MurphyA/hacker-news huggingface dataset:
by hodgesrm | 2025-05-22 17:32:21+00:00
> If we look at the time a bit closer, we see the queries take anywhere between a minute and half an hour. Those are not unreasonable waiting times for analytical queries on that sort of data in any way.

I'm really skeptical arguments that say it's OK to be slow. Even on the modern laptop example queries still take up to 47 seconds.

Granted, I'm not looking at the queries but the fact is that there are a lot of applications where users need results back in less than a second.[0] If the results are feeding automated processes like page rendering they need it back in 10s of millisecond at most. That takes hardware to accomplish consistently. Especially if the datasets are large.

The small data argument becomes even weaker when you consider that analytic databases don't just do queries on static datasets. Large datasets got that way by absorbing a lot of data very quickly. They therefore do ingest, compaction, and transformations. These require resources, especially if they run in parallel with query on the same data. Scaling them independently requires distributed systems. There isn't another solution.

[0] SIEM, log management, trace management, monitoring dashboards, ... All potentially large datasets where people sift through data very quickly and repeatedly. Nobody wants to wait more than a couple seconds for results to come back.
by kstrauser | 2025-05-22 17:32:44+00:00
Crap. My Kobo Libra supports Pocket as its only built-in way to get articles onto the device. I use GoodLinks to store links I like, and have a Shortcut that copies new articles from GoodLinks to Pocket. If I’m reading something interesting but long, I bookmark it, and that evening it’s on my ereader waiting for me.

It’s a nice setup. I’ll miss it. There’s not a great replacement, either. Even if I create a GoodLinks-to-epub pipe or something, now all those articles will be mixed in with my books and magazines. I don’t want to have to pick through a hundred random articles to find the next book I want to read.

Mozilla, hear me out: what if, just what it, you drop some of the AI stuff you’re blowing cash on that people who use Firefox often actively dislike? Could you shave a percent off that and use it to fund Pocket instead?
by aidenn0 | 2025-05-22 17:33:12+00:00
At higher quality/bitrates, the difference is much smaller and device support is universal for AVC and quite good for HEVC. Anything over 1.5GB for a single episode would probably only be farily similarly sized with AV1.

There is one large exception, but I don't know the current scene well enough to know if it matters: sources that are grainy. I have some DVD and blurays with high grain content and AV1 can work wonders with those thanks to the in-loop grain filter and synthesis -- we are talking half the size for a high-quality encode. If I were to encode them for AVC at any reasonable bitrate, I would probably run a grain-removal filter which is very finicky if you don't want to end up with something that is overly blurry.
by mmh0000 | 2025-05-22 17:33:20+00:00
That's a very general statement.

For the last 10 years, I've taken 2500IU/day of Vitamin D. My last bloodwork put my D at 54ng/Ml which is slightly on the high side.

Everyone, but especially those using supplements, should be getting bloodwork done at least twice a year. Guessing which additional vitamins are needed in your diet is a great way to waste money. Bloodwork is covered by most insurance and will give you concrete numbers.

Also, I think you may have misread the title, it shaves 3 years off your biological age. I.e. biomarkers look younger than you are.
by eggbrain | 2025-05-22 17:34:26+00:00
> [...] Its 100% about getting people to stay on your platform as long as possible and engage with your content. Usually that means creating content that gets people to negatively engage with your content. So much so, its now referred to as "rage bait" where Only Fans women purposely post content that gets men to engage with their posts in order to make more money. Political posts are made to inflame either side and get more shares and upvotes.

I touch upon this in https://www.scottgoci.com/social-media-platforms-whats-wrong... and https://www.scottgoci.com/social-media-platforms-whats-wrong... -- but as you mention, this is a result of engagement being a core metric of social media platforms, and users attempting to game the platform's algorithm for their own purposes.

