For me, it's basically C++ for low-level, Python for high-level, Java for insanely large corporate codebases, JavaScript (oh boy...) for the Web. Tons of better languages are out there, but they lack the same level of support, tooling and libraries' availability.
An example to the UAE citizens that their government will protect them. Sense of citizenship is worth $20B. Plus, it's not that UAE actually lost this money. Neither did France. They may lose/delay $20B in revenue.
He did not know that he would be arrested there. The plane tried to leave Paris airspace at the last minute, but it was too late. Durov should have known that he could be arrested. Basically, arrogance and wishful thinking, complacency, believing in "democracy". Still, UAE will probably get him out.
Documented evidence where Elon says things that aren’t true seems to be a valid response to someone claiming something unlikely because Elon says it’s so.
I honestly don't understand how this is flamebait? Elon Musk constantly lies about his companies, so it is relevant to the thread, especially the post I was responding to which is very likely a lie from Musk. Is pointing out the documented fact that Elon Musk constantly lies about his companies not allowed?
It came across as a list of pre-assembled talking points, which is the kind of thing that hardened warriors on whatever $topic do, and the kind of thing that curious conversationalists don't do. We want curious conversation here. I know it sounds strange to put it this way, but: that's more important than being right. A lot more important, in fact.
It looks like this article does not mention it, but linear regression will also exhibit Double Descent phenomenon, commonly seen in deep learning. You would need to introduce some regularization, in order to see this. It would be nice to add this discussion.
Are there some papers in particular that you're referring to? Does the second descent happen after the model becomes overparameterized, like with neural nets? What kind of regularization?
[Submitted on 24 Mar 2023]
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle
Rylan Schaeffer, Mikail Khona, Zachary Robertson, Akhilan Boopathy, Kateryna Pistunova, Jason W. Rocks, Ila Rani Fiete, Oluwasanmi Koyejo
Double descent is a surprising phenomenon in machine learning, in which as the number of model parameters grows relative to the number of data, test error drops as models grow ever larger into the highly overparameterized (data undersampled) regime. This drop in test error flies against classical learning theory on overfitting and has arguably underpinned the success of large models in machine learning. This non-monotonic behavior of test loss depends on the number of data, the dimensionality of the data and the number of model parameters. Here, we briefly describe double descent, then provide an explanation of why double descent occurs in an informal and approachable manner, requiring only familiarity with linear algebra and introductory probability. We provide visual intuition using polynomial regression, then mathematically analyze double descent with ordinary linear regression and identify three interpretable factors that, when simultaneously all present, together create double descent. We demonstrate that double descent occurs on real data when using ordinary linear regression, then demonstrate that double descent does not occur when any of the three factors are ablated. We use this understanding to shed light on recent observations in nonlinear models concerning superposition and double descent. Code is publicly available
"For a few months in 2013, Allred camped out of his car while in Silicon Valley, and frequently describes this period as having been homeless. However, a deleted post on his blog titled 'Voluntarily Homeless in Silicon Valley' explains that he lived out of a car by choice."
I have a friend who is adamant that he lives out of his truck by choice, but it's hard to call it a choice when there's only one option. I wouldn't hold his feet to the fire if he later admitted he was in a rough spot (our friend group is all very clear on this situation). I had put Allred entirely out of my mind for a while, but I seem to recall his "homelessness" was characterized more by image than by practicality. Since we're being technical, it seems worth making the distinction.
I had this same debate here a few months ago, about people living out of their truck/van in Seattle, and the "choice" of it. There was more than one person that could (or would) not see the distinction. "I've seen plenty of social media and YT videos talking about how much they enjoy the experience".
Uhh, when people talk of living out of a vehicle in the context of homelessness, they're talking about people parked in the back corner of a Walmart lot with their laundry and many earthly possessions beside them, not social media creators making YouTube videos for "#vanlife".
LCDs still can not change resolution away from native max, without screen getting blurred. As I recall, LCDs started to get wide adoption about 2004 or so. It has been only 20 yrs. Why can't they make them to be able to run on resolutions other than native? CRT could do that with no problems.
