HomeAIOpen the Synthetic Mind: Sparse Autoencoders for LLM Inspection | by Salvatore...

Open the Synthetic Mind: Sparse Autoencoders for LLM Inspection | by Salvatore Raieli | Nov, 2024


|LLM|INTERPRETABILITY|SPARSE AUTOENCODERS|XAI|

A deep dive into LLM visualization and interpretation utilizing sparse autoencoders

Towards Data Science

13 min learn

15 hours in the past

Explore the inner workings of Large Language Models (LLMs) beyond standard benchmarks. This article defines fundamental units within LLMs, discusses tools for analyzing complex interactions among layers and parameters, and explains how to visualize what these models learn, offering insights to correct unintended behaviors.
Picture created by the writer utilizing DALL-E

All issues are topic to interpretation whichever interpretation prevails at a given time is a perform of energy and never fact. — Friedrich Nietzsche

As AI techniques develop in scale, it’s more and more troublesome and urgent to know their mechanisms. As we speak, there are discussions in regards to the reasoning capabilities of fashions, potential biases, hallucinations, and different dangers and limitations of Massive Language Fashions (LLMs).



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