👉 Computing, at its core, involves the processing of data through algorithms and hardware to perform tasks that would typically require human intelligence, such as learning, reasoning, and problem-solving. However, in certain contexts, computing can appear computationally intensive, meaning it requires significant processing power, memory, or time to execute tasks. This is often seen in complex computations like deep learning, large-scale simulations, or data-intensive analyses. For instance, training a neural network can take hours or even days on powerful GPUs due to the sheer volume of calculations involved. Similarly, processing massive datasets or running intricate simulations can strain even the most advanced computing resources, making it seem computationally intensive despite the underlying hardware being capable and efficient.
