MurphyA/hacker-news huggingface dataset:
by whizzter | 2025-08-08 20:06:27+00:00
RightToolForTheRightJob!

Would you try to write/work on a collaboratibe text document (ie Google Docs or Sheets?) by editing a paragraph/sentence that's server side rendered and hope nobody changes the paragraph mid-work because the developers insisted on SSR ?

These kinds of tools (Docs, Sheets, Figma, Linear,etc) work well because changes have little impact but conflict resolution is better avoided by users noticing that someone else is working on it and hopefully just get realtime updates.

Then again, hotel booking or similar has no need for something like that.

Then there's been middle-ground like an enterprise logistics app that had some badly YOLO'd syncing, it kinda needed some of it but there was no upfront planning and it took a time to retrofit a sane design since there was so much domain and system specifics things lurking with surprises.
by Aurornis | 2025-08-08 20:06:33+00:00
I think the local LLM scene is very fun and I enjoy following what people do.

However every time I run local models on my MacBook Pro with a ton of RAM, I’m reminded of the gap between local hosted models and the frontier models that I can get for $20/month or nominal price per token from different providers. The difference in speed and quality is massive.

The current local models are very impressive, but they’re still a big step behind the SaaS frontier models. I feel like the benchmark charts don’t capture this gap well, presumably because the models are trained to perform well on those benchmarks.

I already find the frontier models from OpenAI and Anthropic to be slow and frequently error prone, so dropping speed and quality even further isn’t attractive.

I agree that it’s fun as a hobby or for people who can’t or won’t take any privacy risks. For me, I’d rather wait and see what an M5 or M6 MacBook Pro with 128GB of RAM can do before I start trying to put together another dedicated purchase for LLMs.
by 8note | 2025-08-08 20:06:34+00:00
the existence of "legacy code" i think is sufficient evidence that the code is not a sufficiently detailed description of a system. if it were, legacy code would not exist, because any engineer could simply read the code and maintain it like the original authors, without needing to say, talk to stake holders or prior documentation, etc.

we're still going to need well educated, skilled engineers, but the LLM context can store both lower fidelity details - eg. "this needs a list, but who cares if its an array or a linked list" and detail not covered by the running code "this looks like it could be a set, but we didnt do that because ..."
by kens | 2025-08-08 20:06:35+00:00
As an aside, people should avoid using "deprecate" to mean "shut down". If something is deprecated, that means that you shouldn't use it. For example, the C library's gets() function was deprecated because it is a security risk, but it wasn't removed until 12 years later. The distinction is important: if you're using GPT-4o and it is deprecated, you don't need to do anything, but if it is shut down, then you have a problem.
by ewoodrich | 2025-08-08 20:06:42+00:00
It's my workhorse model with Roo Code given the cost - or lack thereof. I was about to cancel Copilot after they massively cut the premium limits until they swapped out 4o with 4.1 for the base model. 4.1 is just decent enough for simple, uncreative tasks and is pretty reliable as far as tool use (especially compared to 4o) so I have had a lot of success with it.

For any problem with a lot of reasoning or problem solving I use "architect" mode first with Gemini 2.5 Pro or Claude Sonnet 3.7/4 to break it into discrete subtasks that 4.1 can follow pretty successfully. This approach is very cost effective as Gemini can do a lot of high level planning quickly and cheaply.

I'm sure a lot of the experience depends on how 4.1 is being used, I've fine tuned my custom Roo code configuration to work around its limits without a lot of sacrifices, I'm sure using it out of the box with Copilot is asking a lot more from a weaker model on its own.
by Szpadel | 2025-08-08 20:07:14+00:00
AFAIK main trick is batching, GPU can do same work on batch of data, you can work on many requests at the same time more efficiently.

batching requests increase latency to first token, so it's tradeoff and MoE makes it more tricky because they are not equally used.

there was somewhere great article explaining deepseek efficiency that explained it in great detail (basically latency - throughput tradeoff)
by chasd00 | 2025-08-08 20:07:17+00:00
This is about 2/3 the way through the article:

"The employment statistics are broadly consistent with the reduction in immigrant labor supply. Job growth has slowed more this year in industries that have a higher fraction of unauthorized immigrants like construction and restaurants, according to analysis by Jed Kolko at the Petersen Institute."

