BlueDot Narrated The AI Triad and What It Means for National Security Strategy
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May 20, 2024 
Ben Buchanan, author of the AI Triad framework, discusses the inputs powering machine learning: algorithms, data, and compute. The podcast explores the impact of these components on national security strategy, the disparities between machine learning and traditional programming, and the application of machine learning in national security, robotics, and AI advancements.
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The AI Triad Distills Modern AI
- Modern AI's essence: computing power runs algorithms that learn from data.
- These three elements form the 'AI Triad' that explains machine learning capability.
Neural Networks Trade Power For Opacity
- Neural networks power flexible machine learning but lack transparent reasoning.
- That opacity creates major legal and ethical challenges in high‑stakes domains.
GPT-3 Shows The Triad In Action
- OpenAI trained GPT-3 on nearly a trillion words reduced to ~540GB and 175 billion parameters.
- The result ran on high-performance computers for days and convincingly imitated human writing.