172: Transformers and Large Language Models

Episode description

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)