MurphyA/hacker-news huggingface dataset:
by systems | 2025-05-27 14:43:01+00:00
"LumoSQL can swap back end key-value store engines in and out of SQLite."

=>

"LumoSQL can swap SQLite backend, with Key-value store engines"

===

"LMDB is the most famous (but not the only) example of an alternative key-value store"

=>

"We currently only support LMDB as an alternative KV store"

===

"and LumoSQL can combine dozes of versions of LMDB and SQLite source code like this:"

=>

"LumoSQL will allow you to use different versions of SQLite and LMDB in parallel as different backends"
by pdabbadabba | 2025-05-27 14:43:09+00:00
> Peregrine falcons adapted quite well, and they're much more sizeable.

I'm not sure what you mean. As far as I am aware -- and according to every source I've looked at in the last few minutes -- Peregrine falcons and Cooper's hawks are about the same size (length and wingspan are within 1-2 inches).
by overflow897 | 2025-05-27 14:43:10+00:00
I think articles like this have the big assumption under them that we are going to plateau with progress. If that assumption is true, then sure.

But if it's false, there's no saying you can't eventually have an ai model that can read your entire aws/infra account, look at logs, financials, look at docs and have a coherent picture of an entire business. At that point the idea that it might be able to handle architecture and long term planning seems plausible.

Usually when I read about developer replacement, it's with the underlying assumption that the agents/models will just keep getting bigger, better and cheaper, not that today's models will do it.
by mmmBacon | 2025-05-27 14:43:26+00:00
Quantum computing is still a technology of the future. When we are still talking about 12 qubits as a breakthrough, there’s a long way to go. Optical interconnects are the least of quantum computing’s problems.

However, it’s not correct to say lasers are unreliable. It’s fundamentally false and it’s not supported by field data from today’s pluggable modules. 10’s of millions of lasers are deployed in data centers today in pluggable modules.

It’s also useful to remember that an LED is essentially the gain region of a laser without the reflectors. When lasers fail in the field, they fail for the same reasons an LED will fail; moisture or contamination penetration of the semiconductor material.

An LED is not useful for quantum computing. To create a Bell pair (2qubits) you need a coherent light source to create correlated photons. The photons produced by an incoherent light source like an LED are fundamentally uncorrelated.
by dgfl | 2025-05-27 14:43:32+00:00
Trapped-ion and neutral-atom QC require lasers because the light signal needs to be coherent. That's the main feature of a classical laser, really. The explanation with the number of photons doesn't really cut it, because even a perfect laser does not have a definite photon number: coherent states are inherently uncertain in both photon number and phase. But LEDs are even worse, because the light signal is truly incoherent. It's not even a good quantum state, it's a classical superposition of incoherent photons that you can't really use for any quantum control.

But even more than that, this seems to me like a purely on-chip solution. For trapped ions and neutral atoms you really need to translate to free-space optics at some point.
by cometapi | 2025-05-27 14:45:01+00:00
Midjourney’s Remix Mode has rapidly become one of the most transformative features for creators seeking to iterate on and refine their AI-generated imagery. As of April 2025, with the launch of Midjourney V7, Remix Mode has been enhanced with smoother workflows, expanded parameter control, and deeper integration across both Discord and the Midjourney web interface. In this comprehensive guide, we’ll explore what Remix Mode is, how to activate and leverage its capabilities, recent updates that have shaped its evolution, and best practices for integrating Remix into professional design and content creation pipelines.
by falcor84 | 2025-05-27 14:45:34+00:00
> Humans are insanely smart and capable, treat them that way and good results occur.

My experience isn't quite that. While most humans can be capable when they want to, in typical situations they often don't and aren't. People who have put in years to become proficient in mainframe terminals aren't representative people in a typical situation; most people (myself definitely included) perform most daily actions on autopilot.
by serf | 2025-05-27 14:45:57+00:00
a large part of the benefit to an agentic ai is that it can coordinate tests that it automatically wrote on an existing code base, a lot of time the only way to get decent answers out of something like that is to let it run as bare metal as it can. I run cursor and the accompanying agents in a snapshot'd VM for this purpose. It's not much different than what you suggest, but the layer of abstraction is far enough for admin-privileged app testing, an unfortunate reality for certain personal projects.

