MurphyA/hacker-news huggingface dataset:
by code_biologist | 2025-05-23 07:17:28+00:00
fuzzycomplete - https://github.com/Query-farm/fuzzycomplete "This fuzzycomplete extension serves as an alternative to DuckDB's autocomplete extension, with several key differences: ..."

lindel - https://github.com/Query-farm/lindel "This lindel extension adds functions for the linearization and delinearization of numeric arrays in DuckDB. It allows you to order multi-dimensional data using space-filling curves. ... Linearization maps multi-dimensional data into a one-dimensional sequence while preserving locality, enhancing the efficiency of data structures and algorithms for spatial data, such as in databases, GIS, and memory caches."
by AnthonyMouse | 2025-05-23 07:17:53+00:00
> many people in this thread are saying average users are just using their web browser, so they are “served fine with linux”. But apparently 8GB is unacceptable to run a web browser on mac os.

Are these things in contradiction? A web browser can very easily use more than 8GB of RAM by itself.

> Barely noticeable and the system remained very responsive.

"It's fine to run out of ram and start swapping because the SSD is fast."

Wearing out the soldered SSD isn't fine.
by AnthonyMouse | 2025-05-23 07:21:15+00:00
> That $40 16GB SODIMM is significantly slower than the memory they use

No it isn't, Apple uses ordinary LPDDR5. The higher end models achieve higher bandwidth in the same way as HEDT PCs: By using more memory channels. The base M1 in that MacBook Air doesn't even do that, it has the same memory bandwidth as dual channel DDR5 PCs.
by eviks | 2025-05-23 07:21:26+00:00
If it's not impressive why is the article so impressed (it's even in the headline)?

And no, not making any mistakes isn't critical, ... some are. You can have a million of UI mistakes and regressions (where is the stat for how many regressions there are?) and what not in the UI of you Stripe Dashboard app without any of them being critical. The "finance" aura doesn't permeate literally everything a finance company does, raising it to the critical level
by DonHopkins | 2025-05-23 07:21:55+00:00
Yeah, it seems pretty up-to-date with Elon's latest White Genocide and Holocaust Denial conspiracy theories, but it's so heavy handed about bringing them up out of the blue and pushing them in the middle of discussions about the Zod 4 and Svelte 5 and Tailwind 4 that I think those topics are coming from its prompts, not its training.
by smadge | 2025-05-23 07:22:06+00:00
One letter increments wouldn’t work because each commit has to leave the program correct. For example committing the first f of a for loop would leave the code with a syntax error. But you often should break up changes into as small as possible commits that leave the code correct. E.g. make one commit that refactors the code (no change in program output), then another change which implements the change in program behavior that motivated the refactor. This generally makes commits easier to review, less likely to contain defects, and easier to attribute bugs and roll back.
by kriro | 2025-05-23 07:22:38+00:00
I think you overestimate the level of math required in AI and at the same time I think you underestimate the math skills of John. AI runs on GPUs, Quake 2 engine was one of the first to optimized for GPUs (OpenGL).

I'm pretty excited to see him in this domain. I think he'll focus on some DeepSeek style improvements.
by aaiiggcc000 | 2025-05-23 07:23:09+00:00
Hey HN

I'm thrilled to launch SlimImg.tools today – a project born out of a simple need: a fast, private, and powerful way to compress images and manage their metadata without uploading them to a server.

We all know large images slow down websites and can be a pain to share. While many online tools exist, I was always a bit uneasy about uploading my images, especially sensitive ones, to third-party servers. Plus, I often wanted more control over EXIF data like location tags.

That's why I built SlimImg.tools! It's a completely browser-based image utility that puts you in control:

Key Features:

100% Local Processing: Your images are processed directly in your browser. No uploads, ever. This means super-fast operations and your privacy is completely respected. Adjustable Compression: Fine-tune the quality percentuale and see a live preview to get the perfect balance between file size and visual fidelity for JPG, PNG, and WebP. Powerful EXIF Management: View, edit, or completely strip EXIF metadata, including GPS location data, to protect your privacy. Image Resizing: Easily resize images by pixels, percentage, or max dimension while keeping aspect ratio. Format Conversion: Convert images between common formats (though EXIF preservation is best with JPEG output for now). Batch Processing: Optimize multiple images with the same settings at once and download them as a ZIP. Multiple Format Support: Works with JPG, PNG, WebP, and can read many others. Light & Dark Mode: Adapts to your system or lets you choose. Free & No Sign-up: Just drag, drop, and optimize! Whether you're a developer optimizing site assets, a marketer prepping images for a campaign, a photographer managing metadata, or just someone who wants to quickly shrink a photo before emailing it, SlimImg.tools is designed to be your go-to.