An easy way to solve for this is customization -- if no two users have the same "algorithm" powering their feed, it becomes hard for anyone to do this, because perhaps one user's algorithm filters out anything tagged with politics, or with a low Flesch–Kincaid score, or non-text posts, etc.
by minimaxir | 2025-05-22 17:34:27+00:00
So I decided to try Claude 4 Sonnet against my "Given a list of 1 million random integers between 1 and 100,000, find the difference between the smallest and the largest numbers whose digits sum up to 30." benchmark I tested against Claude 3.5 Sonnet: https://news.ycombinator.com/item?id=42584400

The results are here (https://gist.github.com/minimaxir/1bad26f0f000562b1418754d67... ) and it utterly crushed the problem with the relevant microoptimizations commented in that HN discussion (oddly in the second pass it a) regresses from a vectorized approach to a linear approach and b) generates and iterates on three different iterations instead of one final iteration), although it's possible Claude 4 was trained on that discussion lol.

EDIT: "utterly crushed" may have been hyperbole.
by Draiken | 2025-05-22 17:34:33+00:00
Our brains are wired to answer to stimuli but that doesn't necessarily mean we consciously want it.

These platforms prey on us with every possible tactic to keep us there since every second "engaged" means profits for them.

If we take a generic view of "if they are in these platforms, then they want it" we might as well say that fish want to be caught because they bite the hook.
Show HN: Secure Execution of AI-Generated Code Locally on macOS/Linux MicroVMs
by appcypher | 2025-05-22 17:34:52+00:00
Built a Rust project that lets you securely run untrusted/AI-generated code in lightweight VMs. Spins up in milliseconds, runs on your own infra, no containers. And it works on Macos and Linux.

Python, Rust, and TypeScript SDKs are available now so you can spin up vms with just 4-5 lines of code. Run code, plot charts, tear down VMs programmatically with no complex setup.

Early days though. Thoughts appreciated if you're building dev tools or AI agents that need proper isolation without performance headaches.
by AdmiralAsshat | 2025-05-22 17:35:07+00:00
Well, crap. I've had a Pocket account for more than ten years. It's a key feature on my Kobo devices, to boot.

I hope Kobo manages to find some alternative provider for similar functionality, rather than just dropping it altogether.

EDIT: Oh, and worth noting that this product will officially die before Mozilla fulfills its promise to open source it, back when they acquired Pocket. Thanks, guys.
by jt2190 | 2025-05-22 17:35:27+00:00
Kikkoman USA has been brewing a lighter soy sauce in Wisconsin for the U.S. market for a few decades while now. It’s what most people in the U.S. think of when they hear “Kikkoman”.

Specialty markets sell imported Kikkoman products, such as “traditionally brewed” soy sauce which tastes stronger. Note that “stronger” doesn’t mean “better”: Asian consumers are used to using different styles of soy sauce as they see fit. U.S. consumers still largely view soy sauce as a single thing with no variation except maybe “low sodium”. Definitely worth exploring the different varieties.
by margalabargala | 2025-05-22 17:35:29+00:00
I couldn't have explained it better myself. Glad you understand!

Aside from the last bit. The rainfall per unit area is not relevant to the shape of a particular container. 5mm of rain falls regardless of your container shape. Whether that 5mm of rain falling, also means that the water in your container is 5mm deep, is a function of your container shape.

It's not a unit problem. If you're trying to measure rainfall in a conical vessel, you can do that, and the conversion from collected volume to fallen rain will still yield the same 5mm out of the sky.
by stevekemp | 2025-05-22 17:36:45+00:00
I've been forced to use linear a fair bit recently and I have to say it's a mess of client-side javascript that often gets itself into a weird state.

For example open five tabs, each pointing to a new issue. Then clicking on an issue in the current cycle will just show a blank page.

Or when accepting an issue from triage you might find it defaults to "subscribe to updates", randomly. Or you might find you're the owner of a new story for no reason.

The number of times I have to force-reload the website to "fix" things is uncountable. And the whole forced-workflow is unpleasant compared to how I prefer to work. I mean it's better than Jira, in most ways, but .. sometimes I wish to go back to server-rendered stuff even if it is Atlassian-speed, where it felt like your server literally was in Australia the amount of time page-fetches took to complete.
by diggan | 2025-05-22 17:37:05+00:00
> Can we assume everything that can be updated is updated?

