🔗 ← Class 4: AI Capabilities - What Can It Actually Do? | Class 6: Commercial LLM Platforms →
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Resources
📄 Lesson PDF
📊 Slides PDF
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Video Lesson
https://youtu.be/H0SlVfTn_vE
Learning Objectives
- Explain tokens and context windows using operational analogies such as mission briefs and intelligence reports to understand fundamental performance constraints
- Evaluate the speed-price-intelligence tradeoff when selecting models for different mission requirements, recognizing that optimization of all three factors simultaneously is not possible
- Interpret performance benchmarks including Humanity's Last Exam, Coding Index, and Omniscience Leaderboard to assess model reliability for mission-critical applications
- Differentiate between reasoning and non-reasoning architectures and determine when each type is appropriate based on task complexity and operational constraints
Introduction
Military leaders at every echelon now face decisions about large language model deployment, yet most lack the technical vocabulary to evaluate competing systems objectively. Commercial vendors present capability claims without context. Technical specifications list numbers without operational translation. The result is predictable: organizations select premium models for routine tasks, waste budget on unnecessary capabilities, or worse, deploy inadequate systems for critical missions.