skysight-inc/HackerNews huggingface dataset:
Ask HN: Deploying Docker Compose to the Desktop
I'm a bit frustrated that I can't seem to find a tool that will bundle my Docker compose app as a Windows and OSX app. Sure, there's Electron, I suppose, but I really want to take my app, which has three services, a React UI, a database server, and my worker nodes, along with a Postgres database, and deploy it to a customer's desktop using Docker Engine and my docker-compose.yml file. Starting Docker compose would pull the latest containers from the public repository and start the services, which can then be accessed at, say localhost:8080 (or another port).

Kamal (https://kamal-deploy.org/), from the Basecamp folks, seems interesting, but targeted more for IT folks than consumers.

Ideally, I'd like the OSX application to be installed as a normal OSX app, by dragging it into the Applications folder, and the Windows app would have an installer, I guess. Docker Engine would be installed, if needed, and the background services would be started on startup. Ideally, they'd even get a little icon to click on that launches their browser on a specified localhost port. The only bit of local info the app needs is the directory to mount via a Docker volume to access the local filesystem repository.

Why am I deploying a web app as a desktop app? Because the data the app uses, large audio and video repositories, are stored locally by most people, and not available on the cloud. Why not write a regular Desktop app? Because it makes more sense as a server-based app with multiple worker nodes, and it allows the same code to migrate to the cloud later. The worker nodes really want to be Python apps, because all ML is Python. The database service is pretty simple, and could be JavaScript, Python, Java, Go, or whatever. Mine is Python, just to make coordinating with the workers easier. The front end wants to be JavaScript so that I don't need to reimplement it for every OS. Is there a better way to cobble all that together other than containers?
I don't know why you got voted down. I am also skeptical about this bold claim because AI models are just complex mathematical functions/software and they do not have the capability to access, modify, or control computer systems or networks. It's most likely marketing fluff.
This could very well prove to be the case in software engineering, but also could very well not; what is the equivalent of "larger sets" in our domain, and is that something that is even preferable to begin with? Should we build larger codebases just because we _can_? I'd say likely not, while it does make sense to build larger/more elaborate movie sets because they could.

Also, a piece missing from this comparison is a set of people who don't believe the new tool will actually have a measurable impact on their domain. I assume few-to-none could argue that power tools would have no impact on their profession.
Yep. They're also a hearing aid that isn't conspicuously a hearing aid (i.e. "I'm not hard of hearing, I was just listening to some music earlier and haven't taken them out"). For younger users who might feel self-conscious about using a hearing aid, that's a big plus.
The problem is that SQLite already exists, and is public domain. It's a fantastic piece of software engineering that has had a lot of time and effort put into making it great.

The pitch for these SQLite alternatives is:

- SQLite is public domain so there's no problem with us rewriting it

- We're going to rewrite it in Rust because that's going to make it inherently better (and don't question this)

- We're going to MIT license our rewrite because there's various reasons why people would rather use MIT-licensed code than public domain code (but SQLite being public domain means we get to do all of this rewriting and re-licensing to begin with)

- Also we're going to extend SQLite to be “cloud-capable” because that's our business use-case, even though it's completely at odds with SQLite's intended use-case

- Also we're going to foster a “community” around our rewrite(-in-progress) (because people still think this is something desirable for some reason, as though a nonzero part of SQLite's greatness is that it operates entirely without having do deal with “nerd drama” that such “communities” inevitably breed)

- Also, we replaced that pesky, unsavory-to-our-sensibilities “Code of Ethics” with a bog-standard “Code of Conduct”—because, again: “community”

- But we're not going to even attempt to replicate the rigorous, arduous, and closed-source testing that goes into developing SQLite (which really makes up the bulk of its engineering effort)

- We've made some progress toward all of this, but it's nowhere near done yet

- But we're announcing it now anyway, because “hype” and “community” and “modern”

