19:10:10+00:00
People can disagree with the claims of course, but I don't think they are baseless.

On the Postgres side: https://planetscale.com/blog/benchmarking-postgres

On the Vitess side, I would point to our customers, who, on individual databases, have achieved pretty high QPS (millions), on large datasets (100s of TiBs), at a latency that is lower than what other DBaaS providers can offer: https://planetscale.com/case-studies/cash-app
by ChrisMarshallNY | 2025-09-22 19:10:11+00:00
I agree with the article, but I'll bet a lot of others, don't. Discussions on Code Quality, don't fare well, here. Wouldn't surprise me, if the article already has flags.

Of course, "testing," is in the eye of the beholder.

Some folks are completely into TDD, and insist that you need to have 100% code coverage tests, before writing one line of application code, and some folks think that 100% code coverage unit tests, means that the system is fully tested.

I've learned that it's a bit more nuanced than this[0].

[0] https://littlegreenviper.com/testing-harness-vs-unit/
by TMWNN | 2025-09-22 19:10:48+00:00
In 1977, the Apple II was the only personal computer in the world on which this sort of game—color, animation, sound—was possible. Not TRS-80, not Commodore PET.

Put another way, from 1977 to 1979 (when the Atari 8-bit appeared), the Apple II was the world's best video game machine.
by lcnPylGDnU4H9OF | 2025-09-22 19:11:00+00:00
> This isn't a matter of meeting peoples needs

Curious how you reach this conclusion from the point that they do it for money?

> They want money

> It's just a job to them.

That's pretty much exactly how most people meet their needs: do a job for money. That they are stealing things other than what is directly needed is a distraction from the point that they are stealing to meet their needs.
by aerostable_slug | 2025-09-22 19:11:06+00:00
Also revenue loss due to fewer impulse purchases. You could still have candy bars in the line to get to the counter, but it's not the same thing as merchandising in aisles and on end caps.

With robots doing the picking and packing the employee problem becomes reduced, but it might take some serious innovation to reliably get customers to leave with more products than they went to the store to buy.
by paganel | 2025-09-22 19:11:30+00:00
> debt is highly explosive (see GE during the GFC) whereas equity is not.

Not as explosive as debt but I'd venture to say that nowadays equity is a lot more "inflamable" compared to 2008-2010, as in a lot more debt-like (which I think partly explains the current equity bubble in the US).

As in, there are lots and lots of investment funds/pension funds/other such like financial entities which are very heavily tied to the "performance" of equity, and I'm talking about trillions (at this point) of dollars, and if that equity were to get a, let's say, 20 or 30% hair-cut in a matter of two-three months (at most), then we'll for sure be back in October 2008 mode.
by clearleaf | 2025-09-22 19:11:39+00:00
There's a phenomenon of fraudulent "security researchers" which has sprung out of the AI world. I became aware of it when someone on discord posted a video covering an "ACE exploit" against users of a particular AI coding assistant. The exploit was this: 1. You accidentally grab a malicious config file for the assistant 2. For some reason, you would pipe this entire file into curl and then into bash 3. This results in downloading and running a script that sets up malware.

It didn't make sense at any point but I was gripped by a need to know the intention such a worthless video. It made sense when the host started shilling his online course about how to be a "security researcher" like him. Not only that, paying members get premium first access to the latest "disclosures" that professional engineers are afraid to admit exist. It's likely that the creator of this bug report is building up their own repertoire of exploits that have been ignored. Or perhaps they're trying to put their course knowledge to use.
by vunderba | 2025-09-22 19:12:36+00:00
Nice job. I made a similar python script available as a Github gist [1] a while back that given an audio file does the following:

- Converts to 16kHz WAV

- Transcribes using native ggerganov whisper

- Calls out to a local LLM to clean the text

- Prints out the final cleaned up transcription

I found that accuracy/success increased significantly when I added the LLM post-processor even with modestly sized 12-14b models.

I've been using it with great success to convert very old dictated memos from over a decade ago despite a lot of background noise (wind, traffic, etc).

[1] https://gist.github.com/scpedicini/455409fe7656d3cca8959c123...
by mgh95 | 2025-09-22 19:12:47+00:00
Currently, selling LLM inference is a red queen race: the moment you release a model, others begin distilling and attempting to sell your model cheaper, avoiding the expensive capitalized costs associated with R&D. This can occur because the LLM market is fundamentally -- at best -- minimally differentiated; consumers are willing to switch between vendors ("big labs", as you call them, but they aren't really research labs) to whomever offers the best model at the lowest price. This is emphasized by the distributors of many LLMs, developer tools, offering ways to switch the LLM at runtime (see https://www.jetbrains.com/help/ai-assistant/use-custom-model... or https://code.visualstudio.com/docs/copilot/customization/lan... for an example of this). The distributors of LLMs actively working against LLM providers margin provides an exceptionally strong headwind.