...I feel like the article answers its own question pretty well. I guess the headline is there for SEO/"engagement".
by KraftyOne | 2025-08-08 20:08:03+00:00
As the post says, the exactly-once guarantee is ONLY for steps performing database operations. For those, you actually can get an exactly-once guarantee by running the database operations in the same Postgres transaction as your durable checkpoint. That's a pretty cool benefit of building workflows on Postgres! Of course, if there are side effects outside the database, those happen at-least-once.
by chatmasta | 2025-08-08 20:08:36+00:00
I will mess with all kinds of hardware, especially mini PCs and routers.. I once had a few hundred iPhones in my closet… but I draw the line at anything that uses batteries or electricity in a non-standard way. If the wire can’t carry data, I’m not touching it.

Maybe it’s because when I was a kid, I fancied myself an experimenter, and I had a wire ripped off a lamp, and touched the two ends together…
by ActorNightly | 2025-08-08 20:08:53+00:00
Those days are all over btw.

Most trading firms are past the whole "beat the other guys to buy". Established large investment firms already have all that on lockdown in terms of infrastructure and influence to the extent where they basically just run the stock market at this point (i.e Tesla posts horrible quarter numbers, but stock goes up).

Most of the smaller firms basically try to figure out the patterns of the larger firms and capitalize on that. The timescales have shifted quite a bit.
by mhh__ | 2025-08-08 20:09:05+00:00
> "We have a fancy trading algorithm that statistically is never going to outperform just buying VOO and holding it, but the thing is if you get lucky, it could".

You wish lol. How do you think they pay for all the developers?

Firms like HRT don't even take outsider money, they don't really need to.

And besides, we don't get paid for beating stocks, a lot of funds will do worse than equities in a good year for the latter, the whole point is that you're benchmarked to the risk free rate because your skill is in making money while being overall market neutral. So you rarely take a drawdown anywhere near as badly as equities.

As a service this is often a portfolio diversification tool for large allocators rather than something they put all the money into.

It is true however that some firms are basically just rubbish beta vehicles that probably should in an ideal world shut down.
by oneplane | 2025-08-08 20:09:37+00:00
The article says so:

> AWS blamed the termination on a “third-party payer” issue. An AWS consultant who’d been covering my bills disappeared, citing losses from the FTX collapse. The arrangement had worked fine for almost a year—about $200/month for my testing infrastructure.

He essentially got screwed over by the consultant. Everything else is a side-effect but not material to the cause.
by PaulHoule | 2025-08-08 20:09:40+00:00
... it drives me crazy that there is a drumbeat over this every year in the US, which feels some real guilt over this and has had some reconciliation of it with Japan whereas people in China, Korea and elsewhere in Asia are 1000x angrier about what Japan did to them than how Japan is angry with the US and where there has been much less reconciliation.

Sometimes I wonder if it's just an attempt to keep a cloud spread over atomic energy.
by magicmicah85 | 2025-08-08 20:09:53+00:00
I am asking in good faith and I understand why there would be a preference towards private versus public. It sounds like Trump does not care to attempt a private conversation as he wants Tan out. The Cadence settlement is likely the only public info we have about Tan's conflicts, the government has more info and they aren't going to spend time working through private channels, though it sounds like Tan is trying that now.
by ladberg | 2025-08-08 20:10:32+00:00
> Its a finance firm - i.e scam firm. "We have a fancy trading algorithm that statistically is never going to outperform just buying VOO and holding it, but the thing is if you get lucky, it could".

HRT trades their own money so if it didn't beat VOO then they'd just buy VOO. There are no external investors to scam.
by nuancebydefault | 2025-08-08 20:10:48+00:00
If you follow that reasoning, no person is useful and no tool is useful.

