Part 6/10:
The production quality of AI systems, akin to manufacturing processes like semiconductor fabrication, reveals another layer of complexity. A critical factor is the yield; even with high precision at each task level, the cumulative effect can lead to surprisingly low performance outcomes. This problem underscores the difficulty in creating AI agents capable of performing a series of tasks reliably.
For example, current language models often yield less than 100% accuracy. When copycatting tasks, even minor errors can accumulate, leading to failure in completing tasks efficiently. This has been evident in the domain of self-driving technology, where strict standards and structures have yet to be met, leading to a reliance on human oversight even in controlled environments.