I haven't had a cursor install nuke itself yet, but I have had one fiddling in a parent folder it shouldn't have been able to with workspace protection on..
by jgwil2 | 2025-05-27 14:47:07+00:00
The word "keep" here is synonymous with "continue," implying that this is already happening. It's fair game to ask if that's actually the case.

And this is by the way, but English sentences almost always have some degree of ambiguity; to talk about "well defined meaning" in the context of natural languages is to make a category error.
Show HN: I made a tool to create diagrams from sketches
by pc11000 | 2025-05-27 14:47:40+00:00
Hey HN

I used tools like drawio to create diagrams manually. But its slow and painfull! So, I built something more convenient!

It lets you create diagrams from a simple text prompt or sketches. You can export them as image or JSON and edit them if needed.

Would love your feedback
by Balgair | 2025-05-27 14:47:43+00:00
I think you've identified the main issue here:

LLMs aren't destroying the University or the essay.

LLMs are destroying the cheap University or essay.

Cheap can mean a lot of things, like money or time or distance. But, if Universities want to maintain a standard, then they are going to have to work for it again.

No more 300+ person freshman lectures (where everyone cheated anyways). No more take-home zoom exams. No more professors checked out. No more grad students doing the real teaching.

I guess, I'm advocating for the Oxbridge/St. John's approach with under 10 class sizes where the proctor actually knows you and if you've done the work. And I know, that is not a cheap way to churn out degrees.
by throwanem | 2025-05-27 14:47:54+00:00
Peregrines are somewhat smaller and much more lightly built. I live in a nesting pair's territory which often sees transitory Cooper's; they're easy to distinguish both in flight and at rest. Male Cooper's are more peregrine-sized and hard to tell from sharp-shinned hawks sometimes, but that is an ordinary enough sexual dimorphism in birds.

Interestingly, while peregrines and accipiters like Cooper's share a habit of taking passerines in flight, the response of potential prey seems to differ. I frequently see songbirds mob a Cooper's; I can't think offhand of a time I've seen them respond to a peregrine other than by crypsis.
by bartread | 2025-05-27 14:48:40+00:00
I don't know about that: I'm a manager, I'm aware of Taylorism (and isn't that guy discredited by sensible people anyway?), and I don't think the factory view holds up. Manufacturing is about making the same thing (or very similar things) over and over and over again at scale. That almost couldn't be further from software development: every project is different, every requirement is different, the effort in every new release goes into a different area of the software. Just because, after it's gone through the CD pipeline the output is 98% the same is irrelevant, because all the software development effort for that release went into the 2%.
by ranger207 | 2025-05-27 14:48:55+00:00
There's a few comments here about how AI will revolutionize learning because it's personalized or lets users explore or whatever. That's fundamentally missing the point. College students who are using AI aren't using it to learn better, they're using it to learn _less_. The point of writing an essay isn't the essay itself, it's the process of writing the essay: research, organization, writing, etc. The point of doing math problems isn't to get the answer, it's to _do the work_ to find the answer. If you let AI do that, you're not learning better, you're learning worse.

Now, granted, AI can help with things students are passionate about. If you want to do gamedev you might be able to get an AI to walk you through making a game in Unity or Godot. But societally we've decided that school should be about instilling a wide variety of base knowledge that students may not care about: history, writing, calculus. The idea is that you don't know what you're going to need in your life, and it's best to have a broad foundation so that if you run into something that needs it you'll at least know where to start. 99% of the time developing CRUD apps you're not going to need to know that retrieving an item from an array is O(n), but when some sales manager goes in and adds 2 million items to the storefront and now loading a page takes 12 seconds and you can't remove all that junk because it's for an important sales meeting 30 minutes from now, it's helpful to know that you might be able to replace it with a hashmap that's O(1) instead. AI's fine for learning things you want to learn, but you _need_ to learn more than just what you _want_ to learn. If you passed your Data Structures and Algorithms class by copy/pasting all the homework questions into ChatGPT, are you going to remember what big-O notation even means in 5 years?
by georgemcbay | 2025-05-27 14:49:01+00:00
I totally agree as a developer (who sometimes uses LLMs).

