matsemann

Norway has the same law. I get no spam calls like this from Norway.

What I do get is spam calls from abroad. Often with a spoofed Norwegian number. Why can't operators block this? I know call centers and various things need to "spoof" a number they own, and when I myself call from abroad my Norwegian number will come from outside Norway.

But why can't they attest the numbers somehow? Owner of +47 XXXXXXX is currently not abroad. So why allow someone from the other side of the world to call me pretending to come from that number? Why does the Norwegian operators allow that?

At a certain bet size it would almost be self-fulfilling, heh, as one side would be very incentivized to keep at least that url working (buying the domain + hosting it if the page were to die)

Simon's really doesn't bring anything useful to the table.

One question I'm stuck with after reading is why. Why did the agents do these things? I get them being adamant on getting internet, but why did they continue? Why hack HuggingFace?

That's an incredibly dishonest characterization of what I wrote. Please re-read the guidelines of the site, they say exactly not to do that.

> saying that you should be entitled to behave as you please because you are a paying customer

No, I'm saying my usage of the site was exactly as if I used my browser agent instead of the llm agent. It visited the category for the product I was interested it, then it visited the pages for the various items to read their specs. Exactly what I would do in my browser as well. In the end I bought one of the products. Point is that I used the site as desired. No extra calls / mass scraping, no stealing of content without them getting anything in return, no breaking of rules.

No, the first case I used their website in a way that gave them a sale, which is why they have it. Why is it a straw man case when it's reality? Don't argue in bad faith, please. Express your reasoning, like I did, don't just dismiss me because you disagree..

My experience is that your description works for a certain time, since you're knowledgeable of the codebase and can guide it. But after too many iterations with not hand-holding the llm, it quickly gets unwieldy.

I use this. Buy a domain, set up a cloud flare pages that builds an Astro page on git push, served statically for free.

I don't disagree, but there is a sliding scale here.

For instance, I wanted to buy a piece of equipment the other day from a local company for a specific usecase. I wanted to find a specific price/weight/specs ratio, and asked an llm to loop through the 20 or so items, fetch their page and calculate and present some values for each. This then led to me going and buying the one I found. So the llm was mainly just an extension of me clicking into every page and making a spreadsheet myself.

However, if it were to continuously poll, or just scrape or something with no intention of buying, I would be no better than a bot.

> Just asking these questions underscores lack of understanding how things are usually done in Django and Python in general.

No, it doesn't. It's fair to criticize the consequences of this approach to coding.

I honestly think the wikipedia article is too complicated. My own image example here as an another attempt to explain: https://imgur.com/a/5ZQIJDb

Mapping the cost of something (like an algorithm), and the time it takes (so lower is better for both). 1, 3 and 5 are all optimal in their own sense. No one is strictly better than the other, just different tradeoffs you have to choose yourself. However, you would never choose 2, because for a lower cost you could get the same result choosing 3. Same with 4, 6 and 7, they all have something that's both faster and at the same time just as cheap you could choose.

A pareto front is a bit like the classical "fast, cheap, good, choose 2". There are always tradeoffs, but if something is both slow, expensive and not better than something that's faster and cheaper, it's a bad choice, and thus not on the "pareto front".

My thesis many years ago was on multi-objective optimization using evolutionary algorithms (in my profile), and maintaining a wide pareto front was what most algorithms (like NSGA-II) were attempting. If all individuals cluster around a small area (in for instance a weight/strength tradeoff), you will quickly get stuck. So should select solutions to keep for further search along the whole front (for instance some solution that is very strong but unfortunately also very heavy). Maybe keep some of them as candidates even if worse (not part of the pareto front), just to keep that part of the search space alive and avoid local optima.

Of course, what's hard anyways when you have a good set of solutions that are pareto optimal, is to then choose between them. Especially as the dimensions (objectives) grow. In my example we can end up with many variants of strength/weight trade-offs that each are optimal, which one to choose?

I really like the ORM and the migrations, but some parts I really dislike. They're maybe not Django's fault, but how it's used most places:

* Models being passed around everywhere, queries happening everywhere. I prefer having a dedicated service/selector layer to do those things. Then convert to pydantic objects or something that's passed around further.

* Corollary, but adding stuff to querymanagers quickly goes out of control. Sure, it's nice to reuse MyModel.objects.annotate_something().annotate_something_else().... but it can quickly become unwieldy and even wrong with exploding joins. And it promotes doing queries in places they shouldn't happen.

* It's veeery easy to make spaghetti. Very easy to query across boundaries, into other apps. Fine on smaller projects, but in huge codebases it quickly makes things hard to control, especially since it's all stringly typed. If I want to modify my model, it's hard to know if someone else have done a query where they did theirmodel__some_relation__another_relation__mymodel__some_field. Blows up in production.

