Imagine a camera with only one column of pixels, so a resolution of 1x3000, for example. You point it in a fixed direction and you keep firing extremely fast. Eventually you’ve photographed everything that has passed the camera. Paste the pixels together from right to left, and you’ve got something resembling a normal photograph, but with some distortions due to the time difference between the photos. For example, if someone put their foot on the ground in front of the camera, it will be stationary between photos and appear smeared out in the final result. Since every column of pictures is made at the exact same location, you can determine that the person on the right has finished first and the person on the left last. They apparently measure this at the level of the torso (the red lines).
oktoberpaard
Exactly, so on this photo you can see exactly who finished at what position, because it’s all taken at the finish line.
Right, I see what you mean now. I misread your comment as explaining something that was already clear.
It’s by design. They photograph only one slice repeatedly at the finish and then paste them all together. That means that everything you see here was at the same location, not at the same moment in time.
A false positive is when it incorrectly determines that a human written text is written by AI. While a detection rate of 99.9% sounds impressive, it’s not very reliable if it comes with a false positive rate of 20%.
The kernel is written in C and a bit of assembly. When support for a new language is added, that’s big news and worthy of headlines. The other languages are just there for various tools and helper scripts and are not used for kernel code, so not newsworthy by any means.
I might be wrong, but I think they will probably let the OS handle the biometrics offline, which means that they won’t have access to your biometrics, they just work with cryptographic keys. Otherwise it doesn’t make sense, as apps usually don’t have direct access to the fingerprint reader. It will probably be similar to how a passkey works.
The black one is the 1x and is the tastiest of the three in my opinion. The 3x seems to be tastier than the 2x (both red), but that’s based on memory, as I haven’t tasted them side by side. We buy the 1x quite often and add some extra ingredients to it (egg, spring onions, crispy chili oil, cheese). It’s spicy, but not extremely so according to our taste, especially not with the extra ingredients.
“Our analysis shows that the two voices are similar but likely not identical,” Berisha said.
They also point out the main differences between the two voices in the paragraphs below this quote. I do believe that they hired a voice actress and that they didn’t train on SJ’s voice, or at least not entirely. However, I wouldn’t be surprised if there was big push for finding a voice similar to SJ’s voice in Her, no matter how much they deny this.
For me they only work in relatively quiet environments, or with earplugs. As soon as a car drives by it completely drowns out the sound. With music that might not be an issue, but with podcasts or calls it’s very annoying. I’ve bought earplugs especially for this, as my other earbuds have issues with wind while running, but it does feel like it’s defeating the purpose a bit. I guess turning them all the way up would also work, but that doesn’t feel healthy. Other than that I like them and the mic quality is also good according to people I’ve spoken with over the phone.
WSL 1 is a compatibility layer that lets Linux programs run on the Windows kernel by translating Linux system calls to Windows system calls, so in that sense I understand the name: it’s a Windows subsystem for Linux [compatibility]. It doesn’t use the Linux kernel at all. With WSL 2 they’re using a real Linux kernel in a virtual machine, so there the name doesn’t make much sense anymore.
The red lines on the finish line are real and the ads are projected from a small vertical projector at the other side of the track and are not visible in real life.