It is not just him, but also the people he is trying to reach. Even if he gets assistance & the resources to set up an independent platform for this, he still has to get people to use it - which is a much higher bar to meet.

Most LLM chatbots don’t push back when they should. When combined with situations like these, at a large scale, even 5 percent is abysmal, let alone 55 percent.

To be similarly pedantic: Ctrl+C is a hotkey that sends the corresponding ASCII code / codepoint to signal something, it is not an ASCII code itself.

You could have the same character be sent by using Ctrl+Q (if you were to remap it), and not break compatibility with other processes while doing so: the codepoint being sent would be the same. From a technological perspective there is nothing special about the key combination Ctrl+C specifically, but altering this behavior in a terminal absolutely wreak havoc on the muscle memory of terminal users, and altering it’s behavior in a text editor on everyone else’s.

The key issue is that the request is to change behavior in one place (browser) to match that of a rare case (terminal), causing a mismatch with the frequent case (office suites, mail programs, …). The terminal is the odd one out, not the browser, and ought be the one to change the default for the reason you provide.

In practice, a terminal is a special case and not just a text input window, and current convention is that Ctrl + C aborts / cancels.

(You could of course have a duplicate hotkey, but now you are inconsistent w.r.t. other browsers, and there will be someone else who will be annoyed by the difference)

Yep. LLMs are at their core text completion engines. We found out that when performing this completion, large enough models account for context enough to perform some tasks.

For example, “The following example shows how to detect whether a point is within a triangle:”, would likely be followed by code that does exactly that. The chatbot finetuning shifts this behavior to happen in a chat context, and makes this instruction following behavior more likely to trigger.

In the end, it is a core part of the text completion that it performs. While these properties are usually beneficial (after all, the translation is also text that should adhere to grammar rules) when you have text that is at odds with itself, or chatbot-finetuned model is used, the text completion deviates from a translation.

Privacy concerns are valid when an external server needs to be queried, like if you were to use DeepL or Google Translate for this stuff, or for any LLM related muck, but they have been accounting for this already by making things work locally. For example, translations performed fully on device, and are an example of a feature I wanted.

Like many here, the entire AI browser idea doesn’t appeal to me at all, but I also struggle to come up with ‘features their users want’ if I take myself as an example. I have previously used Vivaldi, and while it is much more full featured, it doesn’t add any features that I actually end up using frequently.

I think it makes more sense if you view the country as an addict.

And it still cleans up once the ownership model indicates it can be cleaned up. That does not ensure memory is never leaked, but it is equivalent to destructors running automatically when using unique ptr or shared ptr without cycles in C++, which avoids at least a portion of possible memory leaks.

That difference is so large, they must be quoting different numbers. Something like DOJ is looking at Advertising providers or search providers alone, while Google quotes a number for percentage of all websites visited or something.

Yeah, even if it is the law, companies do tend to fall short of adhering to said law. For example, a lab that does cancer screening got hacked and pretty much messed up their entire response.

At least the EU is somewhat privacy friendly here (excluding the Google tie in) compared to whatever data sharing and privacy mess the UK has obligated people to do with sharing ID pictures or selfies.

Proving you are 18+ through zero knowledge proof (i.e. other party gets no more information than being 18+) where the proof is generated on your own device locally based on a government signed date of birth (government only issues an ID, doesn’t see what you do exactly) is probably the least privacy intrusive way to do this, barring not checking anything at all.

It is complicated. It is not technically always, but in practice is may very well be. As this page (in Dutch) notes that, unless the driver can show that ‘overmacht’ applies (they couldn’t have performed any action that would have avoided or reduced bodily harm), they are (at least in part) responsible for damages. For example, not engaging the brakes as soon as it is clear that you would hit them, would still result in them being (partially) liable for costs, even if the cyclist made an error themselves (crossing a red light).

Because the burden of proof is on the driver, it may be hard to prove that this is the case, resulting in their insurance having to pay up even if they did not do anything wrong.

Mattermost does have an Github Repository with a choice of three licenses: MIT (if using versions compiled by them), AGPLv3 (if compiled by you) or an Enterprise license. I would count that as open source.

A more general business management application like Odoo could work?

As a past customer of Gandi, they have been bought out and have been significantly increasing their prices (renewal this year would have cost me twice what I paid a couple years back) while reducing the value proposition of their offering (e-mail is no longer included…)

Note that while entering the Schengen area does not require a visa for USA citizens, you do have to get a visa waiver which is subject to limitations. See this document.

Thunderbird has RSS integrated, which could be quite neat once that synchronizes.

I think the video LegalEagle uploaded explains it quite succinctly: for the sale there was a certain split between the debtors, the debtors with the largest portion were willing to forego a portion such that the other debtors would get a larger portion if The Onion’s bid was the winning one. In effect, the other debtors would get more money out of the 1.75m than the 3.5m bid, and the debtors that ‘got less’ are the ones that offered the money in the first place.

They were removed from MAINTAINERS, which is what identifies the people responsible for maintaining a piece of code, a subsystem of Linux, not the credits, which is encoded in the git commit history.

A very similar situation to that analysed in this paper that was recently published. The quality of what is generated degrades significantly.

Although they mostly investigate replacing the data with ai generated data in each step, so I doubt the effect will be as pronounced in practice. Human writing will still be included and even curation of ai generated text by people can skew the distribution of the training data (as the process by these editors would inevitably do, as reasonable text could get through the cracks.)