What does that even mean? Of course an LLM doesn't know everything, so it we wouldn't be able to assume everything got updated either. At best, if they shared the datasets they used (which they won't, because most likely it was acquired illegally), you could make some guesses what they tried to update.
by waleedlatif1 | 2025-05-22 17:37:36+00:00
imo, model regression might actually stem from more aggressive use of toolformer-style prompting, or even RLHF tuning optimizing for obedience over initiative. i bet if you ran comparable tasks across 3-5, 3-7, and 4-0 with consistent prompts and tool access disabled, the underlying model capabilities might be closer than it seems.
by samrus | 2025-05-22 17:37:45+00:00
from a foundational research perspective, the pokemon benchmark is one of the most important ones.

these models are trained on a static task, text generation, which is to say the state they are operating in does not change as they operate. but now that they are out we are implicitly demanding they do dynamic tasks like coding, navigation, operating in a market, or playing games. this are tasks where your state changes as you operate

an example would be that as these models predict the next word, the ground truth of any further words doesnt change. if it misinterprets the word bank in the sentence "i went to the bank" as a river bank rather than a financial bank, the later ground truth wont change, if it was talking about the visit to the financial bank before, it will still be talking about that regardless of the model's misinterpretation. But if a model takes a wrong turn on the road, or makes a weird buy in the stock market, the environment will react and change and suddenly, what it should have done as the n+1th move before isnt the right move anymore, it needs to figure out a route of the freeway first, or deal with the FOMO bullrush it caused by mistakenly buying alot of stock

we need to push against these limits to set the stage for the next evolution of AI, RL based models that are trained in dynamic reactive environments in the first place
by dang | 2025-05-22 17:37:45+00:00
8 isn't large enough to overcome randomness, alas!

Edit: I actually looked through https://news.ycombinator.com/submitted?id=imurray yesterday to see if there was anything we could invite a repost of. (I do this sometimes when looking at which users were first to submit an interesting article.) I didn't see anything, but on a second look https://news.ycombinator.com/item?id=7984992 could be interesting, so you'll get an email inviting you to repost that one, if you want to :)
by ortusdux | 2025-05-22 17:37:51+00:00
I really enjoyed https://waldenpond.press/ when it was up and running. They selected articles from your pocket once a month and then printed, bound, and mailed them to you. When I discovered the service I had a 500 hour reading backlog, and for $14/mo I was getting 100+ page books of self-curated content. They were perfect for flights, trips, and lending out. I was able to force it to include recipes as well, and I still find myself referencing them frequently.
by amlib | 2025-05-22 17:37:51+00:00
Not automatically but when you open a dead link you can ease the pain by using an extension such as "page archive" [1] to quickly search an archive such as the wayback machine and perhaps get something useful out of it.

I've always wished a browser such Firefox would extend bookmarks as an offline archive of all links you add to it. Your own personal wayback machine perhaps.

[1] https://addons.mozilla.org/firefox/addon/view-page-archive/
by zamadatix | 2025-05-22 17:38:08+00:00
Sure, but despite there being a 2.0 release between they didn't even feel the need to release a Pro for it still isn't the kind of GPT 2 -> 3 improvement we were hoping would continue for a bit longer. Companies will continue to release these incremental improvements which are all always neck-and-neck with each other. That's fine and good, just don't inherently expect the versioning to represent the same relative difference instead of the relative release increment.
by trod1234 | 2025-05-22 17:38:08+00:00
This is what happens when you let delusional bankers run things.

Monetary policy fails in low interest rate environments, and you get chaotic whipsaws thereafter which grow with time. You can find reference to this if you know where to look as far back as the 1930s.

Greedy corrupt blind individuals who have managed to infect leadership win so much that they lose everything.