I'd absolutely love for you to give it a try at https://slimimg.tools/ and let me know what you think! All feedback, suggestions, and questions are incredibly welcome – they'll help make SlimImg even better.
by realusername | 2025-05-23 07:24:07+00:00
In today's world, attacks on your data are much more common than targeted exploits on the kernel so I would put it in opposite order. If there's no privacy then there's no security.

> Irony being that Mac OS X is the best at privacy out of the commercial OS out there.

The bar is very low and OSX is still way below a Linux distribution
by forgotoldacc | 2025-05-23 07:24:47+00:00
Verily, it could thus be said that that grammar of thine is incorrect, could it not? Wherefore dost thou decide grammar shan't change?

today's right grammar is yesterday's wrong grammar. yesterday's right grammar is today's cringe tryhard writing. languages evolve

and tbh most people who demand strict compliance are always the ones who make grammatical mistakes and don't realize it

> What a motherf*ing garbage the new iOS keyboard is

is not grammatically correct. "a" breaks the sentence
by mschuster91 | 2025-05-23 07:25:48+00:00
> But it still feels like some key ingredient is missing.

Continuous training is the key ingredient. Humans can use existing knowledge and apply it to new scenarios, and so can most AI. But AI cannot permanently remember the result of its actions in the real world, and so its body of knowledge cannot expand.

Take a toddler and an oven. The toddler has no concept of what an oven is other than maybe that it smells nice. The toddler will touch the oven, notice that it experiences pain (because the oven is hot) and learn that oven = danger. Place a current AI in a droid toddler body? It will never learn and keep touching the oven as soon as the information of "oven = danger" is out of the context window.

For some cases this inability to learn is actually desirable. You don't want anyone and everyone to be able to train ChatGPT unsupervised, otherwise you get 4chan flooding it with offensive crap like they did to Tay [1], but for AI that physically interacts with the meatspace, constant evaluation and learning is all but mandatory if it is to safely interact with its surroundings. "Dumb" robots run regular calibration cycles for their limbs to make sure they are still aligned to compensate for random deviations, and so will AI robots.

[1] https://en.wikipedia.org/wiki/Tay_(chatbot)
by BoorishBears | 2025-05-23 07:26:32+00:00
I'm not sure how anyone's really going act like the vast majority of the deepfakes generated with celebrity LORAs isn't porn when the term itself has become synonymous with non-consensual porn.

And it was just in April (less than a month ago) that they stepped up moderation of celebrity NSFW content: the study is from June of 2024.

The study was an attempt to avoid someone immediately trying to argue about a really obvious truth, but some people will still try to argue about the study about the really obvious truth.
by hijodelsol | 2025-05-23 07:27:09+00:00
If you read any work from Ed Zitron [1], they likely cannot remain sustainable. With OpenAI failing to convert into a for-profit, Microsoft being more interested in being a multi-modal provider and competing openly with OpenAI (e.g., open-sourcing Copilot vs. Windsurf, GitHub Agent with Claude as the standard vs. Codex) and Google having their own SOTA models and not relying on their stake in Anthropic, tarrifs complicating Stargate, explosion in capital expenditure and compute, etc., I would not be surprised to see OpenAI and Anthropic go under in the next years.

1: https://www.wheresyoured.at/oai-business/
by mattbee | 2025-05-23 07:28:33+00:00
Yes! It's exactly what it says it's not, an Incredible Journey post, from Anil, who is a laser-sharp writer.

I kept reading because I assumed they were going to - idk open source it or allow you to host Glitch apps elsewhere - but nope, it's just a straight shutdown announcement. What have I got wrong?

