What is a primary reason for machine learning becoming the dominant form of artificial intelligence?

Access to massive amounts of digital data is a primary reason for machine learning becoming the dominant form of artificial intelligence. The effectiveness of machine learning models significantly relies on the quantity and quality of data available for training. With the rise of the internet, social media, IoT devices, and other digital technologies, enormous datasets can now be collected from various sources. This data serves as fuel for machine learning algorithms, enabling them to learn complex patterns and make accurate predictions.

The massive volumes of data enhance the training process by providing diverse examples that allow models to generalize better to unseen scenarios. In contrast, while powerful hardware, increased demands for automation, and advanced algorithms contribute to the growth and capabilities of machine learning, the foundational element that drives most advancements in the field is the sheer volume of data accessible for analysis and training. Without sufficient data, even the most sophisticated algorithms would struggle to perform effectively, making access to substantial and varied datasets a critical factor in machine learning's prominence in AI.