We are getting a front-row seat to the specifics described in the socialist calculation problem, and it won't stop with just the US. This type of fire keeps burning until the fuel is out.
by chriskw | 2025-05-22 17:38:23+00:00
The post presents it a bit out of order, but it was mostly from realizing at some point that the way the fractal grows by a factor of 5, base 5 number systems, and the "spiral" mentioned in the post can all fit together. I also thought a lot about how to programmatically draw the fractal and a natural way would be to start from the middle and zoom out.

There's an apocryphal story about Richard Feynman about how he used to keep a dozen or so random problems in the back of his mind and made a little bit of progress on them every time he saw a connection, until finally he'd solve one and everyone would think he magically figured it out instantly. This was a bit similar except I'm not nearly at that level and I've only been able to do that for one problem instead of a dozen.
by steveBK123 | 2025-05-22 17:38:24+00:00
> The unspoken secret is that this kind of BS wasn't/isn't only going on in the data fields (in my opinion).

Yes, once you see it in one area you notice if everywhere.

A lot of IT spend is CEOs chasing something they half heard/misunderstanding a competitor doing, or a CTO taking Gartner a little too seriously, or engineering leads doing resume driven architecture. My last shop did a lot of this kind of this stuff "we need a head of [observability|AI|$buzzword].

The ONE thing that gives me the most pause about DuckDB is that some people in my industry who are guilty of the above are VERY interested in DuckDB. I like to wait for the serial tech evangelists to calm down a bit and see where the dust settles.
by uxcolumbo | 2025-05-22 17:38:41+00:00
They should at least allow to download their copy of the saved articles, PDF or HTML or whatever format they save it in.

This is such a betrayal. Some old links might not exist anymore, so it's useless to only get the links.

EDIT: Betrayal, because the main reason I paid for Pocket was the archiving of articles and now I can't actually export the archived copies.

Their decision of not enabling export of the archived copies now makes it very unlikely that I'll ever pay for any of their paid services in the future.

A shame really because I like supporting Firefox as a browser.
by dpacmittal | 2025-05-22 17:38:49+00:00
I read an article a while ago where the goal is to process a file as fast as possible and the article talks about compressing the data chunks so they fit in L1 cache. The cache misses were slower than compressing and decompressing the data from L1 cache.

I've been trying to find that article ever since but I'm not able to. Anyone knows the article I'm talking about?
by diggan | 2025-05-22 17:39:05+00:00
> although it's possible Claude 4 was trained on that discussion lol

Almost guaranteed, especially since HN tends to be popular in tech circles, and also trivial to scrape the entire thing in a couple of hours via the Algolia API.

Recommendation for the future: keep your benchmarks/evaluations private, as otherwise they're basically useless as more models get published that are trained on your data. This is what I do, and usually I don't see the "huge improvements" as other public benchmarks seems to indicate when new models appear.
by toss1 | 2025-05-22 17:39:24+00:00
That is trivially true, but stop both-sides-ing it with false equivalency.

At this point, the major party in power is doing all they can to undermine democracy and strip-mine the country for their own benefit and that of their few multi-billionaire sponsors.

The other party is attempting to herd a broad coalition of people to maintain democracy.

Yes, it is imperfect, and the country has fallen often far short of perfection through it's entire history.

That is no reason to set the perfect as the enemy of the good. Simply declaring "every form of government is (or all parties are) awful" is a cop-out, and the logical conclusion of that is a complete power vacuum which leads only to the population being ruled by rival gangs & fiefdoms.
by fhd2 | 2025-05-22 17:39:44+00:00
I'd argue a lot of the current AI hype is fuelled by hopium that models will improve significantly and hallucinations will be solved.

I'm a (minor) investor, and I see this a lot: People integrate LLMs for some use case, lately increasingly agentic (i.e. in a loop), and then when I scrutinise the results, the excuse is that models will improve, and _then_ they'll have a viable product.

I currently don't bet on that. Show me you're using LLMs smart and have solid solutions for _todays_ limitations, different story.
by thimabi | 2025-05-22 17:39:59+00:00
> How important is it to be using SOTA?

I believe in using the best model for each use case. Since I’m paying for it, I like to find out which model is the best bang for my buck.

