The Emergence of Instruction-Following at Scale
Early text-generating AI systems often struggled to follow simple, direct instructions, producing low-quality or irrelevant outputs. However, as these systems grew significantly in size and complexity, the same technique of using simple instructions became a highly effective method for accomplishing a wide variety of tasks. Analyze the key factor that explains this dramatic improvement in the utility of simple instructions.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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A researcher provides the exact same simple instruction—'Summarize the provided article about renewable energy in three sentences'—to two different text-generating AI systems. System X is a model with a few hundred million parameters, developed several years ago. System Y is a modern model with hundreds of billions of parameters. Based on the relationship between model scale and the power of instruction-following, what is the most likely outcome?
Evaluating the Impact of Model Scale on Instruction Following
The Emergence of Instruction-Following at Scale