A good photo can really go a long way. Back up and zoom in as much as possible to reduce perspective distortion. Try to get the camera square to the part.
Another nice trick for small parts with a flat face is a flatbed document scanner. Unlike a camera, the scanner ensures no perspective distortion. They also have a known scale (the DPI). Or, for more accuracy, you could calibrate the scale factor by scanning a ruler.
If you like OpenSCAD, you should definitely give CadQuery a try. I’ve used both, and CadQuery absolutely blows OpenSCAD out of the water.
What does the probed mesh look like? If you run multiple probe cycles, are the results consistent?
However, that’s not really any better for privacy. There’s absolutely nothing preventing someone from logging a history of the changes.
As someone who has been using Linux since the 90s and gone through many different unit systems, I like systemd way more than any of the past ones. It makes adding services dead simple, and is much smarter about handling dependencies and optimizing startup sequences.
The main complaints I’ve seen about it seem to be people that don’t understand that systemd init is a separate thing from all the other systemd stuff. If you don’t like all the other systemd things, you don’t need to install them at all.
The number of users who care about emulation is utterly insignificant compared to the hold Nvidia has on the compute market. There is a lot of stuff that either requires or is more optimized for CUDA.
Currently, these systems have no way to separate trusted and untrusted input. This leaves them vulnerable to prompt injection attacks in basically any scenario involving unvalidated user input. It’s not clear yet how that can be solved. Until it has been solved, it seriously limits how developers can use LLMs without opening the application up to exploitation.
Yup, and they are published by Microsoft. So all ChatGPT is doing here is spitting out a key commonly found in it’s training set. It’s not calculating anything.
Could be port security. Or an auto speed/duplex negotiate issue.
They also dominate compute. There’s still a lot of software that depends on CUDA.