input: from typing import List
  
  def predict_annual_income(features: List[List[int]], labels: List[int], age: int, education: int) -> float:
      """ A neural network is designed to predict a customer's annual income based on their age and education level. 
      The model returns the predicted annual income for a given age and education level.
      
      >>> predict_annual_income([[25, 0], [30, 0], [35, 0], [40, 0], [45, 1], [45, 2], [50, 1], [50, 2], [55, 1], [55, 2], [50, 3], [60, 3]], [15000, 20000, 25000, 30000, 40000, 45000, 50000, 60000, 65000, 70000, 80000, 90000], 50, 3)
      80000
      """
output:     for i in range(len(features)):
          if features[i][0] == age and features[i][1] == education:
              return labels[i]
      return 0.0