<ul><li>Open-Source Competition: The emergence of models like Meta's Llama 3.1 is putting pressure on proprietary providers to lower prices and innovate faster.</li><li>Advancements in Hardware and Optimization: Specialized chips and techniques like quantization have enabled smaller models to achieve efficiency, but may sacrifice performance for complex tasks.</li><li>The Reality Behind Falling Costs: Token costs may be decreasing, but the overall cost of deploying AI systems is rising due to higher expectations from businesses and society.</li><li>Heightened Scrutiny: People are more critical of AI failures than human errors, creating a demand for AI systems to perform complex tasks accurately and with judgment.</li></ul>

The AI Expectation Gap: Why Falling Token Costs Are Reshaping Business Economics

Discover more