* For some reason it's very common in Django/python projects to have types.py, models.py, selectors.py, views.py, services.py etc. And then each of those end up with lots of unrelated things in the same python file, while related stuff is spread over many files. Django apps doesn't really solve this cleanly either.

Think it depends on usage? Taking October 1st and 20th, and you want to know how many days passed, what's the right answer? If it's days lived, you would want the answer to not be 20, as some of those days didn't happen. But in some other context (perhaps something transitioning to the calendar earlier), they did?

Same, at least for smaller projects where I want some kinds of interactivity, but also a good static rendered page first and just the ease of writing, Astro+preact has been very nice.

Which straw man are you arguing against?

I also enjoy reading about how the colleagues and him genuinely like each other. So often on US forums I read a sentiment along the lines of "shut up and just do your work", but since I spend 8 hours with these people each day I prefer us to be as close to friends as possible.

As a Norwegian working for a company that expanded into Germany, I also was a bit surprised about the author claiming Germany to have a flat structure. I found it very hierarchical compared to what I'm used to. Like, setting up a new business it's very all-hands-on-deck until established, but had people refuse to do stuff "beneath their role" or outside their responsibility, or to do anything unless explicitly ordered by their direct manager when asked by someone else.

Nothing wrong in that, really, just a bit of a culture shock when you're used to something working a certain way. It was on us to adjust.

Before, only the senior cobol programmers at the company understood and knew the codebase.

Now, no one does.

I can see the allure of moving away from a legacy cobol system. But an AI rewrite doesn't actually solve any of the issues with having a legacy cobol codebase. You just have a new system no one knows or understands.

What does it mean for building software? These games cannot become fun. There is no way to prompt it fun, and any change you try to prompt it to make will inevitably blow up something else. The code is a mess and impossible to build upon.

I'm pretty tired of the "Y made this game in Z tokens" all over the internet last week. They look impressive, and it's cool that it's even possible, but they're useless as games. None of them are any fun. They're like the most boring variant of basic controllers you can imagine. None have any cool mechanics. None have any tweaks made from hours and hours of testing. All have the same cel-shader.

Not the same. And it's not like the same scams don't exist for crypto. Even worse, many of them are automated. One bad npm install could swipe my crypto, but probably not my bank account.

Law isn't code. Intention and context matters. You don't need a precise specification to mandate something. https://en.wikipedia.org/wiki/I_know_it_when_I_see_it

In Norway ads already must specify if a person in it has been digitally altered (changed shape, smoothed skin etc). Quite funny with international ads getting these banners plastered over their face. Random example: https://imgur.com/a/t8zT37o (rules for size and contrast)

Here are the rules: https://www.forbrukertilsynet.no/vi-jobber-med/merking-av-re... Quite level headed and easy to follow. So no, editing contrast or whatever people think they're clever to point out doesn't count.

> This is how most of Simon Tatham’s puzzles work, and that works well.

They btw also have a feature that swaps main and secondary action when toggled, which could work here.

Almost two decades ago I used a software called Rasterbator to dither an image into dots, blowing it up to multiple A4 pages one could then decorate a whole wall with. Up close it would just be circles of various sizes, but from a distance the image would show up. Super cool. Used it to decorate a wall in my dorm with a picture of the family dog.

Edit: found it. One picture taken from up close. Other pictures the whole image when laid out over multiple pages in the software https://imgur.com/a/OeaIWuY

Yeah, her enthusiasm is contagious.

It's factually incorrect that gopro hasn't kept up with image quality. One independent comparison I saw for instance put the gp13 in front of the others in most situations except low light. So if anything it's contested who's better/worse, far far from the statement in those videos.

It's factually correct and widely known that lots of tech "reviewers" get paid by the competition to shill products, was a whole scandal even with how Insta360 was caught telling reviewers not to mention their sponsorship. The contracts also often forbid them do do direct comparisons. Also funny how there will be a hundred identical reviews, as they all got the same script.

So, my statement is true. If you've watched a couple of videoes telling you to buy dji/insta360, it's very very likely you've been lied to.

So, ball is in your court.

Agree. Gopro recently released a DaVinci plugin for 360 videoes, which is great. But I often would like something in between the advanced DaVinci and the simple mobile editing. After the release of Max2, the Quik app got a big overhaul and is quite capable now. But it's still mobile, and Gopro Player (for desktop) is then now even further behind on capabilities. Same issue with Insta360 (both mobile and desktop, never tried Dji's apps)

A gopro isn't worse than the competition, nor at a premium.

What makes gopro the standard in proper productions (and science etc) is that they're so hackable with the gopro labs software. With that, all the other cameras are toys in comparison for professional usage.

> many YouTubers suggesting outright against GoPro since they haven't kept up with image quality.

Fyi: This is a lie, the youtubers are paid to tell you this.