The little box I'm filling now is, compared to a lot of other interfaces, a shitty interface. That doesn't mean it isn't useful. Probably it is getting replaced, only with a slightly better inferface.

The karma system is quite simplistic and far from perfect. I'm sure there are ways to go around it. The moderators make mistakes.

That doesn't mean the karma and moderation are not useful. I hope you get my point but it's fine if we disagree as well.
by whizzter | 2025-08-08 20:12:01+00:00
It could also be that some ransomware crap has used their codebase as a foundation for their system and then it gets flagged.

It's a very very common problem in the Demoscene, demoscene authors striving to impress in the 64k category created better generic EXE compressors to shrink more content into their 64k binaries, just when any tool is publicly released it is almost immediately flagged by AV software since virus makers scour our forums knowing that once in a while a useful tool comes to hide their malicious code.
by tracker1 | 2025-08-08 20:12:38+00:00
I think that security/stability for a country as big as the US requires at least some localization. For example, IMO all medications, medical devices, infrastructure systems (such as telecom, power, etc.), hardware and materials should be at least 50% domestically produced and have at least dual sourcing.

I realize that not all countries are big or diverse enough to accomplish this, and that's a reason why loose confederations like the EU exist. The US started much closer to that itself.
by motorest | 2025-08-08 20:12:55+00:00
> If the political angle is not relevant to the analysis, then why do you enjoy it?

The politics angle is unavoidable because Krugman is commenting on the impact that the economic policies of the current US administration is having on the US economy.

This is the same US administration that fires staticians for reporting numbers that render bare the impact of their own economic policies, which they are actively trying to censor.

We live in a day and age where in the US reporting facts leads to political persecution. Of course mentioning stagflation, as Krugman does, is deemed political.
by captainmuon | 2025-08-08 20:13:12+00:00
I work at a university data center, although not on LLMs. We host state of the art models for a large number of users. As far as I understand, there is no secret sauce. We just have a big GPU cluster with a batch system, where we spin up jobs to run certain models. The tricky part for us is to have the various models available on demand with no waiting time.

But I also have to say 700M weekly users could mean 100M daily or 70k a minute (low ball estimate with no returning users...) is a lot, but achievable at startup scale. I don't have out current numbers but we are several orders of magnitude smaller of course :-)

The big difference to home use is the amount of VRAM. Large VRAM GPUs such as H100 are gated being support contracts and cost 20k. Theoretically you could buy a Mac Pro with a ton of RAM as an individual if you wanted to run auch models yourself.
by alpb | 2025-08-08 20:13:17+00:00
I've been following DBOS for a while and I think the model isn't too different than Azure Durable Functions (which uses Azure Queues/Tables under the covers to maintain state). https://learn.microsoft.com/en-us/azure/azure-functions/dura...

Perhaps the only difference is that Azure Durable Functions has more syntactic sugar in C# (instead of DBOS choice being Python) to preserve call results in the persistent storage? Where else do they differ? At the end, all of them seem to be doing what Temporal is doing (which has its own shortcomings and it's also possible to get it wrong if you call a function directly instead of invoking it via an Activity etc)?
by CalRobert | 2025-08-08 20:13:33+00:00
It's not just the filing, the tax burden is heavy and complicated. You need to opt for one of three regimes, etc.

https://accountinginsights.org/how-does-pfic-taxation-work-f...

I live in Europe and contemplated writing a tool to analyze ETF holdings and buy the stocks individually with the IBKR API, but it's an expensive and error-prone approach.
by Aurornis | 2025-08-08 20:13:40+00:00
> If you bought a decently powerful inference machine 3 or 5 years ago, it's probably still plugging away with great tok/s.

I think this is the difference between people who embrace hobby LLMs and people who don’t:

The token/s output speed on affordable local hardware for large models is not great for me. I already wish the cloud hosted solutions were several times faster. Any time I go to a local model it feels like I’m writing e-mails back and forth to an LLM, not working with it.

