“It’s popular so it must be good/true” is not a compelling argument. I certainly wouldn’t take it on faith just because it has remained largely unquestioned by marketers.

The closest research I’m familiar with showed the opposite, but it was specifically related to the real estate market so I wouldn’t assume it applies broadly to, say, groceries or consumer goods. I couldn’t find anything supporting this idea from a quick search of papers. Again, if there’s supporting research on this (particularly recent research), I would really like to see it.

If there is any research from the last 50 years suggesting this actually works, I’d love to see it.

Wait, isn’t it the other way around? You should arrive in NY earlier than you left London, since NY is 5 hours behind London. So if you leave at 8:30 and arrive 1.5 hours later, it should only be 5AM when you arrive.

You might need a third breakfast before your elevenses in that case.

Jerboa is solid, but it’s not feature-rich. Not great for media browsing. It’s still my main client since I use Lemmy mostly for text, not images or videos.

Eternity and Voyager are worth looking at, too.

Interesting read, thanks! I’ll finish it later, but already this bit is quite interesting:

Without access to gender, the ML algorithm over-predicts women to default compared to their true default rate, while the rate for men is accurate. Adding gender to the ML algorithm corrects for this and the gap in prediction accuracy for men and women who default diminishes.

We find that the MTEs are biased, signif-icantly favoring White-associated names in 85.1% of casesand female-associated names in only 11.1% of case

If you’re planning to use LLMs for anything along these lines, you should filter out irrelevant details like names before any evaluation step. Honestly, humans should do the same, but it’s impractical. This is, ironically, something LLMs are very well suited for.

Of course, that doesn’t mean off-the-shelf tools are actually doing that, and there are other potential issues as well, such as biases around cities, schools, or any non-personal info on a resume that might correlate with race/gender/etc.

I think there’s great potential for LLMs to reduce bias compared to humans, but half-assed implementations are currently the norm, so be careful.

After all these years, I’m still a little confused about what Forbes is. It used to be a legitimate, even respected magazine. Now it’s a blog site full of self-important randos who escaped from their cages on LinkedIn.

There’s some sort of approval process, but it seems like its primary purpose is to inflate egos.

It was an SEO hellhole from the start, so this isn’t surprising.

Do Forbes next!

Better links to the community:

!taneggs@lemmy.ca

/c/taneggs@lemmy.ca

I claim ownership of the microorganisms in and on my body. I am not merely human; I am a glorious amalgamation of trillions of distinct beings, working in harmony to bring you shitposts!

simply logging out or using an alt account

It is increasingly difficult to use X without an account. Not sure what the signup process is like nowadays. IIRC it used to require phone number verification in the Twitter days, but perhaps Musk relaxed the requirements in order to better pad the usage stats with spambots?

Yep. If it uses a cloud service, they’re probably going to squeeze you, pull a bait-and-switch, or go out of business. The only exceptions that spring to mind are services with significant monetization in the corporate space, like Dropbox. And I’m not really confident that Dropbox’s free tier will remain viable for long, either.

Even non-cloud-based apps are risky nowadays because apps don’t remain compatible with mobile OSes for very long. They require more frequent updates than freeware/shareware generally did back in the 90s. I remember some freeware apps that I used for 10 years straight, across several major OS versions, starting in the 90s. That just doesn’t happen anymore. I’ve been using Android for over 10 years and I don’t think there’s a single app I used back then that would still work.

Single-purchase apps are basically dead, at least on mobile platforms. Closed-source freeware is dead, too. If it’s open-source, if push comes to shove someone can always pick up the torch and update it. It’s very rare for an open-source project to be completely abandoned without there at least being a viable open-source alternative available.

At this point, I don’t even look at Google Play. It’s F-Droid or bust.

That is probably true for podcasts on exclusive platforms like Spotify, but those are few and far between. Even with those, I don’t think Spotify is delivering customized audio files to each user.

It’s more like with broadcast TV, where they have general demographic information that they use to attract advertisers.

The general case is a plain ol’ RSS feed accessed by any arbitrary client. There’s not much data to be tracked there. And there’s not a whole lot you can do with an IP address without introducing highly-visible problems. You can infer the general geographic location of your listeners, but that’s about it. If you try to do personal tracking via IP address, it’s going to be messy. Cell phones don’t typically have persistent unique IPs, and even most laptop users are going to be running on a shared external IP (e.g. at a college campus, business, or any ISP that does not provide users with a dedicated IP). And again, they’re not customizing audio files per user. It’s a mostly static medium.

Podcasts, by their very nature, do not use any kind of tracking whatsoever (well, besides IP address regions, anyway).

Absolutely no reason for a browser developer to get in on this besides shameless profiteering.

That’s a problem for site operators, not for browser developers.

I don’t believe a web browser should be designed specifically for one business model, period.

There are plenty of free sites. Truly free, with no ads.

There are plenty of paid sites, supported by subscribers.

There are plenty of sites funded by educational institutions, nonprofits, or similar.

There used to be plenty of sites that were supported by non-invasive ads.

I don’t give a damn if everyone uses Facebook and Google. That doesn’t mean we need to cater to their business model at the technical level.

I’m certain that if someone did collect data from the Fediverse; it would become a hot topic

I’d assume bad actors (or at least chaotic neutral actors) are slurping up the entire fediverse already. It is trivial to do, and nobody would know.

I mean, the whole point is that anyone can spin up a server and federate with others. I could start my own server, which would by default federate with almost all other servers. That means I wouldn’t even need to write a scraper. All that data would be sent straight to my server. All I need is access to my own database at that point. With Lemmy, I’d even get users’ upvote/downvote history, which is not visible in any clients AFAIK. The only barrier would be to subscribe to communities on different servers to kickstart federation.

As long as you don’t run obvious spam/bot accounts, nobody would block your instance.

Alternatively, if you want to write a scraper, that’s also pretty easy. Most servers are publicly accessible. Every community has an RSS feed. You don’t even need an account in general. Again, the whole point is to be open and accessible, in contrast to closed-off data-misers like Facebook, Reddit, and X.

The fediverse is friendly to users, with very little regard for what those users might do. I believe this is the correct philosophy, but I won’t pretend that it doesn’t leave us open to bad behavior.

This is a FAQ for end users, about a feature in software running on end users’ computers.

It is absolutely doublespeak to call it “local”. Are we supposed to invent an entirely new term now to distinguish between remote and local? Please do not accept this usage. It will make meaningful communication much harder.

Edit: I mean seriously, by this token OpenAI, Google, Facebook, etc. could call their servers “locally hosted”. It is an utterly meaningless term if you accept this usage.

If they had said “locally hosted in our datacenter”

Then that would also be an oxymoron.

Local is the opposite of remote. This is a remote server. Remote servers are not local. This is not a matter of interpretation.

Why does local mean local? I’m not sure I understand your question.