- Also, look at our microbenchmarks that show that our unfinished SQLite rewrite is already faster than SQLite (because we haven't reimplemented everything from SQLite yet) (and also we don't plan to reimplement everything from SQLite anyway)

I find it really odd that I can only seems to find criticism of any of this here on HN, and in a couple of reddit threads. It's kind of like when there was that Godot controversy awhile back, and some people made a fork and announced it, despite being identical aside from the Code of Conduct. Merely announcing a fork/rewrite of existing open-source software as a means of "building hype" and “creating a community”, while benefiting from untold man-hours of work done by others, strikes me personally as rather untoward behavior—regardless of whether the reasoning behind said fork/rewrite is ideological (Redot) or business (libSQL/“Limbo”).

Software—especially software used to create other software—should be lauded for its engineering efforts, rather than its ability to “build hype” or “build and foster online ‘community’ ‘engagement’”. If SQLite was abandonware, then it would be a somewhat different story, but SQLite is an amazing piece of software—perhaps the most widely-used on the planet—that is still being actively developed and supported. So, piggybacking on its success, without having concrete, demonstrable improvements to its functionality, comes across as… well, I can't think of another polite, applicable adjective than “untoward”.
Can it help with technical analysis as well? And screening of stocks based on technicals?
LLMs as they currently exist will never yield a true, actually-sentient AI. maybe they will get better in some ways, but it's like asking if a bird will ever fly to the moon. Something else is needed.
Costco is my new restaurant. Food is more fresh and costs way less.
McDonalds is financially quite healthy. They've never been the cheapest nor the best quality. McDonalds excels in having food at the right place at the right time and a minimal effort to transact.

If you are traveling at any random place in the US, and you are in a hurry and want something you are familiar with, McDonalds is the most likely thing you will come across first. There is a huge cognitive anchoring this has.
Its not mine, just learned about it is all
McDonald’s has also seen a major boycott because of its Israeli branch’s support for the Israeli actions in Gaza:

https://fortune.com/2024/07/30/mcdonalds-gaza-boycott-israel...

Apparently it was so bad that global McDonalds bought back all the Israeli franchises.
> Difference Engine basically implemented one algorithm in hardware

So, did Pong run on a computer?
'isit'
Good article. This is the clearest explaination I've read of how and why Ada was meaningfully innovative, and worthy of her recognition.
'Alarming': A Dangerous Diarrhea-Causing Superbug Is Spreading in Los Angeles
Embedded C usually isn't much better quality than JS, it's just less public. There's very little overlap with the relatively high quality OSS C available.
I just did the same search, and it literally said "Sources" with seven different links to the RFC and related documentation.
I am really enjoying the nano-texture. After turning down the brightness it appears like an electronic reader. One drawback, the auto adjust brightness is a bit sensitive to light coming directly at it. Sometimes the screen repeatedly dims in the morning when the sun is not causing a problem.
You can theorize a million scenarios, but clearly no one here will know what really transpired for Nvidia to hobble their consumer chips. I really don't think consumer is loss leading, GPUs for AI is a fairly recent market while Nvidia has existed churning out consumer GPUs since 90s.

But clearly, lack of competition is one thing that supports whatever rent Nvidia seeks.
It’s an established practice in journalism to describe accused who haven’t been convicted as “alleged” criminals, regardless of how damning the evidence is.

The legal basis of this is a fear of libel lawsuits. But I think even when a libel lawsuit is extremely unlikely the practice is still followed - out of an abundance of caution, out of convention, or perhaps out of principle - that is, out of deference to the presumption of innocence on a fundamental level.
> No, there would just be less 4080s for people to buy.

