Resources from our AI Engineering Reading Group, originally forked from the Latent Space paper club. While we maintain some of their excellent research paper selections, our focus extends to practical AI engineering materials and implementation details.
Our goal is to bridge the gap between cutting-edge research and real-world applications in AI/ML systems.
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Attention Is All You Need: Query, Key, and Value are all you need (Also position embeddings, multiple heads, feed-forward layers, skip-connections, etc.)
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AI Engineering: Building Applications with Foundation Models Chapter 3 - Evaluation Methods: Understanding evaluation metrics (entropy, perplexity), AI as judge, and comparative evaluation methodologies for foundation models.
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AI Engineering: Building Applications with Foundation Models Chapter 6 - RAG: Deep dive into Retrieval-Augmented Generation architectures, retrieval algorithms and optimization, and extending RAG beyond text applications. (Cookbook)