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172: Transformers and Large Language Models – Beragampengetahuan

172: Transformers and Large Language Models

Intro topic: Is WFH actually WFC?

News/Links:

  • Falsehoods Junior Developers Believe about Becoming Senior
    • https://vadimkravcenko.com/shorts/falsehoods-junior-developers-believe-about-becoming-senior/
  • Pure Pursuit
    • Tutorial with python code: https://wiki.purduesigbots.com/software/control-algorithms/basic-pure-pursuit 
    • Video example: https://www.youtube.com/watch?v=qYR7mmcwT2w 
  • PID without a PHD
    • https://www.wescottdesign.com/articles/pid/pidWithoutAPhd.pdf
  • Google releases Gemma
    • https://blog.google/technology/developers/gemma-open-models/

Book of the Show

  • Patrick: The Eye of the World by Robert Jordan (Wheel of Time)
    • https://amzn.to/3uEhg6v
  • Jason: How to Make a Video Game All By Yourself
    • https://amzn.to/3UZtP7b

Patreon Plug https://www.patreon.com/programmingthrowdown?ty=h

Tool of the Show

  • Patrick: Stadia Controller Wifi to Bluetooth Unlock
    • https://stadia.google.com/controller/index_en_US.html
  • Jason: FUSE and SSHFS
    • https://www.digitalocean.com/community/tutorials/how-to-use-sshfs-to-mount-remote-file-systems-over-ssh

Topic: Transformers and Large Language Models

  • How neural networks store information
    • Latent variables
  • Transformers
    • Encoders & Decoders
  • Attention Layers
    • History
      • RNN
        • Vanishing Gradient Problem
      • LSTM
        • Short term (gradient explodes), Long term (gradient vanishes)
    • Differentiable algebra
    • Key-Query-Value
    • Self Attention
  • Self-Supervised Learning & Forward Models
  • Human Feedback
    • Reinforcement Learning from Human Feedback
    • Direct Policy Optimization (Pairwise Ranking)


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Contents

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