1. Journey
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  3. Intermediate
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  5. Applied Interpretability

Applied Interpretability

Build tools to understand and explain AI behavior

0/5 completed

Topics

01

Mechanistic Interpretability Practice

Reverse engineer neural network behaviors

⏱️ 12 hoursAdvanced
→
02

Building Explainable AI Systems

Create AI systems that can explain their decisions

⏱️ 10 hoursIntermediate
→
03

AI Debugging Frameworks

Tools and techniques for debugging AI behavior

⏱️ 8 hoursIntermediate
→
04

LLM Psychology and Behavior Analysis

Understanding what we can learn about LLMs from conversational interaction

⏱️ 10 hoursIntermediate
→
05

Chain of Thought Analysis and Faithfulness

Analyzing and improving the reliability of reasoning traces in LLMs

⏱️ 12 hoursAdvanced
→
← Back to Intermediate
⚡Pre-rendered at build time

Created By

Veylan Solmira

AI Safety Researcher & Educator

✉️ veylan@example.com💼 LinkedIn🐙 GitHub

Quick Links

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About This Project

The AI Safety Research Compiler is a comprehensive curriculum designed to systematically develop AI safety research capabilities. It features dual learning modes, hands-on experiments, and philosophical explorations.

This project represents original work in AI safety education, including case studies, interactive notebooks, and philosophical essays.

Learn more about the project →

© 2025 Veylan Solmira. All rights reserved.

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