Sure, and more 4090s at a lower price.
It can also scan in a printed audiogram (using the camera) and apply corrections based on that.
I’d still take the bet. FIB and SEM stuff is highly specialized and miniaturizing it to be obtainable by a garage user seems unlikely even in the distant future. Either way, you still couldn’t take a 4090 and make it functional as a 6000 series. You’d destroy it in the process if it was even possible at all.
Journalists generally say "alleged", even when it's real obvious someone did the crime, in order to limit liability. They don't want to risk the off chance that the person is found not guilty and then comes after the journalists for libel.
As a kid I found it embodied quite fittingly the naive mystery of the comics, the direction, pacing, music .. everything was on point. (Something that was lost on spielberg 3d movie variant imo, too much indiana jones in spirit)
> then I would count that as "replaced 2 programmers"

Well then you can count IDEs, static typing, debuggers, version control etc. as replacing programmers too. But I don't think any of those performance enhancers have really reduced the number of programmers needed.

In fact it's a well known paradox that making a job more efficient can increase the number of people doing that job. It's called the Jevons paradox (thanks ChatGPT - probably wouldn't have been able to find that with Google!)

Making people 20% more efficient is very different to entirely replacing them.
The arrogance of comments like this is amazing.

I think it's an interesting psychological phenomenon similar to virtue signalling. Here you are signalling to the programmer in-group how good of a programmer you are. The more dismissive you are the better you look. Anyone worried about it reveals themself as a bad coder.

It's a luxury belief, and the better LLMs get the better you look by dismissing them.
That's actually not accurate. See Jevons paradox, https://en.m.wikipedia.org/wiki/Jevons_paradox. In the short term, LLMs should have the effect of making programmers more productive, which means more customers will end up demanding software that was previously uneconomic to build (this is not theoretical - e.g. I work with some non-profits who would love a comprehensive software solution, they simply can't afford it, or the risk, at present).
Have you spent much time in their dining rooms? Niche as Chris Arnade’s expertise may be, it sure seems hard-earned:

> I can answer both questions. I’ve spent over a decade sitting in McDonald’s all over the United States—I believe I’ve visited over 500 franchises. Roughly half the conversations I had for my 2019 book Dignity took place in a McDonald’s—in fact, my working title was, Everything You Want to Know About America Can Be Learned in a McDonald’s, because I sincerely believe this.
The political landscape in Germany is closing to the one we have in France. Happening in the UK too, at a slower pace, but it is happening.

I thought the "we are fed up" political trend was frenchy french... well, nope, it spans all over EU.

Here, political coalition has never been a thing (we tried after WWII, but hardcore failed) : either one party has the majority by itself, either it is the circus. If we had the same election system than in Germany and UK, the "rassemblement national" would have been in power for years.

We have a "weakest link" election system: if the biggest party is not big enough, all the other parties can team up to block it.
but not as convenient as McDonald's . fewer locations, need membership afik for food
AI models are just complex mathematical functions/software and they do not have the capability to access, modify, or control computer systems or networks. There are technical boundaries and I doubt the team at OpenAI just let the AI have full control. This gets filed under marketing fluff.
Are M1 GPUs available for data center deployment at scale? Are Google TPUs available outside of Google? Can Amazon or Microsoft or other third parties deploy them?

Anyone that wants off the shelf parts at scale is going to turn to Nvidia.
Trump was an actual campaign stop photo op... Harris didn't do a McD photo op. So not clear on your point.

Also Trump rode in a garbage truck around the same time. Was he one upping Harris? Or just trying to appeal to the working class? Probably the latter...
A 50 thousand year-old love story between humans and Neanderthals
My perspective is that if you are unable to find ways to improve your own workflows, productivity, output quality, or any other meaningful metric using the current SOTA LLM models, you should consider the possibility that it is a personal failure at least as much as you consider the possibility that it is a failure of the models.