And also, the first Apple M1 chip was released less than 5 years ago, not 7.
by sagarm | 2025-08-08 20:13:54+00:00
Taxing land ownership reduces returns on land ownership, making consolidation less rather than more likely. Wasn't that your main concern?

And yes, the amount of money to spend and how that money are collected are separate political questions. LVT is just about funding sources. Most Georgists are also for "pigouvian" taxes and taxing negative externalities.
by zerd | 2025-08-08 20:14:06+00:00
This. the main trick, outside of just bigger hardware, is smart batching. E.g. if one user asks why the sky is blue, the other asks what to make for dinner, both queries go though the same transformer layers, same model weights so they can be answered concurrently for very little extra GPU time. There's also ways to continuously batch requests together so they don't have to be issued at the same time.
by dragonwriter | 2025-08-08 20:14:20+00:00
Property is a legal construct. (“Fiction” implies that legal constructs are intended to say something about external reality, such that there could also be contrasting “legal nonfiction”, but all the constructs are equally constructed and equally not dictated by reality but instead by what someone thinks will have desirable effects on reality.)

The question for any category of property is whether it is a socially useful construct or not, not whether it has a basis is nature.
by andylizf | 2025-08-08 20:14:45+00:00
This is fantastic work. The focus on a local, sandboxed execution layer is a huge piece of the puzzle for a private AI workspace. The `coderunner` tool looks incredibly useful.

A complementary challenge is the knowledge layer: making the AI aware of your personal data (emails, notes, files) via RAG. As soon as you try this on a large scale, storage becomes a massive bottleneck. A vector database for years of emails can easily exceed 50GB.

(Full disclosure: I'm part of the team at Berkeley that tackled this). We built LEANN, a vector index that cuts storage by ~97% by not storing the embeddings at all. It makes indexing your entire digital life locally actually feasible.

Combining a local execution engine like this with a hyper-efficient knowledge index like LEANN feels like the real path to a true "local Jarvis."

Code: https://github.com/yichuan-w/LEANN Paper: https://arxiv.org/abs/2405.08051
by parliament32 | 2025-08-08 20:15:20+00:00
> But Montanez said there’s no immediate indication as to who the culprit is.

My understanding was you cannot fly without filing a flight plan (or is this just a Canada-specific thing?), and that flight plan has to be submitted by someone, so there has to be a trail here. If the plans were not filed, after all, how would he be able to tell the plane was flown "multiple times" during one of this extended absences?

EDIT: Yes it's Canada-specific, required for any flights over 25 nautical miles, including VFR https://laws-lois.justice.gc.ca/eng/regulations/sor-96-433/p...
by canyon289 | 2025-08-08 20:15:20+00:00
Im a research person building models so I can't answer your questions well (save for one part)

That is, as a research person using our GPUs and TPUs I see first hand how choices from the high level python level, through Jax, down to the TPU architecture all work together to make training and inference efficient. You can see a bit of that in the gif on the front page of the book. https://jax-ml.github.io/scaling-book/

I also see how sometimes bad choices by me can make things inefficient. Luckily for me if my code/models are running slow I can ping colleagues who are able to debug at both a depth and speed that is quite incredible.

And because were on HN I want to preemptively call out my positive bias for Google! It's a privilege to be able to see all this technology first hand, work with great people, and do my best to ship this at scale across the globe.
by 82716f12 | 2025-08-08 20:15:37+00:00
> "We have a fancy trading algorithm that statistically is never going to outperform just buying VOO and holding it, but the thing is if you get lucky, it could".

How they make $8B/y underperforming VOO?

Reference: https://www.businessinsider.com/hudson-river-trading-hrt-8-b...
by Volundr | 2025-08-08 20:15:57+00:00
Obviously I'm not an economist, nor do I play one on TV.

One would indeed expect removing currency from the economy to be deflationary, but in GPs example we didn't just remove currency, we removed demand too. If less people have money to buy a car, less cars are produced. When you are making 1k instead of 1m cars, you no longer benefit as much from scale and must raise your prices, which only the rich can afford.