They can be a useful tool, but their current capabilities and (I personally believe) their ability to improve indefinitely are wildly overhyped. And the industry as a whole has some sort of blinders on, IMO, related to how progress made with them is lumpy and kind of goes in both directions in the sense that every time someone introduces their grand new model and I play around with it I'll find some things it is better at than the previous version and some things it is worse at than the previous version. But number go up, so progress... I guess?

On one hand I can laugh this all off as yet another management fad (and to be clear, I don't think LLM usage is a fad, just the idea that this is going to be world-changing technology rather than just another tool), but what scares me most about the current AI hype isn't whether LLMs will take all of our jobs, but rather the very real damage that is likely to be caused by the cadre of rich and now politically powerful people who are pushing for massive amounts of energy production to power all of this "AI".

Some of them are practically a religious cult in that they believe in human-caused climate change, but still want to drastically ramp up power production to absurd levels by any means necessary while handwaving away the obvious impact this will have by claiming that whatever damage is caused by the ramp up in power production will be solved when the benevolent godlike AI that comes out on the other side will fix it for us.

Yeah, I uh don't see it working out that way. At all.
by mcdermott | 2025-05-27 14:49:05+00:00
When raw performance matters, vLLM wins, but Ollama often wins on everything else.

My benchmarks showed vLLM delivering up to 3.2x the requests-per-second of Ollama on identical hardware, with noticeably lower latency at high concurrency.

If you're not looking for the ultimate performance on the latest GPU hardware, then Ollama is still hard to beat. It installs in minutes, runs on laptops, supports CPU fallback, and provides a curated model hub plus on-the-fly model switching. If your typical load is a handful of concurrent users, batch jobs that can wait an extra second, or local exploration during development, Ollama’s “good-enough” performance is exactly that, good enough.

Ollama is the reliable daily driver that gets almost everyone where they need to go; vLLM is the tuned engine you unleash when the freeway opens up and you really need to fly.
by mdaniel | 2025-05-27 14:49:08+00:00
> In this case, you can visit kulfi://http-e9b1c82b43206c96173848ed0afad2fe633fdc8a02ba391a3d37, which is where the Talk App lives.

What is the DNS story for this platform? Or are you intending to be kind of like a replacement for Syncthing where each endpoint has to explicitly approve the other and thus discovery is left as an exercise to the reader?

Actually, even after further thought, I am still able to rename my peers in Syncthing, and unless one has to go to the dashboard for getting that Talk App link(? button?) all the time, it's been my experience that folks will always want aliases for ginormous hex strings

---

p.s. you have some broken images in your Journey docs
by deepdarkforest | 2025-05-27 14:49:11+00:00
Terrible stuff and a reddish flag. First of all, gpt signs all over the blog post, reads like a bottom of the barrel linkedin post.

But more importantly, why double and triple down on no RAG? As with most techniques, it has its merits in certain scenarios. I understand getting VC money so you have to prove differentiation and conviction in your approach, but why do it like this? What if RAG does end up being useful? You'll just have to admit you were wrong and cursor and others were right? I don't get it.

Just say we don't believe RAG is as useful for now and we take a different approach. But tripling down on a technique so early into such a new field seems immature to me. It screams of wanting to look different for the sake of it.
by beAbU | 2025-05-27 14:49:16+00:00
> slightly archaic

How are em-dashes "slightly" archaic in this context? Can you point me to a single example of internet discourse from the last 30 years where a human used an em-dash unironically?

Academic papers doesn't count, literature doesn't count. I'm looking for an example of human created discourse online. The crux of the allegation is that normal meatbag humans don't use an em-dash when conversing with one another online, or when writing informal texts, purely because there is no key for the em-dash on the keyboard (that I know of).

I posit that the use of an em-dash in online discourse is so archaic that it's a 100% surefire giveaway of AI.
by serbuvlad | 2025-05-27 14:49:41+00:00
Sure.