A more tangible pitfall I see people falling into is testing LLM code generation using something like ChatGPT and not considering more involved usage of LLMs via interfaces more suited for software development. The best results I've managed to realize on our codebase have not been with ChatGPT or IDEs like Cursor, but a series of processes that iterate over our full codebase multiple times to extract various levels of resuable insights, like general development patterns, error handling patterns, RBAC-related patterns, extracting example tasks for common types of tasks based on git commit histories (i.e. adding a new API endpoint related to XYZ), common bugs or failure patterns (again by looking through git commit histories), which create a sort of library of higher-level context and reusable concepts. Feeding this into o1, and having a pre-defined "call graph" of prompts to validate the output, fix identified issues, consider past errors in similar types of commits and past executions, etc has produced some very good results for us so far. I've also found much more success with ad-hoc questions after writing a small static analyzer to trace imports, variable references->declarations, etc, to isolate the portions of the codebase to use for context rather than RAG-based searching that a lot of LLM-centric development tools seem to use. It's also worth mentioning that performance quality seems to be very much influenced by language; I thankfully primarily work with Python codebases, though I've had success using it against (smaller) Rust codebases as well.
To be honest I kind of find myself drifting away from gRPC/protobuf in my recent projects. I love the idea of an IDL for describing APIs and a great compiler/codegen (protoc) but there's just soo many idiosyncrasies baked into gRPC at this point that it often doesn't feel worth it IMO.

Been increasingly using LSP style JSON-RPC 2.0, sure it's got it's quirks and is far from the most wire/marshaling efficient approach but JSON codecs are ubiquitous and JSON-RPC is trivial to implement. In-fact I recently even wrote a stack allocated, server implementation for microcontrollers in Rust https://github.com/OpenPSG/embedded-jsonrpc.

Varlink (https://varlink.org/) is another interesting approach, there's reasons why they didn't implement the full JSON-RPC spec but their IDL is pretty interesting.
> and I would like to be able to tell it not to keep featuring photos of my ex wife years after the divorce.

You can already do that by pressing the three dots menu on a featured photo or memory and selecting the Feature this person less, with then options to not feature at all or just less.
> Is there any expectations that things will?

Seems like an odd question. The answer is obviously yes: There is a very pervasive expectation that LLM's will continue to improve, and it seems odd to suggest otherwise. There is hundreds of billions of dollars being spent on AI training and that number is increasing each year.

> Is there more untapped great quality data that LLMs can ingest?

Why wouldn't there be? AI's are currently trained on the internet but that's obviously not the only source of data.

> Will a larger model perform meaningfully better?

The answer to this, is also yes. It is well established that, all else being equal, a bigger model is better than a smaller model, assuming that the smaller model hasn't already captured all of the available information.
Wouldnt e-tag version numbers also work? Or just havkng .jsom with version metadata next to the db blob? No need to sync clocks. Just GET the small db-ver.json and compare version details?
Better recurring revenue if you need to say buy a new iPhone every year
I'll break this down simply:

- the Affordable Care Act subsidizes American health insurance with tax payer funds by covering much of the cost of insurance

- Health insurance companies are required by law to spend 85% of that revenue on healthcare

- Health insurance companies, logically, acquire providers. Thus, the 85% of their spending on healthcare is just funneled into the other companies that they own

The system is currently the worst of both worlds. We have tax payer funds going straight to for-profit entities which have become vertically integrated throughout every aspect of the American healthcare system.
I think it might be the opposite. It's not advisable to give advice to young SWEs when you might be one yourself out some.

Junior devs aren't going away. What might improve is often the gap between where a junior dev is hired and the effort and investment to get them to the real start line of adding value, before they hop ship.

AI agents will become their coding partners, that can teach and code with the Junior Dev, it will be more reliable contributions to a code base, and sooner.

By teach and code with, I mean explaining so much of the basic stuff, step by step, tirelessly, in the exact way each junior dev needs, to help them grow and advance.

This will allow SWE's to move up the ladder and work on more valuable work (understanding problems and opportunities, for example) and solve higher level problems or from a higher perspective.

Specifically the focus of Junior Devs on problems, or problems sets could give way to placing them in opportunities to be figured out and solved.

