Pop has not received feature updates for years, because the dev team focuses on implementing Cosmic.
Given the overall progress of Linux Desktop environments, this might have led many users to switch away from Pop.
Pop has not received feature updates for years, because the dev team focuses on implementing Cosmic.
Given the overall progress of Linux Desktop environments, this might have led many users to switch away from Pop.
Interessant, dass du die Qualität nicht so gut findest. Ich fand sie bisher nämlich enorm gut und bin für meine Chinos, Shirts und Pullis fast ausschließlich auf Uniqlo umgestiegen.
Uniqlo hat viele verschiedene Basics. Auch schön dicke aus Baumwolle.
I agree with your statements. Based on my knowledge of German history as well as Kahnrmann's "Thinking, Fast and Slow" I too think that language forms reality and is strongly related to tractable actions.
However, regarding PCMR, one could certainly argue that the title is more meant like a meme. This might make it acceptable. Further, the meme-like character is in contrast to my aforementioned examples, which came from science and software engineering.
So my point is, while one should treat language seriously, the notion of what is acceptable and what not strongly depends on context. In the case of PCMR, the presence of many younger kids should make us wary of our language, because they might not understand what is meant as a joke and what not.
I'm not familiar with the history of the sub, could you elaborate a bit more please?
Thanks! I did not know that. Very neat :)
What exactly happened? The reasoning in the graphic does not tell me much. I only saw the summary which listed him as second. He seemed having finished his lap before the red flag, no?
Despite a size reduction of the cars, I cannot imagine how to save a significant amount of weight. The biggest weight contributors besides the chassis are engine and battery, right?
Not available in all countries, though :(
Do you happen to have a good source to read up on continual RL that you can recommend? I am not familiar with this use case for RL.
Depends on the use cases I guess. If any larger scale deep learning is going on, you cannot afford buying all the required GPUs anyways.
However, I found myself using my tower PC quite a lot during my Masters. Especially for Uni projects my GPU came in very handy and was much appreciated by group members. Having your own GPU was often more convenient than using the resources provided by the lab.
Also, while relying mostly on cloud resources in my last job, I would have found having a GPU available on my work machine very convenient at certain times. Very nice for EDA and playing with models during the early phase of a project.
Besides from that, IMO a good CPU and > 32GB RAM on your own machine are sufficient for EDA and related things while I would rely on cloud resources for everything else, e.g., model training and large scale analyses.
Sounds awesome! Could you please provide an exemplary shortcut?