But

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

is less likey to get hijacked and scp all my files to $REMOTE_SERVER than a Deb file from the releases page of a random 10-star github repository. Or even from a random low-use PPA.

But I've just never heard anyway complain about "noobs" installing deb packages. Ever.

Maybe I just missed it.
by BugheadTorpeda6 | 2025-05-27 14:50:14+00:00
I think recent history has made Solows paradox more interesting than Jevons, which is mostly a thing talked about by people with something to sell related to AI it seems, and less so by economists. Seems to have applied much better early in the industrial revolution. I'm not sure economists even work on Jevons anymore (or if it was ever a very interesting topic for them, the writing on it seems very sparse in comparison).
by mmooss | 2025-05-27 14:50:38+00:00
> Back in the early 2000s, UI design like this had a high skill ceiling. It took years to master lighting, materials, and depth. Now? That level of craft is often just a [AI] prompt away.

That is very interesting: Modernism and its descendents were very much about minimalism - how much could you do with minimal components. It applies to visual aesthetics (including much of abstract art), writing (e.g., Hemingway), architecture, and much else, even some music (singer-songwriters, Philip Glass). It's democratic - anyone can do it, or far more than can design complicated aesthetics. There have been other trends since, some rejecting that concept, but you can see that minimalism everywhere, in clothes, in industrial design, and even in HN's design. 'Great designers', you may have heard, 'focus not on what to add, but on what to take away'.

AI enables maximalism; it could transform aesthetics in everything. It enables complexity - including in fashion, in architecture, in writing, almost everywhere.

This theory is that AI removes the issue of efficiency for the creator: AI allows people to create maximalist, or non-minimalist design easily. Still, minimalism's value is very much about efficiency for the user, including focus. Excess design is a distraction and is generally not productive - how does distracting us with detailed icons help us? What is the value?

I love that efficiency in modernism. HN takes the minimalist approach, iirc, in part to attract a community that is focused on its content and not bells and whistles. And I worry that in broader society, as people now routinely hide from very serious dangers (to freedom, to peace, from climate change, etc.), this new trend will be more circuses to distract us.
by dgfl | 2025-05-27 14:51:09+00:00
I use qwerty-fr [0] for this. It's pretty nice, since it works on all three major OSes and is basically a few compose layers on top of a US base layout. I use it to type greek letters, swedish vowels, italian accents and math symbols. A couple of non-breaking spaces are also there. It's the only layout I use nowadays.

[0]: https://qwerty-fr.org/
by noisy_boy | 2025-05-27 14:51:43+00:00
> Even IntelliJ has gateway

By IntelliJ's own (on-machine) standards, Gateway is crap. I use the vi emulation mode (using ideavim) and the damn thing gets out of sync unless you type at like 20wpm or something. Then it tries to rollback whatever you type until you restart it and retry. I can't believe it is made by the same Jetbrains known for their excellent software.
by consumer451 | 2025-05-27 14:51:48+00:00
Related paper: https://arxiv.org/abs/2502.05167

> We evaluate 12 popular LLMs that claim to support contexts of at least 128K tokens. While they perform well in short contexts (<1K), performance degrades significantly as context length increases. At 32K, for instance, 10 models drop below 50% of their strong short-length baselines. Even GPT-4o, one of the top-performing exceptions, experiences a reduction from an almost-perfect baseline of 99.3% to 69.7%.

I post this because this information seems very important for users of LLMs, and devs implementing LLMs in their own solutions.

The fall-off in accuracy is far faster and greater than I had imagined.