LLMs can write code today, not sure if it can manage clean changes to an entire codebase on it's own today at scale, or for many. Some folks probably have this figured out quietly for their particular use cases.
If only they had a $1.50 hamburger option!
You can filter this list to see 200+ GDPR fines assigned to sole proprietors, the smallest of small businesses, individuals that haven't even registered a separate entity for their business:

https://www.enforcementtracker.com/

They're only cataloging the (2500+) publicly known ones, most of which have a link to a news article. As an example: some guy in Croatia emailed a couple websites he thought might be interested in his marketing services, and provided a working opt-out link in his cold emails. One of them reported the email to the Italian Data Protection Authority who then put him through an international investigation and fined him 5000 euro.

"Assuming here that the reasons expressed in the aforementioned document have been fully recalled, [individual] was charged with violating articles 5, par. 1, letter a), 6, par. 1, letter a) of the Regulation and art. 130 of the Code, since the sending of promotional communications via e-mail was found to have been carried out without the consent of the interested parties. Therefore, it is believed that - based on the set of elements indicated above - the administrative sanction of payment of a sum of €5,000.00 (five thousand) equal to 0.025% of the maximum statutory sanction of €20 million should be applied."
I ran the same query, and the first source is: https://commons.wikimedia.org/wiki/Category:Places_named_aft...
I have thought that, if you're on a road trip, Costco could be pretty good. Stop there, get a rotisserie chicken, feeds 2-4 people, costs $5. (I mean, you still need a trash bag, paper plates, and a large number of napkins...) And you were going to stop for gas anyway, and they have that.
Sometimes if it's as much work to setup and keep the tech running compared to writing it, it can be worth thinking about the tradeoffs.

A person with experience knowing how to push LLMs to output the perfect little function or utility to solve a problem, and collect enough of them to get somewhere is the interesting piece.
The right way to split restaurant bills
Agreed.

Anecdotal: I helped my dad a few years ago do a lot of genealogy. He had pictures going back to the late 1800s for one branch of the family that just arrived from Ireland. Most of the men were shirtless and you could count every rib. There was very little muscle.
The label is not even vertically aligned correctly…
Precisely zero reliable evidence has been presented that ties him to the place or the hit, as of right now.

It's anything but obvious. What is obvious is that NYC law enforcement had tremendous pressure to apprehend and prosecute a suspect quickly, and that they had precisely nothing to go on before he was miraculously identified by a random person. You may also recall that there is no imagery of the assassin's face during the hit.

Of course someone who planned such a hit so carefully would keep carrying around the murder weapon for several days, across state lines, as well as a printed hardcopy of a manifesto establishing motive (he worked in IT). Very little of what the police have claimed thus far has made any logical sense.
What's the work you're pursuing?
1. TikTok isn't being banned in Romania

2. Meta has a far worse track record here.

If your argument is social media allows the subversion of free and fair elections there is no reason for TikTok to be singled out. In fact you could argue that WhatsApp groups should be banned as well.
Are you lot really this oblivious? Seriously?
> It's provably true that LLM's can generate working code.

Yeah for simple examples, especially in web dev. As soon as you step outside those bounds they make mistakes all the time.

As I said, they're still useful because roughly correct but buggy code is often quite helpful when you're programming. But there's zero chance you can just say "write me an driver for the nRF905 using Embassy and embedded-hal" and get something working. Whereas I, a human, can do that.
Another thing I want to note is; even if I get replaced by AI, I think I'd be sad for a bit. I think it'd be a fun period to try to find a "hand-focused" job. Something like a bakery or chocolatier. I honestly wouldn't mind if I could do the same satisfying work but more hands-on, rather than behind a desk all day
This would make sense if, as mentioned in the article, loot boxes were also considered problematic. Unfortunately, loot boxes in FC are 3+ even though they're linked to actual gambling addiction, whereas poker-like roguelike mechanics are 18+ even though you never lose a cent of real money (and the game doesn't teach you enough about poker to actually play poker).