👉 Challenged computing refers to the complex and often resource-intensive tasks that push the boundaries of current computational capabilities, particularly in areas like artificial intelligence, machine learning, and large-scale data processing. These tasks frequently require significant amounts of memory, processing power, and specialized hardware to achieve acceptable performance levels. For instance, training deep neural networks with millions or billions of parameters can consume vast amounts of energy and time, making it challenging for many organizations to implement these technologies effectively. Additionally, the need for real-time processing and the demand for high accuracy in applications such as autonomous driving or medical diagnostics exacerbate these challenges, requiring innovative solutions to optimize efficiency and reduce costs.