I'd assume there is some obfuscation required by owners or whatever pending a change of ownership, something like that?

Anyhow, RIP, if the internet has taught me anything it's that we can't have nice things for more than about 10 years.
by MattPalmer1086 | 2025-05-23 07:28:45+00:00
I'd largely agree. Snap was what drove me away from Ubuntu, after the calculator app started taking ages to load. The calculator! It was instant before snapification.

I have played with using FlatPak, and while it seems snappier than snap, I always ended up with something not quite working, because of permissions or sandboxing. The answer to a lot of problems seemed to be "don't use the FlatPak version".

The set of software I use complex enough to need something like FlatPak while also not needing to interact with other things is basically very, very small.
by ivyirwin | 2025-05-23 07:29:48+00:00
I was hoping the article was going to be about a physical device as well as the software to manage and play songs. A few years ago I wanted to get my 10 year old son an mp3 player – he's really into listening to music but wasn't ready (still isn't) for a phone. I was shocked by the state of the mp3 player options. When Apple discontinued the iPod they created a huge vacuum that no one seems to have filled.

I think the iPos shuffle (usb stick form) is still the best mp3 player I ever had – it was small, pluggable without extra cords, and battery lasted a really long time. It didn't have a screen to browse music but that was part of the idea – just let the shuffle do its thing. Even this relatively simple concept has not been replicated in the hardware market.

People will say it's not a hardware problem but a software/drm issue. I think that's a real shame. I wish there were a good, inexpensive, portable device that would just play my music.
by riffraff | 2025-05-23 07:31:48+00:00
The article seems surprised that you can do so many changes at scale, but IMO that's the wrong perspective. The larger the scale you have, the easier it must be to ship a change.

Yes, regressions will be more painful if you manage trillions of dollars, but it also means shipping a fix for such regressions needs to be easy and fast, which you can only do if you have a good and frequent CI/CD pipeline.

See also "The Infallible five-tier system for measuring the maturity of your Continuous Delivery pipeline". You should live on "Friday".

https://qntm.org/cd
by sigmoid10 | 2025-05-23 07:32:27+00:00
This kind of context management is not that hard, even when building LLMs. Especially when you have huge windows like we do today. Look at how ChatGPT can remember things permanently after you said them once using a function call to edit the permanent memory section inside the context. You can also see that in Anthropic's latest post on Claude 4 where it learns to play Pokemon. The only remaining issue here is maybe how to diffuse explicit knowledge from the stored context into the weights. Andrej Karpathy wrote a good piece on this recently. But personally I believe this might not even be necessary if you can manage your context well enough and see it more like RAM while the LLM is the CPU. For your example you can then always just fetch such information from a permanent storage like a VDB and load it into context once you enter an area in the real world.
by Ekaros | 2025-05-23 07:32:48+00:00
Moles are used because they are useful abstraction. When you want to get from reaction equation to actual real word having some fixed weight is useful. It becomes useful to have fixed relatively usable quantity to work with.

They are relatively decent size for actually weighing out things.

And honestly mapping number of elementary particles directly to grams is not unreasonable. Even if because physics of world are tad weird there is still possibility for some sanity checks.
by eru | 2025-05-23 07:33:04+00:00
Yes.

I used to think that worrying about models offending someone was a bit silly.

But: what chance do we have of keeping ever bigger and better models from eventually turning the world into paper clips, if we can't even keep our small models from saying something naughty.

It's not that keeping the models from saying something naughty is valuable in itself. Who cares? It's that we need the practice, and enforcing arbitrary minor censorship is as good a task as any to practice on. Especially since with this task it's so easy to (implicitly) recruit volunteers who will spend a lot of their free time providing adversarial input.
by sailE | 2025-05-23 07:33:33+00:00
I'm not sure why the stat is nitpicked that much. Of course you can completely fake this stat. I have no idea if Stripe does or how much LoC or actual functional changes these deployments do. It's just that they are very confident in shipping changes, all with minimum downtime. Constantly, every day. For a company which does a major part of the financial infrastructure of the web, that's impressive.

