A machine learning engineer claims, 'To improve our language model's performance, our top priority should be to increase its parameter count. A larger model architecture is the most critical factor for achieving state-of-the-art results.' Critically evaluate this claim. In your response, discuss the relationship between model architecture size and the volume of training data, and explain why focusing on one factor in isolation might be a flawed strategy.