Deep Learning Foundations to Stable Diffusion
21–30 of 121 posts
Re: Deep Learning Foundations to Stable Diffusion
#22This is cool, but I have a fundamental question. Why learn machine learning when all the machines will learn how to create and control themselves and powerful elites will offload the burden of governments to control us? Or we race ourselves to fulfill the last jobs on earth? Is this progress for humanity or enslavement and the end of our species? I am serious. This question is honest. Maybe my IQ is too low to unders…
You've guessed it right, AGI is a long way off (if ever) but you're not exactly a general intelligence either - yes, you are fucked.
It's not like I could tell Chat GPT "I want a fully featured browser" or "I want a machine learning framework" and it'll just come up with a working Chrome or PyTorch. But those are way, way, way outside your abilities they might as well be magic as far as you're concerned.
Re: Deep Learning Foundations to Stable Diffusion
#23This is cool, but I have a fundamental question. Why learn machine learning when all the machines will learn how to create and control themselves and powerful elites will offload the burden of governments to control us? Or we race ourselves to fulfill the last jobs on earth? Is this progress for humanity or enslavement and the end of our species? I am serious. This question is honest. Maybe my IQ is too low to unders…
I think it's all to play for, the future that we create using AI technologies. If we don't engage though as citizens then it probably is game over, yes.
The folks at OpenAI like Sam Altman are certainly very aware of the potential hazards of LLMs and advanced AI generally, and Elon Musk famously is. The fact is though, these technologies exist and we can't bury our heads in the sand. There is also an enormous upside if we, as a society, marshal the technology and regulate it properly.
I think a degree of nervousness is an appropriate reaction, I'm a little nervous. I'm also excited about the potential. I also see it as a somewhat inevitable evolution of computers. From at least the early 1950s this was "the plan" in a sense. Alan Turing certainly thought so.
But yes, nervousness is warranted. We must tread carefully.
Re: Deep Learning Foundations to Stable Diffusion
#24Would it be possible to have a transcription of the videos? I have never been able to follow a video for learning, for me the video format if like someone else controlling the way I learn.I much prefer to be able to design my own schedule in text. By using text I am able to skim quickly and select only those parts I consider important. Maybe other people are able to do that with video but I am not in that group.
Re: Deep Learning Foundations to Stable Diffusion
#25Earlier quoted context omitted.
> since you'll be creating everything from scratch (i.e. from only Python and its standard library) Is this correct? I skimmed the notes for both parts 1 & 2 and they stated requiring PyTorch?
Yes, after we create something from scratch, we then see how to use implementations from libraries such as PyTorch. For basic operations like convolution, whilst we do create a GPU-accelerated version, it's not as fast as PyTorch/cudnn's highly-optimised version, so we use the PyTorch implementation for the rest of the course, rather than our handmade version. So that means that nothing is mysterious, since we know h…
Wow, you are really fulfilling the promise of a pragmatic approach. Awesome!
Re: Deep Learning Foundations to Stable Diffusion
#26Would it be possible to have a transcription of the videos? I have never been able to follow a video for learning, for me the video format if like someone else controlling the way I learn.I much prefer to be able to design my own schedule in text. By using text I am able to skim quickly and select only those parts I consider important. Maybe other people are able to do that with video but I am not in that group.
Yes every lesson has a complete transcript written by our wonderful community members. You can access through the usual YouTube interface.
Re: Deep Learning Foundations to Stable Diffusion
#27Earlier quoted context omitted.
> since you'll be creating everything from scratch (i.e. from only Python and its standard library) Is this correct? I skimmed the notes for both parts 1 & 2 and they stated requiring PyTorch?
Yes, after we create something from scratch, we then see how to use implementations from libraries such as PyTorch. For basic operations like convolution, whilst we do create a GPU-accelerated version, it's not as fast as PyTorch/cudnn's highly-optimised version, so we use the PyTorch implementation for the rest of the course, rather than our handmade version. So that means that nothing is mysterious, since we know h…
Ah, I've been waiting for this, looking forward to going through it!
While I appreciate your top-down approach and buy your arguments for doing it this way in previous courses, I also like this new bottom-up where one really learns what lies beneath.
Re: Deep Learning Foundations to Stable Diffusion
#28This is cool, but I have a fundamental question. Why learn machine learning when all the machines will learn how to create and control themselves and powerful elites will offload the burden of governments to control us? Or we race ourselves to fulfill the last jobs on earth? Is this progress for humanity or enslavement and the end of our species? I am serious. This question is honest. Maybe my IQ is too low to unders…
This question isn't specific to machine learning - if you've given up already, don't bother learning anything and see how it goes.
I guess that the fear, be it well founded or delusional, is fueled by the idea that a hammer for example have a lesser potential to inadvertently beat humans at civilizational level.
Re: Deep Learning Foundations to Stable Diffusion
#29I just finished this! My thoughts:
I recommend it. I feel I can now read an arbitrary paper, frown a lot, and eventually understand what it's talking about - to the point where I can implement my own buggy version. And hey, I built my own stable diffusion!!
I found the previous version of this course[1] to be a good complement: it's older (predates SD) but I feel it explains core concepts slightly better. Very understandable given how the close to the bleeding edge this new version is...
Perhaps an even better complement was Karpathy's famous course[2] - similar material but builds towards GPT instead of SD. The fastai coding style is somewhat esoteric (to me) so it was helpful to contrast with Karpathy's more familiar style. I recommend doing both courses. Also I believe the fastai folks are planning a part 3 which covers LLMs; looking forward to that.
Concepts from part 2 helped my hobby project, a 7-day forecast of renewable electricity and power price[3].
Feels pretty great to have built my own Stable Diffusion and GPT! I am grateful to Jeremy and Andrej.
[1] https://course19.fast.ai/part2
Re: Deep Learning Foundations to Stable Diffusion
#30This is cool, but I have a fundamental question. Why learn machine learning when all the machines will learn how to create and control themselves and powerful elites will offload the burden of governments to control us? Or we race ourselves to fulfill the last jobs on earth? Is this progress for humanity or enslavement and the end of our species? I am serious. This question is honest. Maybe my IQ is too low to unders…
I don't get why your question is getting unvoted. This is a serious question. For engineers and "normal people" as well : why bother learning ?