Part 5/10:
Navigating the Challenges of Neural Network Evolution
Progress in neural network-based FSD has historically been unpredictable. Changes in architecture, input types, training data quality, and heuristic code often lead to inconsistent results—causing fluctuations in system performance. Tesla has been navigating these challenges through continuous trial and error, adjusting structure, data, and algorithms.
James suggests that recent developments indicate a promising shift: Tesla’s V12 is likely establishing a stable foundation, enabling predictable, linear improvement in FSD Beta versions. This could mark a turning point where autonomous driving approaches the reliability and consistency needed for widespread deployment.