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Why 4-Bit Weights Are Easy and 8-Bit Activations Break Models: Inside LLM Inference, Part 3

 Towards AI

A systems-level mental model of quantization, built from the asymmetry that explains every method in the field Quantizing the weights of a large language model is close to a solved problem. You can d...

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Context vs. Memory Engineering in Agentic AI Systems

 MachineLearningMastery.com

Compression on Arrival Tool outputs should be compressed after a call returns, not after the window fills.

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Spec-Driven Development in Action with GitHub Speckit

 Towards AI

Source: Image by the author (AI-generated). In a previous article titled Vibe Coding vs spec-driven development, I explored spec-driven development and compared it with vibe coding. The central idea w...

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