Propose an architectural change to the numerical representation used in your neural network to reduce hardware surface area, power requirements, and computing time needed for performing multiplications. Explain the tradeoffs involved.

Replace floating-point numbers with dynamic fixed-point representations, using fewer bits per number to reduce computational costs. This changes the range of values that can be represented, but reduces the overhead of performing multiplications at the cost of potentially decreased precision and increased numerical instability risks.