The problem is that, even when comparing models according to different use cases, better models eventually appear, and the models one uses eventually change as well — for better or worse. This means that using the same model over and over doesn’t seem like a good decision.
by Rudybega | 2025-05-22 17:40:23+00:00
I'm going to have to heavily disagree. Gemini 2.5 Pro has super impressive performance on large context problems. I routinely drive it up to 4-500k tokens in my coding agent. It's the only model where that much context produces even remotely useful results.

I think it also crushes most of the benchmarks for long context performance. I believe on MRCR (multi round coreference resolution) it beats pretty much any other model's performance at 128k at 1M tokens (o3 may have changed this).
by lendacerda | 2025-05-22 17:40:29+00:00
Yes you need good amounts of data for the LLM to learn the language. But after some point, the easyness of the language is more important. Python and Javascript (or TS) are kings

Ideally, you dont wanna LLM to reason. You yourself should understand the problem and the better solution for it, and then the AI just executes on it
by skeaker | 2025-05-22 17:40:36+00:00
I've had this for as long as I can remember. I have distinct memories from being maybe toddler-aged and having this. I've found that the Valsalva maneuver can make it fade away faster, as can placing your palm over your ear and squeezing it to pump air around. Always figured it was something to do with the pressure in my ear.
by hinkley | 2025-05-22 17:40:44+00:00
> I’ve been interested in speeding up allocations for quite some time. We know that calling a C function from Ruby incurs some overhead, and that the overhead depends on the type of parameters we pass.

> it seemed quite natural to use the triple-dot forwarding syntax (...).

> Unfortunately I found that using ... was quite expensive

> This lead me to implement an optimization for ... .

That’s some excellent yak shaving. And speaking up … in any language is good news even if allocation is not faster.
by gobblegobble2 | 2025-05-22 17:40:45+00:00
Same and it's my favourite Kobo feature. I hope Mozilla releases Pocket source code for people willing to self-host it. Kobos are highly hackable and I'm sure the community will find a way to change getpocket.com domain in the built-in Pocket app, even if Rakuten chooses not to provide this option.
by bcrosby95 | 2025-05-22 17:41:14+00:00
Even if LLMs never reach AGI, they're good enough to where a lot of very useful tooling can be built on top of/around them. I think of it more as the introduction of computing or the internet.

That said, whether or not being a provider of these services is a profitable endeavor is still unknown. There's a lot of subsidizing going on and some of the lower value uses might fall to the wayside as companies eventually need to make money off this stuff.
by chermi | 2025-05-22 17:41:17+00:00
I'd interested to hear more about your workflow. I use Gemini for discussing the codebase, making ADR entries based on discussion, ticket generation, documenting the code like module descriptions and use cases+examples, and coming up with detailed plans for implementation that cursor with sonnet can implement. Do you have any particular formats, guidelines or prompts? I don't love my workflow. I try to keep everything in notion but it's becoming a pain. I'm pretty new to documentation and proper planning, but I feel like it's more important now to get the best use out of the llms. Any tips appreciated!
by nine_k | 2025-05-22 17:41:21+00:00
This is what the original Twitter basically was.

Now imagine a celebrity appearing on the network. Suddenly there is a ton of people who want to know which events the celebrity is attending. And what pictures the celebrity shares. And what opinions the celebrity holds.

Then someone discovers that they can attract a lot of followers by posting not only about events they attended, but also cat pictures and funny jokes.

Hello, mentions, retweets, tags, and other ways of mass broadcasting. Hello interactive drama machine.

To avoid this, you have to actively resist broadcasting, force the users vet their subscribers, etc. All this works against the network effects, and thus against the money-making potential of the service.
by devgoth | 2025-05-22 17:41:23+00:00
there is no external server! all meeting information is stored as metadata on the message.

this leads to some issues with potential collisions like if two people click the Whenish message at the same time and submit their message, there is no way to merge both that data. while this is an issue, i wanted to err on the side of privacy as much as possible and not rely on a server at all.