Yes. The article only shows Apple-owned apps: TextEdit and Calculator. And it shows the various border radiuses for different elements straight from XCode's UI builder.
And 1967 was 58 years ago, which was when the first deep neural network was trained with stochastic gradient descent. Yet, DNNs didn't take off until the 2010s when the hardware became powerful enough and data became plenty enough to successfully train and utilize them such that they were practical.
> you cannot use them to solve real world problems
Doesn't waymo and other self-driving systems use reinforcement learning? I thought it was used in robotics as well (i.e., bipedal, quadrupedal movement).
I just want to give a hearty thank you for pixi. It's been an absolute godsend for us. I can't express how much of a headache it was to deal with conda environments with student coursework and research projects in ML, especially when they leave and another student builds upon their work. There was no telling if the environment.yml in a student's repo was actually up to date or not, and most often didn't include actual version constraints for dependencies. We also provide an HPC cluster for students, which brings along its own set of headaches.
Now, I just give students a pixi.toml and pixi.lock, and a few commands in the README to get them started. It'll even prevent students from running their projects, adding packages, or installing environments when working on our cluster unless they're on a node with GPUs. My inbox used to be flooded with questions from students asking why packages weren't installing or why their code was failing with errors about CUDA, and more often than not, it was because they didn't allocate any GPUs to their HPC job.
And, as an added bonus, it lets me install tools that I use often with the global install command without needing to inundate our HPC IT group with requests.
> The main thing conda doesn't seem to have which uv has is all the "project management" stuff.
Pixi[1] is an alternative conda package manager (as in it still uses conda repositories; conda-forge by default) that bridges this gap. It even uses uv for PyPI packages if you can't find what you need in conda repositories.
I've been using Plex (connecting via Tailscale) with their Plexamp music player.
It's been working pretty well, but I might have to give this a try to compare. Although, it's not clear from the GitHub README or the Apple App Store listing if the mobile app allows you to download music for offline listening.
> And calling teams low in the desired section is such an odd assessment.
I said it ranks low in "admired" (i.e., those who use it and want to continue using it). Less than 50% of those using it want to continue using it despite it being the most "popular" by a significant percentage. If everyone had their choice, Teams would drop heavily in popularity.
Regardless, it was just an example of how "popularity" doesn't mean anything because most people don't have a choice in their day jobs.
> What is the primary operating system in which you work?
It doesn't ask anything about preference and I wager most people don't have a say in OS for their jobs. Same reason that Microsoft Teams is the most "popular" synchronous tool, yet so low in the "admired" section.
That's not to say you're wrong, just that the data you linked to does not "back it up".
> Nyxt differs fundamentally in its philosophy- rather than exposing a set of parameters for customization, Nyxt allows you to customize all functionality. Every single class, method, and function is overwritable and reconfigurable. You'll find that you are able to engineer Nyxt's behavior to suit almost any workflow.
Actually, it's probably the opposite. The searches are more than likely to make sure you're not bringing anything in that could exfiltrate data like a camera, usb drive, or even pen and paper.
I work in a similar, secure environment. We are not allowed to bring any items in other than our persons, smart card that we scan on enter/exit, and the clothes on our back. We have to leave the facility to use the bathroom, eat, drink, etc.
Another good Microsoft monospace font: Cascadia. Something about it just makes it super legible for me when coding in it, plus it has nerd fonts built in without needing to be patched.
Could you elaborate? As far as I understand, if you treat it like Python (e.g. use defs and stick with the copy-on-modification default), you'll still see performance improvements without even thinking about memory.
You may be limited for your thesis. My grad program required us to conform to either a Word or LaTeX template, of which I found the latter actually much easier to deal with. I just kept my chapters in separate files that are inputted into the template.
If you're asking for other assignments, I'd actually recommend Quarto [1]. It's basically a streamlined version of your current workflow. The other benefit is that it can convert your markdown to Typst if you decide to switch over in the future.