👉 Modified computing refers to the adaptation and optimization of traditional computing paradigms to better suit modern computational challenges, particularly those involving massive data sets and complex algorithms. It encompasses techniques like parallel processing, distributed computing, and specialized hardware designs such as GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units), which are tailored for specific tasks like machine learning and deep learning. Modified computing also includes software innovations, such as frameworks and languages optimized for these architectures, enabling more efficient data handling, faster computation, and reduced energy consumption. By integrating these advancements, modified computing aims to address scalability, performance, and resource efficiency issues that arise in today's data-intensive applications.