This market dynamic begets a low margin race to the bottom, where no party appears able to secure the highly attractive (think the >70% service margin we see in typical tech) unit economics typical of tech.

Inference is a very tough business. It is my opinion (and likely the opinion of many others) that the margins will not sustain a typical "tech" business without continual investment to attempt to develop increasingly complex and expensive models, which itself is unprofitable.
by makaimc | 2025-09-22 19:12:56+00:00
AssemblyAI (YC S17) is currently the one that stands out in the WER and accuracy benchmarks (https://www.assemblyai.com/benchmarks). Though its models are accessed through a web API rather than locally hosted, and speaker diarization is enabled through a parameter in the API call (https://www.assemblyai.com/docs/speech-to-text/pre-recorded-...).
by kogus | 2025-09-22 19:12:59+00:00
Assuming that these claims are unsubstantiated, as the article indicates[1], what is the motivation for the Trump administration to put forward this bogus assertion?

[1]From the article:

A Kenvue spokesperson told CNBC in a statement that "over a decade of rigorous research, endorsed by leading medical professionals and global health regulators," shows there’s no credible evidence linking acetaminophen to autism.
by theptip | 2025-09-22 19:13:08+00:00
OpenAI is profitable if they stop training their next generation models. Their unit economics are extremely favorable.

I do buy that they are extremely over-valued if they have to slow down on model training.

For cloud providers, the analysis is a bit more complex; presumably if training demand craters then the existing inference demand would be met at a lower price, and maybe you’d see some consolidation as margins got compressed.
by coldtea | 2025-09-22 19:13:11+00:00
>FOSS barely existed in 2005 compared to what it is today.

On the contrary: it barely exists today.

FOSS in (roughly speaking) 2005 and before was about a larger vision and a community. Not about mere access to code with specific licenses, or how many trillion dollar companies are depending on it.

>Communities rarely stay the same as they grow larger, but that doesn't mean they are worse. .

I'm not speaking about how communities in change in abstract (in which case doesn't mean necessarily for the worse). I'm speaking about what specific FOSS communities have had happened to them, and which I, and others, do find worse.
by mNovak | 2025-09-22 19:13:17+00:00
This is ignoring the utilization factor though. Both Google and OpenAI have to overprovision servers for the worst case simultaneous users. So 1.71 GW average doesn't tell use the maximum instantaneous GW capacity of Google -- if we pull a 4x out of the hat (i.e. peak usage is 4x above average), it becomes ~7 GW of available compute.

More than a "Google" of new compute is of course still a lot, but it's not many Googles' worth.
by unshavedyak | 2025-09-22 19:13:26+00:00
> Now you've likely been downvoted because you're complaining about downvotes.

Fwiw i think it was only once, and i was upvoted after mentioning it. You're right i could have worded it as something more ambiguous, aka "it seems this is unpopular" or w/e, but my edit was in reply to someones feedback (the downvote), so i usually mention it.

No complaint, just a form of wordless-feedback that i was attempting to respond to. Despite such actions being against HN will heh.
by Jtsummers | 2025-09-22 19:13:35+00:00
Working Effectively with Legacy Code by Michael Feathers. It spends a lot of time on how to introduce testability into existing software systems that were not designed for testing.

Property-Based Testing with PropEr, Erlang, and Elixir by Fred Hebert. While a book about a particular tool (PropEr) and pair of languages (Erlang and Elixir), it's a solid introduction to property-based testing. The techniques described transfer well to other PBT systems and other languages.

Test-Driven Development by Kent Beck.

https://www.fuzzingbook.org/ by Zeller et al. and https://www.debuggingbook.org/ by Andreas Zeller. The latter is technically about debugging, but it has some specific techniques that you can incorporate into how you test software. Like Delta Debugging, also described in a paper by Zeller et al. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=988....

I'm not sure of other books I can recommend, the rest I know is from learning on the job or studying specific tooling and techniques.
by jjav | 2025-09-22 19:13:53+00:00
> A friend of mine who loves Tesla watched this video and said "many humans would have hit that".

The very same video demonstrates this is not true, since the human in the video sees the debris from far away and talks about it, as the self-driving Tesla continues obliviously towards it. Had that same human been driving, it would've been a non-issue to switch to the adjacent lane (completely empty).

But as you said, the friend loves Tesla. The fanboys will always have an excuse, even if the same video contradicts that.
by scoofy | 2025-09-22 19:13:59+00:00
Yea, what’s the alternative then? When anti-social behavior overwhelms the system, the only alternative is a complete system collapse rather than a removal of the anti-social actors.

Many of us live in places where everyone, in the very same breath, insists everything should be welcoming to everyone (and usually free) while also insisting that enforcement of norms is unjust. You can’t have it both ways.