Now why might this happen instead of prices dropping to the point the now-poorer people can afford them? Maybe the cost of inputs can't go much lower, or maybe other less-stratified markets are picking up the slack, so demand shifts there. Or maybe the rich have enough money they don't care about the higher prices. Or some combination of all of the above.

Economies are complicated beasts, it's rarely as simple as X leads to Y. Instead you have the whole alphabet pulling in different directions and the forces that win out may be quite unintuitive.
by beezle | 2025-08-08 20:16:02+00:00
Home internet is a luxury if you already have a data plan on your phone to accomplish the necessities - that is for access to government and corporate web sites and educational (school related) needs. Social media, in its basic forms are text and photos which also should fit in most included MVNO data plans such as this one from US Mobile which is $22.50/mo or $228/yr (19/mo)

Unlimited High-Speed Data Unlimited Talk & Text 20 GB Hotspot Data

FYI - I live in a fairly rural area and have coverage. The standard home internet plan here runs about $90/mo after all taxes and tithes are paid.
by nine_k | 2025-08-08 20:16:12+00:00
Beside that, I like the idea that the nuclear bombing saved numerous lives of the Japanese, who did not have to experience and die in fire bombings or being recruited to fight on the streets, in the fields, and in the mountains. The battle of Iwo Jima [1] can serve as an example how bloody such fights might be.

In 1945, the Japanese Empire was training schoolchildren to fight with bayonets and sharpened bamboo logs, to make them part of land defense operations. The nukes made the emperor surrender and prevented all that.

[1]: https://en.wikipedia.org/wiki/Battle_of_Iwo_Jima
by heathrow83829 | 2025-08-08 20:16:16+00:00
I think it's a moot point. We've been trying to increase the number of jobs and the amount that jobs pay for most of modern history. And since when has that ever worked? well it worked until about the 70s and then we roughly flat line for about 30 years and since 98, its been nothing but down hill from there (if you dought this, calculate the standard of living: nominal gdp per capita or median wages / case-shiller housing index). by all means try but it's not going to work.

There's two sides to personal finance: what you earn and what you spend. earning more, on a wholistic countrywide scale, simply isn't possible anymore (if the last 50 years has taught us anything).

The answer lies in allowing the economy to make life more cost effective (removing regulations that force housing costs to be high, making more land available for living, thus driving down it's costs, etc.). The answer lies in controlling costs and spending, both in the personal life and for government.
by godelski | 2025-08-08 20:16:33+00:00
I'm actually curious about how you both come to those definitions of hallucinations. It gets very difficult to distinguish these things when you dig into them. Simon dropped this paper[0] in another thread[1] and while they provide a formal mathematical definition I don't think this makes it clear (I mean it is one person (who doesn't have a long publication record, PhD, or work at a university), but following their definition is still a bit muddy. They say the truth has to be in the training but don't clarify if they mean in training distribution or literal training example.

To make a clear example, is the fact that when prompting GPT-5 with "Solve 5.x = x + 5.11" it answers "-0.21" (making the same mistake as when it GPT-4 says 5.11 > 5.9). Is that example specifically in the training data? Who knows! But are those types of problems in the training data? Absolutely! So is this a mistake or a hallucination? Should we really be using an answer that requires knowing the exact details of the training data? That would be fruitless and allow any hallucination to be claimed as a mistake. But in distribution? Well that works because we can know the types of problems trained on. It is also much more useful given that the reason we build these machines is for generalization.

But even without that ambiguity I think it still gets difficult to differentiate a mistake from a hallucination. So it is unclear to me (and presumably others) what the precise distinction is to you and Simon.

[0] https://arxiv.org/abs/2508.01781

[1] https://news.ycombinator.com/item?id=44831621
by andsoitis | 2025-08-08 20:16:36+00:00
> The missing dynamic is that businesses are encouraged to increase growth in profit YoY. > Each year, a business needs to grow faster than it did the previous year.

It is very reasonable for an investor or a worker wanting the business they have hitched their financial wellbeing to to do very well, which means growing profit. It gives the business more strength and stability.