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I started with Artificial Intelligence: A Modern Approach (by Norvig). I know it has nothing to do with the current trends of machine generated images and video

by danwee 4y ago

I started with Artificial Intelligence: A Modern Approach (by Norvig). I know it has nothing to do with the current trends of machine generated images and videos based on textual input... but I don't care. I don't really like machine/deep learning, but I love the AI topics the book covers. Hopefully one day Symbolic AI will kick off.

comfypotato 4y ago
I second this. It’s the golden standard textbook (don’t quote me, but I believe most universities use it for their AI I class). The first 10 or so chapters are written so well that you can literally just read them as a self-study undertaking. Each chapter has an introduction and conclusion that reads like a novel, and the rest of each chapter is delivered in manageable chunks. The second half of the book is more text-booky, but by chapter 10 you will have a much better idea of the field and will have picked up on areas you want to dive into more specifically. Chapters 1-10 cover state spaces, how deductive logic applies to machines, differences between environments from a machine perspective, and more (shoutout to the AI game chapter, it’s a fascinating introduction to how machines play games). I’d estimate that the first 10-12 chapters would take you less than 50 hours total. From there you would have the basics you need to jump into neural networks concepts, robotic decision making, or something else practical. All of AI is built on foundations from 1950-1990 (and earlier), and the first 10-12 chapters will give you that foundation.
cercatrova 4y ago
I can't agree with this. If OP wants to learn practical AI, as in what works today, symbolic AI is not it. For better or worse, they should learn machine learning and particularly neural network, and then deep learning architectures.
- ihatepython 4y ago
  Neural networks are a dead end. Anybody who has experience with them knows this.
  - cercatrova 4y ago
    You're joking right? Where do you think all the innovations are coming from? Stable Diffusion? Dalle? GPT? They're all deep neural nets.
    - ihatepython 4y ago
      You have your opinion, I have mine. I don't consider Stable Diffusion, Dalle, GPT etc to be particularly innovative, in terms of AI. I see them as dead-ends, they don't really work IMO, they don't lead anywhere, so they aren't very interesting to me. Neural nets are a dead end IMO
      - cercatrova 4y ago
        I don't understand your opinion, could you explain? From my point of view they're working just fine, I can type a prompt in SD and I get an image back. What alternate do you think is not a dead end?

by danwee 4y ago

comfypotato 4y ago

I second this. It’s the golden standard textbook (don’t quote me, but I believe most universities use it for their AI I class). The first 10 or so chapters are written so well that you can literally just read them as a self-study undertaking. Each chapter has an introduction and conclusion that reads like a novel, and the rest of each chapter is delivered in manageable chunks. The second half of the book is more text-booky, but by chapter 10 you will have a much better idea of the field and will have picked up on areas you want to dive into more specifically. Chapters 1-10 cover state spaces, how deductive logic applies to machines, differences between environments from a machine perspective, and more (shoutout to the AI game chapter, it’s a fascinating introduction to how machines play games). I’d estimate that the first 10-12 chapters would take you less than 50 hours total. From there you would have the basics you need to jump into neural networks concepts, robotic decision making, or something else practical. All of AI is built on foundations from 1950-1990 (and earlier), and the first 10-12 chapters will give you that foundation.

cercatrova 4y ago

I can't agree with this. If OP wants to learn practical AI, as in what works today, symbolic AI is not it. For better or worse, they should learn machine learning and particularly neural network, and then deep learning architectures.

ihatepython 4y ago
Neural networks are a dead end. Anybody who has experience with them knows this.
- cercatrova 4y ago
  You're joking right? Where do you think all the innovations are coming from? Stable Diffusion? Dalle? GPT? They're all deep neural nets.
  - ihatepython 4y ago
    You have your opinion, I have mine. I don't consider Stable Diffusion, Dalle, GPT etc to be particularly innovative, in terms of AI. I see them as dead-ends, they don't really work IMO, they don't lead anywhere, so they aren't very interesting to me. Neural nets are a dead end IMO
    - cercatrova 4y ago
      I don't understand your opinion, could you explain? From my point of view they're working just fine, I can type a prompt in SD and I get an image back. What alternate do you think is not a dead end?