You were anything but “randomly born in your country”. You are most likely the latest branch in a sedentary tree rooted both geographically and culturally for centuries, and without that tree you certainly wouldn’t exist. This doesn’t mean you shouldn’t travel, perhaps plant a new tree, but the idea that you were born randomly is obviously false.
From your point of view you were born randomly in a universe in a random country to random parents. Yes. There is a story once you were born. But as far you are concerned you could have been born as anything in any Universe. There would always be a story backing it up.
But you are not a tabula rasa. You are made of a genetic code inherited from your parents, which strongly determines how you look and your body can do. You were clothed, fed, raised, cultured, taught by your family and others in their geographic area.
The self has a heritage even if the self refuses to accept it. You are your parents' child and not someone else, for the same reason you are also a human, a hominid, a mammal, not a fish or a tree.
Perhaps you are right, Neo. Perhaps we are in the Matrix. But you lack evidence for your position. How could you tell if you're a transcendental spirit, and not a brain in a jar suffering from last Thursdayism?
I have plenty of evidence that we're bags of chemicals wandering around a rock in space, and our consciousness is the results of electical signals passing through our synapses. If you wish to reduce the majesty of nature to "unknowable", you reduce your own position to unknowable too. If you're fine with that, I'm fine too, but I still like my position better than yours.
The only thing you know is you are aware. Rest everything mere appearances in the awareness. And that includes all the what ifs, the idea that you have evidence and you are sure.
Are you saying CPUs are alive as in how humans and birds are alive and have conscious experiences? What is that experience? Is it the body? Or something else ?
The problem here is that you're defined by the history of environments you've been in, which provides a reason to stay in them (and a reason why the phenomenon of culture shock exists). I could not randomly have been, to take a random person, Carmen Miranda, because I am not her to any extent, so for me to "be" her, in some alternate reality, wouldn't mean anything.
I grew up near a border; a border which changed a lot throughout history. Not to mention that the country I was born into didn't exist as such even a few generations ago. So yeah, I'd go with “randomly born in your country”.
You could have said "two people decided to have sex, you were not born randomly", and it would have had the same relevancy. The fact is that you had 0 input on where you will be born, so from your perspective, it was random. Everything else is just trying to play up a belief, religion, or some kind of woo as a ground truth.
NixOS really makes Ubuntu (and all the other distros) feel old though. I mean I _love_ Ubuntu, and I’ve used it faithfully for 12 years, but once you get used to Nix, and granted, it’s tough, but it’s just an absolute revelation in terms of confidence in one’s operating system, freedom to use so much more software, and not be worried about even very advanced configs. I could never go back.
Interchangeable cookie-cutter coder availability is Finance's number one priority. Definitely no room for critical pricers or infra written in languages that they can't frictionlessly slot someone else into as people leave. So python.
Also, arguably, Julia, while fantastic, just didn't do that much that Python didn't do already. It's main argument outside of tidier ergonomics was basically "speed without leaving Julia" but with Numpy and Pandas being essentially stdlib, that just wasn't a very powerful argument. Julia was basically too incremental to be worth switching to. It seems to have found its niche elsewhere though with the optimization people?
One of the main things I like about Julia is that all the libraries are just built on their core Array type. In Python, there’s torch tensors, numpy arrays, and I think Jax has their own array type too. Also, Julia has a really beautiful distributed computing paradigm, whereas python needs to use libraries like Ray, which have their own quirks and documentation and community
General scientific computing is pretty good across the Julia ecosystem, from optimization, to ODE and now PDE solver libraries, to various statistics and inference packages, etc. It lacks the deep NN tooling or breadth of ML libraries of Python, and nothing matches R for breadth of stats libraries, but for most other scientific computing it is really great at this point.
I am by no means an expert, but I used Flux.jl for a convolutional neural net in electromagnetics for my latest paper and it was such a breath of fresh air compared to Python and PyTorch. (I'm an EE and not great at programming, so I found a lot of frustration in PyTorch). Even though the Keras library in Python is pretty nice, even then I got myself into some odd pickles when trying to do some custom layers which used FFT processing as it relates to gradient computation. Things are much smoother in Julia, and that doesn't even count how much easier the Plots library is! I'm ashamed to admit that I have no idea how to manipulate the figures and axes in Matplotlib without extensive googling.
Scientific/Numeric/Data-Python is essentially a DSL around C-API which creates friction (try for example to map a custom function over a Pandas column). Whereas in Julia, it's just Julia. It's liberating to just extend and use a library written in the same language. It leads to surprising synergies.
numpy is only fast if the computation does not escape it. There are plenty of cases where execution ping-pongs (if that's a verb) between python and the C(++) wrapper numpy actually is. Then everything becomes quite slow.
Anyway, I see data scientists and statisticians (at least 100% of the ones I know) completely ignoring Julia, just because they only have been exposed to Python and R in their education. The quality of the programming language/ecosystem seems to be irrelevant.
In t-SNE, the distances in the feature vector space are preserved in the projected space. IIRC, these distances serve as boundary conditions to a stochastic diffusion problem. The actual positions and the orientation are allowed to be free variables.
yeah but hang on. Why are these charts going down? Is it because questions and answers are actively being _removed_?
Or is this a first-derivative of [answer/question] count ie the rate of change? In which case a) this should be clearly stated ("questions added per period x"), and also, it wouldn't be surprising that the charts go down because the knowledge is already there and so fewer questions/answers are needed, even without AI.
While there is indeed a big decline post-GPT et al, the decline started a lot earlier than general availability of AI.
A constrained environment forces developers to distill to the essence of the problem, thereby possibly understanding it better. It's the old "simple can be harder than complex" attributed to Steve Jobs.
The whole idea of the yield curve is that you (generally) get compensated for that risk with higher rates. That is why (outside of crises) the yield curve is upward sloping. It follows that if you buy shorter dated T-bills or bonds, the liquidation loss risk you mention is low, and you’ll still usually make out better than with the bank because you’re not paying any middleman.
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