If it fails, what protects us? The opposition between a gating network and basic methods for venture success prediction is not a divergence of ambition, but a question of robustness and application conditions.
A sophisticated gating network could be overly sensitive to training data, leading to over-optimization that does not generalize in real market conditions.
For example, a model trained on a bullish market might fail to identify critical failure signals during an economic slowdown, where more stable methods would offer a more reliable predictability.
Protection against losses is paramount, and complexity is not always synonymous with resilience or fail-safe.