No one actually knows why AI works

About this Video

• Video Title: No one actually knows why AI works
• Channel: Alberta Tech
• Speakers: One speaker (name not provided in transcript)
• Duration: 10:30

Introduction

This video explores the current lack of understanding surrounding how AI, specifically large language models (LLMs), actually function. The speaker argues that while the basic mechanics are understood, the emergent capabilities that make AI impressive and transformative are not fully grasped by the field. The video aims to explain this gap and discuss ongoing research into AI interpretability.

Key Takeaways

• LLMs are next-word prediction models: The core functionality of LLMs relies on predicting the next word in a sequence. The transformer architecture, introduced in the 2017 paper "Attention is All You Need," significantly improved this prediction capability.
• Emergent capabilities are unexplained: Impressive AI capabilities like following instructions, answering truthfully, and demonstrating reasoning appear as models reach a certain size. The reason for this emergence is currently unknown.
• Building AI ≠ Understanding AI: Knowing how to build an AI model doesn't equate to understanding why it works. The speaker uses analogies like building a model airplane without understanding aerodynamics to illustrate this point.
• Interpretability research is underway: Researchers are actively investigating AI interpretability, seeking to understand the "black box" of AI models. Examples include Anthropic's work on identifying features (e.g., the Golden Gate Bridge) and circuits within LLMs to trace their reasoning processes.
• Understanding AI is crucial for progress and safety: A deeper understanding of AI is essential for improving AI development, mitigating safety concerns (such as AI manipulation), and addressing the unprecedented nature of this powerful yet opaque technology.