👉 Fixed computing refers to a type of computing architecture where the hardware is designed for specific, predefined tasks, typically involving specialized processing units optimized for particular types of computations, such as matrix operations or neural network inference. Unlike general-purpose computing (like CPUs), which can handle a wide variety of tasks, fixed computing systems are highly efficient and optimized for their designated functions. This specialization allows them to achieve higher performance, lower power consumption, and reduced latency for their intended applications, making them ideal for tasks in machine learning, image processing, and other data-intensive fields. The fixed nature of these systems means they cannot be easily repurposed for different tasks without significant redesign or hardware replacement.
