What I Learned Building and Training an LLM from Scratch (You Can Too)
In this post, I’ll share what surprised me most about building an LLM from scratch—where structure finally became visible. I wanted to write an autoregressive, transformer-based, decoder-only Large Language Model—like GPT, LLaMA, etc.—without too many abstractions and hand-holding. Andrej Karpathy, ARENA, Sebastian Raschka, Stanford's
Introducing "Beyond the Parrot"
In 2021, Emily Bender and her collaborators coined the phrase "stochastic parrots" to describe Large Language Models (LLMs). Their argument was pointed: these systems, trained to predict the next token in vast corpora of text, lacked understanding, merely recombining previously seen patterns—much like a parrot randomly repeating
An Introduction to AI for Investigation: Theory and Practice
The following is an edited, Claude-generated summary of a Whisper-generated transcript of a guest lecture I gave at Berkeley's Human Rights Center on March 4, 2025. I was excited to demonstrate the transformative potential of artificial intelligence in investigation, knowing how limited AI's use is in
Modern AI: Anatomy, agency, and a world beyond the stochastic parrot.
