Python for AI #5: AI APIs (ChatGPT, OpenAI, AssemblyAI, and Replicate)

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  • Опубліковано 24 лис 2024

КОМЕНТАРІ • 16

  • @entreempresarios81
    @entreempresarios81 Рік тому +2

    I am just learning python and seeing this great video made me realize I am walking a good path. Thank you, teacher!

  • @codinglovers5395
    @codinglovers5395 Рік тому +3

    Thank you for creating this valuable resource video. Your video has undoubtedly helped many people, including students, developers, and AI enthusiasts. Love from Bangladesh

  • @lewismuriungi4564
    @lewismuriungi4564 Рік тому +2

    Amazing work, just found this video, wanna start the playlist

  • @shanmukhasuryateja95
    @shanmukhasuryateja95 Рік тому

    Your videos are amazing. You should do more of these!!

  • @truthdeeds3612
    @truthdeeds3612 Рік тому

    Amazing 👏

  • @anirbanc88
    @anirbanc88 Рік тому

    this is the greatest playlist ever #EEAAO

  • @ttaylor9916
    @ttaylor9916 Рік тому

    fantastic tutorial. thanx

    • @ttaylor9916
      @ttaylor9916 Рік тому

      but seems like your website has changed dramatically since you made this video... cant find anything.

  • @wsligter
    @wsligter Рік тому

    DallE vs Huggingface vs Replicate Image generation... Which is best in your opinion?

    • @EliSpizzichino
      @EliSpizzichino Рік тому +1

      Huggingface and Replicate are model hubs where you can find DallE, stable diffusion and other models for Image generation

  • @goodluckefe4795
    @goodluckefe4795 Рік тому

    Any API for text to video ?

  • @mysocial8731
    @mysocial8731 Рік тому

    Hello, I want to ask you whether there are job opportunities for an artificial intelligence engineer or not?

    • @ramikanimperador2286
      @ramikanimperador2286 Рік тому

      Start playing with the AI ​​itself by asking for ready-made codes, like the GPT3.5 AI (or Cloud+), ask for the codes and test them (while studying Python), this way you will be able to get a good idea of ​​the codes and how it works. I don't even know how to program and I've already managed to create a code to train GPT2 chat offline on a weak computer just using the CPU (it took me 6 months to do it)... Those who understand know the difficulty, but apparently I have one last obstacle to solve: Apparently my entire dataset is not being executed when training the AI, I believe it is running completely but randomly in pieces, which is making the AI ​​learn well but as it rarely sees the examples it cannot reproduce when tested. I had the idea of ​​dividing the dataset into small pieces divided by tokens (1084), I will have many files in the folder, but if I manage to code correctly, the PC will train one piece at a time using very little memory and CPU power, but for sure I will greatly increase the training time, which will be very good for my final purpose of taking the AI's training OFFLINE and on computers for ordinary people in countries like Brazil and India, for example, and using their common processors (CPU) or GPU cuda if have.