In my opinion the goal isn't getting to some arbitrary number, it's making this possible. That there are no process/technical/cultural impediments not allowing you to do changes every single day.
by deafpolygon | 2025-05-23 07:36:13+00:00
I often put tentative plans in a separate "Calendar" and reassign it to the category if necessary.

Then I can turn "off" the other calendars and see only the tentative plans to zero in on stuff I have yet to deal with.

If I have a shared calendar, I will title it with (tentative) and promote it by removing the tag.
by fsckboy | 2025-05-23 07:36:36+00:00
https://en.wikipedia.org/wiki/Topping_out#History

the practice of "topping out" a new building can be traced to the ancient Scandinavian religious rite of placing a tree atop a new building to appease the tree-dwelling spirits displaced in its construction... The practice remains common in the United Kingdom and assorted Commonwealth countries such as Australia[7] and Canada,[8] as well as Germany, Austria, Slovenia, Iceland, Chile, Czech Republic, Slovakia, Poland, Hungary and the Baltic States. In the United States the last beam of a skyscraper is often painted white and signed by all the workers involved.[7] In New Zealand, completion of the roof to a water-proof state is celebrated through a "roof shout", where workers are treated to cake and beer.[9]
by deafpolygon | 2025-05-23 07:38:10+00:00
I am curious to see how this unfolds. I know that for many people, myself included, that the main appeal of a digital calendar is the edit-ability of it. I can move, edit, and even copy. And it's in text format (as opposed to ink) so that also means "readable" (in contrast to the chicken scratch that is my handwriting) and searchable.
by pona-a | 2025-05-23 07:39:13+00:00
We're actually quite certain what this new paradigm is, because some poor souls are already practicing it: slop coding. You prompt-whisper poorly-defined changes to make, and if the machine chokes on its own vomit along the way, you delete everything and try again.

It feels reasonable, consistent to see it as another "old man yells at the skies" scenario, but I do think it's unprecedented for a machine to automate thought itself on an unbounded domain and with such unreliability. We know calculators made people worse at mental math, but at least calculators don't give you off-by-one errors 40–60% of the time with no method of verification.

The reason why we haven't lost literacy to Speakwrites and screen readers is because they required more time and effort than doing it yourself. With AI, the supposed time savings are obvious: you don't put hours into reading the source to write an essay, you just ask ChatGPT, you don't learn programming fundamentals, you just ask for a script that does X, Y, and Z, etc... It feels like a good choice, but you're permanently crippling you education, both in a structured course and in the wild, and the supposed oracle is a slot machine, costing you $avg_tokens*$model_rate a pull. The poor news is slot machines sell.
by Paracompact | 2025-05-23 07:40:34+00:00
The execution order, or the order of the output list? The latter should be self-evident from the function body (first elements get collected first), and the former holds no tricks either since filters are evaluated from the head first, and concat (<>) allows lazy access to the first list's elements.

This is just a beginner's Haskell post. If an interviewer really meant to test optimization knowledge, I would hope they wouldn't ask me to optimize one O(n) utility function into another.
by DonHopkins | 2025-05-23 07:42:55+00:00
Fascinating, thank for that link! I was reading the sub-sections of the Proposed Solutions / Rehearsal section, thinking it seemed a lot like dreaming, then got to the Spontaneous replay sub-section:

>Spontaneous replay

>The insights into the mechanisms of memory consolidation during the sleep processes in human and animal brain led to other biologically inspired approaches. While declarative memories are in the classical picture consolidated by hippocampo-neocortical dialog during NREM phase of sleep (see above), some types of procedural memories were suggested not to rely on the hippocampus and involve REM phase of the sleep (e.g.,[22] but see[23] for the complexity of the topic). This inspired models where internal representations (memories) created by previous learning are spontaneously replayed during sleep-like periods in the network itself[24][25] (i.e. without help of secondary network performed by generative replay approaches mentioned above).

The Electric Prunes - I Had Too Much To Dream (Last Night):

https://www.youtube.com/watch?v=amQtlkdQSfQ
by jjmarr | 2025-05-23 07:43:18+00:00
I've never been able to one-shot a feature with an agent. It's much easier to "learn my way around the codebase" by watching the AI search the codebase and seeing its motivation/mental model.

