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The “hard enough” tasks are all behind IP walls. If it’s a “hard enough” that generally means it’s a commercial problem likely involving disparate workflows and requiring a real human who probably isn’t a) inclined and/or b) permitted, to publish the task. The incentives are aligned to capture all value from solving that task as long as possible and only then publish.

I solve plenty of hard problems as a hobby

I've also used em-dashes since before chatgpt but not on HN -- because a double dash is easier to type. However in my notes app they're everywhere, because Mac autoconverts double dashes to em-dashes.

While directionally correct, the article spends a lot of time glorifying jquery and not enough on what a horrible, no good, unoptimized mess of a framework jquery was, and by extension what kinds of websites were built back then. I remember those times well. The reason to use React isn't because it was new, far from it. It was because it won vs. Ember, Angular, et. al. in 2014-2015? as the best abstraction because it was easiest to reason about. It still wasn't great. In fact, still isn't great. But it's the best blend of many leaky abstractions we use to code against the browser apis.

jquery was an unoptimised mess? it's like 30k minimised and just bridged a bunch of functionality that browsers lacked as well as providing a generic api that let you (often) ignore per-browser implementation and testing of your code

there's no reason to blame it for the types of websites being made either, it doesn't really provide enough functionality to influence the type of site you use it on


Since when did we start using file size as a measure of efficiency or optimization?

Off the top of my head: $() CSS parsing and DOM traversal was way slower than querySelector or getElementById, both of which predate jquery by years. Every $('.my-class') created wrapped objects with overhead. Something like $('#myButton').click(fn) involved creating an intermediate object just to attach an event listener you could’ve done natively. The deeper the method chaining got the worse the performance penalty, and devs rarely cached the selectors even in tight loops. It was the PHP of Javascript, which is really saying something.

By the early-2010s most of the library was dead weight since everyone started shipping polyfills but people kept plopping down jquery-calendar like it was 2006.

(I say this as someone who has fond memories of using Jquery in 2007 to win a national competition in high school, after which I became a regular contributor for years)


> $() CSS parsing and DOM traversal was way slower than querySelector or getElementById, both of which predate jquery by years.

You have that backwards – jQuery predates querySelector by years.

The reason why getElementById is fast is because it’s a simple key lookup.


Both querySelector and querySelectorAll came well after jquery. I remember it being a big deal when browsers added support for them.

> By the early-2010s most of the library was dead weight

absolutely correct this is because a lot of the shit jquery did was good and people built it into the browser because of that

putting jquery into a site now would be insane but at the time it pushed forward the web by quite a leap


3 counts of “jquery” in the text. once again, which one of them glorifies it?


Go back far enough and everything was stolen from someone


thats so wrong


ChatGPT does not offer a clear indication that it is blatantly illegal, though the amount of legal risk is high enough that it might as well be.


ChatGPT isn't even a search engine, let alone a lawyer.


Electricians in data-center states are eating; elsewhere they are scraping by due to macro-economics.


On chrome iOS I’m physically unable to press the three checkboxes on the terms which means I can’t try your app. They appear to be overlapped by the terms themselves and thus never received click events.


Yeah, this only appears to work on desktops with a res of 4K or greater, which is… not ideal for a social network?


iOS safari same issue. can’t get passed the terms


Whenever some group is said to have made/fined 1M out of their likely billions in revenue, someone will chime and say “that’s nothing”. But From a “department P&L perspective” yes, it is a lot of money!

Think about the crime families as making e.g. 50% money from construction corruption, 40% from drug sales, 5% from extortion… someone has to run the other smaller departments and that is a lot of money for that “Dept Head”. Also from the FBIs perspective they want to unravel conspiracies, often by yanking on one piece of yarn like this one.


Could this be used to train a text -> audio model? I'm thinking of an architecture that uses RVQ. Would RVQ still be necessary?


I believe DDN is capable of handling TTS (text-to-speech) tasks, because with the text condition, the generation space is significantly reduced.

And it's recommended to combine it with an autoregressive model (GPT) for more powerful modeling capabilities.


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