I also wanted to mention the Noon Universe, but I have to point out that two of the most famous books of the series(Трудно быть богом - Hard to Be a God[0]; Обитаемый остров - The Inhabited Island[1]), which are also my favorite books of the series, are also sort of set in a dystopian world. They had to sneak some dystopian worlds into the utopian universe to make it more interesting.
I'd say that everything post Hard to Be a God had either a streak of disillusionment or something like anxiety over, idk, incomprehensability of the universe and progress, but early works were pretty uplifitng.
"Noon 22nd Century" was very optimistic and inspiring, I really liked it as a kid and dreamt of becoming like the scientists in these stories. Even something like "Far Rainbow" had a grim plot but an uplifting sentiment regarding the nature of human spirit so to say? The tragedy happened but people faced it with strength and honor, so to speak.
The pervasive culture in the west seems to elevate pessimism as intellectual, while optimism is stupid or naive. This bias is interesting considering how much lives have improved by many important quality of life metrics in the last 150 years, partly due to technological progress, which has enabled social progress as well. Yet most people systematically mis-predict a lot of the quality of life metrics toward whatever side is negative (the book Factfulness makes a good case for multiple results of this kind). In high school, people read Brave New World, and it seems the thinking gets stuck there. It is often a signal of education to reference these books in conversation, and you see it. Does our collective thinking get stuck at the level of an emo high-schooler?
Along the same lines, most current western sci-fi I am aware of (mostly mainstream) is dystopian. Black mirror the show is a good example, also considered intellectual by many. I feel this tendency is even stronger in Europe than in the US, at least when I visit.
In contrast, China is somehow more optimistic. Consider AI right now. Some recent poll shows Chinese people are far more optimistic or positive about AI than western people, an interesting perspective considering their own government has made computer vision surveillance and face recognition far more widespread than it is in the west.
Do these kinds of popular sentiment matter for our collective decision making? are they a needed precaution to ensure things keep getting better? or do they create self-defeating collective behaviors? wdyt.
> Does our collective thinking get stuck at the level of an emo high-schooler?
Our society has come to equate contrarian thought with independent thought, but the aren't the same thing. Worse we've simultaneously stopped training young minds to think properly.
Telling someone to think for themselves without first teaching them HOW to do that, doesn't just halt progress it puts it into retreat.
We need to start teaching young people to trust those who know more than they do, and how to tell who those people are. Further, we should teach them how to reason before we admonish them to do it for themselves.
Until we manage those two things we will be a society that distrusts everything we can't understand, and understands very little.
The video was interesting. Seems like a nice way to start a shopping search if you have a picture with something you want where the look matters. Eg, cars, furniture. etc.
Not directly an answer, but similar what if thinking got me wondering: wouldn't it be cool to be able to use postgres much like how you use sqlite with python? I implemented this idea as a pip-installable python package, https://github.com/orm011/pgserver, and your feedback would be great :) I use it for my projects.
I have not compared it.
Have you had issues in this front?
If you are asking in human terms, its instantaneous to start, it simply creates a few files etc and starts a process. If you were using Sqlite, there is no extra associated process. But the processes are simply waiting for your input, so normally this is not really extra work.
In benchmark terms, the way I'm using it startup time is not a huge issue, instead being able to use postgres is helpful (has extensions and you know you can eventually move to a hosted postgres if you want)
If startup really matters, the startup can be amortized (if multiple processes want to access the same file, they get a handle to the same already started process, so only the first one would have waited for startup).
In terms of ongoing resource consumption, I can easily have a bunch of separate servers running for different files (it depends on your workload how much work will happen behind the scenes.) I'm not sure how much extra work postgres needs to do vs sqlite beyond what is kind of inherent for a workload (eg index creation, saving a bunch of data etc).
Hm, not exhaustive but I think these are potentially useful to you:
The deeplearning.ai math basics for deep learning, seems self-contained.
MiniTorch repo (implement your own tiny torch) seems also helpful to understand what goes on during training.
MinGPT repo (to understand a basic version of GPT model structure)
Dive into deep learning (textbook avail online, more focused on practical DL)
I have been waiting for weeks, and am still waiting, to get access to Llama2 (released a month+ ago), and access to this model goes through the same form, so I'm not very hopeful. Are you getting it from other methods?
Does anyone know of good tools to practice tone-listening and recognition for cantonese? or tools for drilling jyutping more generally,
I've used https://chaaklau.github.io/cantorocks/, but I would like to also try others, as the audio is not great sometimes and I'd like to listen to different voices.
When studying Mandarin I found that getting the phonetics right early on really helped me, it can be done in a relatively short time and its hugely motivating.
If you have basic Mandarin knowledge, you could try Duolingo's Cantonese course for Mandarin speakers. I think it is helpful to get familiar with how words are pronounced and what expressions people use in vernacular Cantonese so far. As with the Mandarin course, there is little explanation, you kind of have to complement it eg with some drilling for tones.
I really like this idea, though I haven't tried it yet.
Spotify has lyrics for many songs, but for characters the first hurdle is you cannot really sing along even with the lyrics unless you know them.
Is there some easy way one change the font used by Spotify to be this font somehow?
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