Course 1 · Module 3
Capabilities, Limits, and Trajectory
This module looks at what current models can and can't do and how anyone knows. You'll be able to explain why a model states falsehoods fluently, how reasoning, search, tools, and agents extend it, and how to read a claim about AI progress, including claims about AI systems doing AI research. This is the knowledge you need to weigh a capability headline on your own.
Module objectives
- Explain why a model produces confident errors and inconsistent answers, and what researchers can observe inside it.
- Describe how step-by-step reasoning, retrieval, tools, and memory extend what a model can do.
- Interpret a benchmark claim, and explain how AI systems are used in AI research without treating forecasts as findings.
Lessons
- Lesson 1 Capabilities and Limits: Why models err, and what is known about their inner workings You'll examine why a language model can state something false with complete fluency and why it may answer differently when you rephrase. You'll also see what researchers have… 61111h 3m
- Lesson 2 Capabilities and Limits: Reasoning, tools, and agents You'll look at what has been added around the basic language model: step-by-step reasoning, search and document retrieval, software tools, and agents that work through a task over… 61111h 3m
- Lesson 3 Capabilities and Limits: Measuring progress and AI-assisted AI research You'll learn how AI progress is measured and why a headline score can mislead. You'll then look at how AI systems are being used in AI research itself, and you'll be able to… 611111h 33m