I’ve put like 1000 hours each into Stardew Valley and Rimworld. Not a single ray traced, no advanced boob physics, just good fun.

Wait, is it sitting or standing?

Where does your scale go? All I have is drawers!

My guess, without reading the article, is that they will just require input apps on the Play Store targeting Android 16 with AI features to respect some sort of allowAIInput = false flag

I’d wager side-loading and 3rd party app store apps will be ignored, but those apps will probably do it anyways to keep their Play Store releases.

Hmm, feels like it’s missing stuff. Does disc go shiny side up or down?

Reflections are a great example of this. Real, calculated, reflections are a relatively new concept in videogames, but lots of old videogames are able to replicate this effect by creating an “upside down” world, with duplicates of everything, and reflective surfaces are actually windows peering into the upside-down. Its an OK facsimile, but requires specific conditions to be met and can’t be applied broadly

Didn’t you see? This is XR, totally different.

My experience has been that certain vanity TLDs are not accepted, so if youre using a personal domain on simple login and it has a TLD like .email or .ninja, there’s a chance it’ll be rejected while temporary email with a .com TLD will skirt by.

Keep Talking And Nobody Explodes on the daydream was a next level of fun with friends. Sad it was abandoned so rudely.

You can rent (until your service decides to stop selling that content) and download a DRM-locked copy only playable in one app that’s 1/5 the bitrate. Is that not good enough for you?

What if we include a full screen ad whenever you pause. You’re not watching anyways, what’s the harm?

Oh, also, did you hear about our other content and services? We would like to remind you of all of those every time you start to watch something - we don’t consider them advertisements, just important feature updates, so you can’t remove them.

Aand… you HAVE to be connected to the internet to watch, because we made this really cool AI thing that watches literally everything you do, sends it to our servers, and sometimes happens to recognize which characters are on screen so you can access their IMDB pages through your TV while watching the movie for some reason, like that’s a normal thing people want to interrupt their movie experience to do.

6.9% when?

Yeah, except the states dumb enough to ban porn only have like 1% of the US population.

If I share profits, then how do I, a lowly CEO, keep all of the profits for myself?

No sharing in Notesnook

MKVToolNix is the right answer, BUT if you plan on sharing your Linux ISOs with the wider community you may not want to edit the original file.

Not sure what you’re watching on, but Plex lets you set a preferred audio language per-user, while Jellyfin and Kodi support external audio tracks as long as they are properly identified, so you could extract/find the English track you want and just toss it in the same folder

Of course, when you add a backdoor it’s best to assume everyone will use it sooner or later.

Its true!! I saw several really interesting documentaries about this phenomenon on PornHub

It would be amazing if it could have a significant impact on spatial and temporal accuracy of things like rain. I feel like for me the existing weather report is good enough for “it will probably rain tomorrow” but it’s really hit-or-miss when you get to hourly resolution. A good model may be able to go so far as to say “it will probably rain between 3-4pm on the east side of town tomorrow, and 2-3pm on the west side”

That’s the dream at least. With enough data and a sophisticated enough model it feels like it could be possible.

There’s a difference between the real-ish-time weather data continuously fed in to output predictions, and the decades of weather data used to build the model. The continuous feed of data is more than likely part of what Google alleges is saving significant energy.

Its the training on decades of information, and occasional updates to those trained models that take a significant amount of resources, but hopefully for relatively short bursts.

I feel this personally, I live in the hills outside of a valley metro. All weather data is forecasted off of valley sensors, but shit gets weird when you suddenly climb 2000+ ft.

The best weather services in my area are those that can factor in peoples household meters into their forecasting, but those services still aren’t perfect.

It’s not just about cutting costs, but also improving accuracy. Physical simulations factor in a dozen or so weather conditions to predict outcomes. Machine learning can track thousands of conditions, drawing connections not realized in physical models, leading to much more accurate statistical models.