177: Vector Databases

Intro topic:  Buying a Car

News/Links:

• Cognitive Load is what Matters
  • https://github.com/zakirullin/cognitive-load
• Diffusion models are Real-Time Game Engines
  • https://gamengen.github.io/
• Your Company Needs Junior Devs
  • https://softwaredoug.com/blog/2024/09/07/your-team-needs-juniors
• Seamless Streaming / Fish Speech / LLaMA Omni
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  • Fish: https://github.com/fishaudio/fish-speech 
  • LLaMA Omni: https://github.com/ictnlp/LLaMA-Omni 

Book of the Show

• Patrick: 
  • Thought Emporium Youtube
    • https://youtu.be/8X1_HEJk2Hw?si=T8EaHul-QMahyUvQ
• Jason: 
  • Novel Minds
    • https://www.novelminds.ai/
      

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

Tool of the Show

• Patrick: 
  • Escape Simulator
    • https://pinestudio.com/games/escape-simulator/
• Jason: 
  • Cursor IDE
    • https://www.cursor.com/
      

Topic: Vector Databases (~54 min)

• How computers represent data traditionally
  • ASCII values
  • RGB values
• How traditional compression works
  • Huffman encoding (tree structure)
  • Lossy example: Fourier Transform & store coefficients
• How embeddings are computed
  • Pairwise (contrastive) methods
  • Forward models (self-supervised)
• Similarity metrics
• Approximate Nearest Neighbors (ANN)
• Sub-Linear ANN
  • Clustering
  • Space Partitioning (e.g. K-D Trees)
• What a vector database does
  • Perform nearest-neighbors with many different similarity metrics
  • Store the vectors and the data structures to support sub-linear ANN
  • Handle updates, deletes, rebalancing/reclustering, backups/restores
• Examples
  • pgvector: a vector-database plugin for postgres
  • Weaviate, Pinecone 
  • Milvus

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