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Latent Space: The AI Engineer Podcast — Practitioners talking LLMs, CodeGen, Agents, Multimodality, AI UX, GPU Infra and all things Software 3.0 cover image

The "Normsky" architecture for AI coding agents — with Beyang Liu + Steve Yegge of SourceGraph

Latent Space: The AI Engineer Podcast — Practitioners talking LLMs, CodeGen, Agents, Multimodality, AI UX, GPU Infra and all things Software 3.0

NOTE

Debating the Paths to Artificial Intelligence

The history of artificial intelligence involves a long-standing debate on the path to achieving general human-level intelligence. This debate consists of two main schools of thought: the Norvig approach, which emphasizes learning from data through models like large language models and regression, and the Chomsky approach, which focuses on constructing precise formal systems using tools like compilers and parsers. While the Norvig approach currently holds the upper hand with the advancements in machine learning, the Chomsky-based tools still play a crucial role in providing context, knowledge graph backbone, guardrails, and safety checkers for the output of data-driven systems.

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