Going AFK is a terrible idea anyways because I have to intervene when it's making bad architectural decisions. Otherwise it starts randomly deleting stuff or changing the expected results of test cases so they'll pass.
by MarcellusDrum | 2025-05-23 07:43:34+00:00
I think its a demand issue, not a hardware/software one. Chinese manufactures are creating Mini IPhone 16 and Mini S24, devices that look good, can play music, have the functionalities of a smart phone, and sell for $50-$100.

Parents will probably buy similar devices to their children instead of an MP3 Player. You have an unconventional parenting style not to get your son a phone at 14. Don't get me wrong, I respect that, but there isn't a lot like you to warrant a demand beyond what's currently available.
by adrian_b | 2025-05-23 07:44:29+00:00
During their early success years, Intel has made extremely few innovations. One of their few innovative products was the floating-point coprocessor 8087, which has changed completely how everybody does floating-point computations, and for which they were smart to hire external expertise (i.e. William Kahan) which has brought most of the innovative features.

On the other hand, during those years Intel has been extremely good at adopting very quickly any important innovation made by a competitor, while also succeeding to obtain better manufacturing yields, so that they were able to have greater profits, even with cheaper products.

Bellmac-32 has not been important commercially, but without it a product like Intel 80386 would have appeared only some years later.

With 80386, Intel has switched their production of CPUs from NMOS to CMOS, like also Motorola had done one year earlier with 68020. Both Intel and Motorola have drawn heavily from the experience gained by the industry with Bellmac-32.
by blippage | 2025-05-23 07:44:35+00:00
I'm currently using Slackware current. I use an approach of compiling from source or using AppImage. Things like Flatpak and Snaps are an opaque black box to me.

I have AppImages for things like Zoom, KeePass and LibreOffice. I don't need to keep updating them. They do what I want them to do. I have them on a separate partition. If I reinstall my system they're all ready to go out of the gate.

It's ridiculously simple.

I did try out Fedora awhile ago, but decided it wasn't for me. Why is everything a Flatpak? Just use the repo mechanism.
by thewisenerd | 2025-05-23 07:46:07+00:00
for this particular deployment;

we're only using the blob storage on azure. the deployments are on an on-prem kubernetes cluster with replicas=1 and strategy: recreate.

throughput: not very heavy tbf.. one webhook request every 10-ish seconds; each request leads to about 10-100+ entries added in a table.

migrations: since it's an internal console, we just took a couple hours downtime and did it.
by tucnak | 2025-05-23 07:46:31+00:00
Precursor just happens to use Xilinx Spartan 7-class, a 100 MHz VexRISC-V, RV32IMAC + MMU, 4k L1 I/D cache. But these days you could buy Versal devices with 1M+ LUT, and up to 100K DSP slices, in under a thou. However, integrating it—would be the real challenge. The FPGA hardware is sufficient for many non-toy Linux applications; open hardware isn't. This is a gateware limitation, not a hardware one.
by PeterStuer | 2025-05-23 07:46:38+00:00
'This requires discipline from both the person leading and the participants, but we're talking about a professional setting here, this isn't a big ask'

In my experience anything that requires discipline is too brittle to last. You can argue it should not be so, but it is.

Instead of discipline, an extrinsic force, robust motivation should be intrinsic, born from delivering a real value feeling to all participants.
by dmurray | 2025-05-23 07:47:29+00:00
It does discuss performance and points out some places where the Haskell implementation makes the natural naive solutions performant.

> While it's true that sort has an O(nlogn) performance profile, one interesting thing here is that sorting is lazy in Haskell! This means that if our two strings are unequal, they will only be sorted far enough to determine inequality!

I don't understand exactly how this works - don't all O(n log n) sorting algorithms still have to do some work on the other elements of the list before pulling out the smallest one? If you just scanned and pulled the smallest one to the front each time that is O(n^2). And there's an implementation detail here that differences at the start of the sorted string will be caught more quickly than at the end, so real-world behaviour is dependent on your choice of sort order.

Agreed that the performance analysis is quite superficial and that some of the solutions like sum NToTotal must be very sub-optimal.