This is awesome!
I loved the previous FastAI courses, and the top-down approach taken in them is really fun to go along with.
I guess now it's time for an LLM-themed course?
Deep Learning Foundations to Stable Diffusion
71–80 of 121 posts
Re: Deep Learning Foundations to Stable Diffusion
#72This looks awesome, however I probably need to do a bootcamp with real people to compete and have comradery with to actually retrain on the basics in this. It doesn't matter where in the world this is (I like to travel), but does anyone have a recommendation for in person bootcamps on AI?
If you're interested in taking this course, you can check the forums and/or Discord where people will organize study groups going through the course. Some of the study groups organized are in-person, some are virtual. These are usually great opportunities to study with some real people at the same time and get that camaraderie.
Re: Deep Learning Foundations to Stable Diffusion
#73Hi folks. Nice to see our new free (and ad-free) course here on HN! This course is for folks that are already comfortable training neural nets and understand the basic ideas of SGD, cross-entropy, embeddings, etc. It will help you both understand these foundations more deeply, since you'll be creating everything from scratch (i.e. from only Python and its standard library), and to understand modern generative modelin…
I hope that one day you will do another part about LLM, in pytorch, that would be great :-) Thanks for this material.
There are plans for an LLM course but very early ideas, stay tuned!
Re: Deep Learning Foundations to Stable Diffusion
#74This 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…
> Or we race ourselves to fulfill the last jobs on earth? I find the gitlab employees (developers) being excited over copilot to be almost the definition of insane short term gain, but in the long term it destroys demand for their own product developers that don't need to be employed don't need a subscription to github automating your own company/business out of existence
Depends what people are motivated to do - if you just want to build cool things quicker, you will probably be excited by ML.
If you like writing algorithms and enjoy the mental problem-solving aspect of it, then you might not like it.
If your main motivation is to protect your job/livelihood and ensure your existing skillset is in demand, then you will probably be worried.
But in any scenario, the cat is out of the bag - you can't un-invent it so might as well get excited and be on the train, rather than be the person that gets left behind.
Re: Deep Learning Foundations to Stable Diffusion
#75Earlier quoted context omitted.
That's not a serious question, it's the very definition of trolling. You can replace Stable Diffusion with any other subject to learn, and that particular doom scenario with a similar one or, if you don't feel very inclined to ellucubrate, just say the good old "why learn anything when we all are eventually going to die and be forgotten". Not cool.
Please, tell me your definition of trolling. Maybe after you help me understand, I will explain to the illustrators why they must prompt with text instead of drawing? Assuming that I don't learn is wrong. I have a local installation of SD with a lot of models to test. The only useful thing in this gizmo is the Control Net module or maybe the Photoshop plugin for outpainting. You can upload your linear representation…
Please, tell me your definition of trolling.
You enter a room where people are discussing a technical subject, trying to find ways to collaborate and have a better understanding and then you start giving your speech about the dark future of humanity, education, poverty and politics.
Picture yourself in the physical world doing that and imagine the reactions. Why do you think it's acceptable online?
Re: Deep Learning Foundations to Stable Diffusion
#76Earlier quoted context omitted.
> Or we race ourselves to fulfill the last jobs on earth? I find the gitlab employees (developers) being excited over copilot to be almost the definition of insane short term gain, but in the long term it destroys demand for their own product developers that don't need to be employed don't need a subscription to github automating your own company/business out of existence
Depends what people are motivated to do - if you just want to build cool things quicker, you will probably be excited by ML. If you like writing algorithms and enjoy the mental problem-solving aspect of it, then you might not like it. If your main motivation is to protect your job/livelihood and ensure your existing skillset is in demand, then you will probably be worried. But in any scenario, the cat is out of the b…
> But in any scenario, the cat is out of the bag - you can't un-invent it so might as well get excited and be on the train, rather than be the person that gets left behind.
there are plenty of other ways to deal with it
politically push for AI output to be banned, made un-exploitable or highly taxed
or the luddite approach
time will tell how the several billion people about to be made destitute will react
Re: Deep Learning Foundations to Stable Diffusion
#77Earlier quoted context omitted.
That's not a serious question, it's the very definition of trolling. You can replace Stable Diffusion with any other subject to learn, and that particular doom scenario with a similar one or, if you don't feel very inclined to ellucubrate, just say the good old "why learn anything when we all are eventually going to die and be forgotten". Not cool.
Please, tell me your definition of trolling. Maybe after you help me understand, I will explain to the illustrators why they must prompt with text instead of drawing? Assuming that I don't learn is wrong. I have a local installation of SD with a lot of models to test. The only useful thing in this gizmo is the Control Net module or maybe the Photoshop plugin for outpainting. You can upload your linear representation…
First answer for the trolling "argument": Because of freedom of speech.
Second answer: I am quite capable, technically speaking, to assess the technology. I don't see the benefits for humanity in A.I. "art" generators. And implementing A.I. outside the narrow use cases, which must be regulated in a form close to how we regulate nuclear energy, is not a good thing. Exponential growth is a reality with this one.
Outside the hype cycle, a lot of specialists are ringing the alarm bell already.
Dismissing their expertise because it represents an obstacle to startup and corporate ROI is not a form of rational thinking.
On the other hand, the signs are clear and finally the lack of empathy and ethics in tech industry will come to fruition.
Re: Deep Learning Foundations to Stable Diffusion
#78my nephew who is going to college this fall at east coast said, "what's the point of CS major anymore" and i asked "what do you mean" and he goes " ChatGPT".
This is very cynical coming from 16 year old; however, got me thinking about impact of Chatgpt on peoples' mind about learning ML/AI if chatgpt can do it all!
Re: Deep Learning Foundations to Stable Diffusion
#79Why would I want to learn fast.ai... I feel that while this course is surely superb, I don't want to invest time in a new framwework. What's your opinion? We've got lightning, fast.ai, and another one that I forgot about... why?
Did you create this account just to hate on the course? xd
Re: Deep Learning Foundations to Stable Diffusion
#80I've watched all of the fastai tutorials. I've screwed up by not going through and actually writing the code, but I hope to do it again and do it right this time. My biggest question is if this the whole part 2 course or still the 2-3 preview courses released around last November?