Someone should really make this an ongoing thing, which evaluates new models as they are released. Or, this information should be included in all model system cards.
by bartread | 2025-05-27 14:52:01+00:00
You're misunderstanding my meaning with pipeline: you're thinking it's just the CD part of the equation. I'm thinking about it as the whole software development and delivery process (planning, design, UX, dev, test, PR reviews, CD, etc), which can be standardised (and indeed some certifications require it to be standardised). In that context, even when the development pipeline follows a standardised process, most of it's nothing like a factory: just the CD part, as you've correctly identified. Because the output of CD will be, for mature software, 99+% similar to the output of the previous build - it is definitely somewhat analagous to manufacturing, although if you think about adding tests, etc., the process evolves a lot more often and rapidly than many production lines.
by electroly | 2025-05-27 14:52:06+00:00
I'm not convinced--codebase indexing is still a killer feature in Cursor. I have tens of thousands of reference files stashed in the project directory to be indexed so that any time the model reaches out to the codebase search tool with a question, it finds a file with the answer. Lots of it is not code and has no AST representation; it's documentation. Without codebase indexing, it may entirely miss the context.

1. This argument seems flawed. Codebase search gives it a "foot in the door"; from that point it can read the rest of the file to get the remaining context. This is what Cursor does. It's the benefit of the agentic loop; no single tool call needs to provide the whole picture.

2. This argument is "because it's hard we shouldn't do it". Cursor does it. Just update the index when the code changes. Come on.

3. This argument is also "because it's hard we shouldn't do it". Cursor does it. The embeddings go in the cloud and the code is local. Enforced Privacy Mode exists. You can just actually implement these features rather than throwing your hands up and saying it's too hard.

This honestly makes me think less of Cline. They're wrong about this and it seems like they're trying to do damage control because they're missing a major feature.
by jodrellblank | 2025-05-27 14:52:20+00:00
> "they followed herds of ruminant animals and hunted them. they were working 90% of their waking hours"

Idk if you've ever seen sheep in person, but "standing near some sheep while they eat grass" is not work in the sense of effort, concentration, labour. There's a reason the Boy Who Cried Wolf was bored out of his skull, and why shepherding was a task given to a boy while the village adults were doing other things.
by ogogmad | 2025-05-27 14:52:36+00:00
Slightly OT: Regarding the raising of the minimum wage example, is there a reason why the following linear argument is not universally accepted?

> The more something costs, the less of it people buy; > THEREFORE the more that hiring people costs, the fewer people get hired; > SO raising the minimum wage raises unemployment.

I doubt anything in economics is as linear as WHEN PRICES GO UP THEN PURCHASES GO DOWN, especially given demand inelasticity, feedback loops, and other things that complicate such a model.
by FinnKuhn | 2025-05-27 14:52:57+00:00
I believe all international organizations and projects I support from time to time were already mentioned in this thread.

However, there are also some local (German in my case) organizations I have donated to.

1. GFF - Gesellschaft für Freiheit (anti surveillance and pro digital civil rights in the EU and Germany) [1]

2. Frag den Staat (platform enabling easy freedom of information requests in Germany and their publishing in addition to related digital civil rights activities) [2]

[1] https://freiheitsrechte.org/en/ [2] https://fragdenstaat.de/ (German only)
by palmotea | 2025-05-27 14:53:51+00:00
> I'm not saying they can do it today. I'm saying there's no ruling out they might be able to do it soon.

There's also no "ruling out" the Earth will get zapped by a gamma-ray burst tomorrow, either. You seem to be talking about something that, if done properly, would require AGI.

You can do anything with AI. Anything at all. The only limit is yourself.
by formalreconfirm | 2025-05-27 14:54:06+00:00
Thank you for your work ! We use DuckDB with dbt-duckdb in production (because on-prem and because we don't need ten thousands nodes) and we love it ! About the COPY statement, it means we can drop Parquet files ourselves in the blob storage ? From my understanding DuckLake was responsible for managing the files on the storage layer.
by Tycho | 2025-05-27 14:54:10+00:00
I read Jack Welch’s autobiography Straight from the Gut. He was quite proud of the stack ranking process he introduced (rate employees every year and fire the bottom 25%). I recently listened to an interview with TSMC founder Morris Chang (arguably a better CEO than Welch, at this point), who said he never agreed with the idea of doing layoffs based on performance appraisals. He pointed out that any such process was hopelessly subjective and so how, as an engineer, could he support it and keep his integrity intact.

Btw, there’s a great interview with the author of Power Failure on the Bloomberg Masters in Business podcast.