By mistake. Thanks for notifying me.

To nitpick for nitpicking’s sake: You can make Ctrl+Click work in JS.

*compliment

The madman theory is a political theory commonly associated with the foreign policy of U.S. president Richard Nixon and his administration, who tried to make the leaders of hostile communist bloc countries think Nixon was irrational and volatile so that they would avoid provoking the U.S. in fear of an unpredictable response.

https://en.wikipedia.org/wiki/Madman_theory

What was particularly binary about the old mascot?

Free Speech, baybeee.

And yes, spending money counts as speaking.

I’ve made up my mind. Don’t confuse me with facts!

They’re ’Muricans. You gotta give them some slack. Thinking doesn’t come naturally to them.

I don’t know who is password, or why is password, or when is password, but I do know where is password, and it’s out there!

Jesus, Buddah, Spongebob! I don’t have time to be picky!

Suppose the average person p₀ has n acquaintances. Then a naive approach would say that each of p₀’s acquaintances (call one of them p₁) also has n acquaintances, leading p₀ with n² acquaintances of the second degree.

However, in a social network, many of p₁’s acquaintances are shared between p₀ and p₁. Let’s say that r⋅n (1/n≤r≤1) of p₁’s acquaintances are actually first-order acquaintances of p₀. The lower limit for r is 1/n because naturally one of p₁’s acquaintances is p₀ themselves.

This gives us n⋅(1−p)⋅n = n²⋅(1−p) as the number of second-degree acquaintances, if my math is mathing. Increase n for more extraverted people in the network, and increase p for more closely-knit networks.

To model the headline X % know someone who knows, we solve 1 / [n²⋅(1−p)] ≥ x where x is X% expressed as a fraction. Plugging in n=100 and p = 1/10 (I pulled these numbers out of my ass) and X=20% we get 1 / [100² ⋅ (1−.1))] = 1 / [ 10^4 ⋅ 0.9 ] = 1 / 900; again, if my math is mathing.

So this headline is true if about 1 in 900 people are in a relationship with AI.

I wonder how many AI-relationships it actually takes to get 20% of a network to know one of them.

I think I would’ve no—

Oh my!

The browser can never know what information is needed for a certain use case. So it needs to be permissive in order to not break valid uses.

For instance, your list does not include the things a user clicks on the website. But that’s exactly the info I needed to log recently. A user was complaining that dropdowns would close automatically. We quickly reached the assumption that something was sending two click events. In order to prove that, I started logging the users’ clicks. If there were two in the same millisecond, then it’s definitely not a bug but a hardware (or driver or OS or whatever) issue.

In this case the developer hasn’t designed this with the user in mind. Their rock is clearly too small for the user to sit on comfortably. Therefore it’s the dev’s fault.

On the contrary, websites are incredibly sandboxed. It’s damn near impossible to find out anything about the computer. Off the top of my head: Want to know where the file lives that the user just picked? Sure, it’s C:\fakepath\filename. Wanna check the color of a link to see if the user has visited the site before? No need to check. The answer will be ‘false’. Always.

First comment from the link:

Every time you open LinkedIn in a Chrome-based browser, LinkedIn’s JavaScript executes a silent scan of your installed browser extensions. The scan probes for thousands of specific extensions by ID, collects the results, encrypts them, and transmits them to LinkedIn’s servers.

That is very different from “searches their computer for installed software”

Yeah, I thought that, too. But to be fair, I can’t think of any missing feature.

If you have htop installed, run it in a terminal and click, for instance, the column headers.