Inside the Black Box: Cracking AI and Deep Learning

Fine Tuning Lora: It's Not What You Think

When you fine-tune an AI model, what changes inside doesn't predict what changes outside. This week on Inside the Black Box, I break down why — and what it means for anyone auditing or regulating these systems.

When Fluent Answers Start Sounding True

This episode explores why smooth, coherent language can feel more credible than it is, and how processing fluency, familiarity, and authority cues shape what we believe. It also digs into why conversational AI is especially persuasive, from polished explanations to confident-sounding confabulations.

Why Your Brain Believes the Model

The Heuristic Loop You Can't Break from Inside

When Polished Answers Feel Finished

This episode explores fluency-as-validity: the way polished AI responses can make us feel like the work of judgment is already done. It also looks at why large language models are so effective at creating the sensation of clarity, and why mechanistic interpretability may be a way to push back against that enchantment.

What Seneca Teaches Us that Marcus Couldn't

716 features fire on both Seneca and Marcus Aurelius but stay dark for ad copy. The model learned Stoic philosophy, not just an author's style. Plus: why 'inert' features aren't all the same thing.