You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: As you can see, there are several advantages of smaller CNN architectures.With this in mind, we focus directly on the problem of identifying a CNN architecture with fewer parameters but equivalent accuracy compared to a well-known model.We have discovered such an architecture, which we call SqueezeNet.In addition, we present our attempt at a more disciplined approach to searching the design space for novel CNN architectures. In this section, we design and execute experiments with the goal of providing intuition about the shape of the microarchitectural design space with respect to the design strategies that we proposed in Section 3.1.Note that our goal here is not to maximize accuracy in every experiment, but rather to understand the impact of CNN architectural choices on model size and accuracy.

Question: The goal of authors regarding microarchitectural design space was to understand the impact of CNN architectural choices on model size and accuracy. Were they able to draw a conclusive impact?
They come to an impact that the size of the model can be reduced while still obtaining same or higher accuracy with fewer parameters through manipulating architectural design strategies as is the case in their architecture -SqueezeNet. Although the authors rather design and execute experiments with the goal of providing intuitions about the shape of the microarchitectural design space with respect to the design strategies they proposed, SqueezeNet and other models reside in a broad and largely unexplored design
space of CNN architectures that need more investigations