The advancement of artificial intelligence (AI) technology has been rapid in recent years, and some experts argue that it is progressing at a faster pace than Moore’s Law.
Moore’s Law is a prediction made by Intel co-founder Gordon Moore in 1965 that the number of transistors on a computer chip would double approximately every 18-24 months, leading to a steady increase in computing power and a decrease in cost per transistor. This prediction has held true for several decades, but it is now reaching its physical limits as transistors approach the size of individual atoms.
On the other hand, AI progress is driven by a combination of hardware advancements (such as the increase in computing power and storage capacity) and software innovations (such as the development of new algorithms and models). These factors have led to significant breakthroughs in areas such as image and speech recognition, natural language processing, and autonomous systems.
One reason for the faster progress of AI is the availability of large amounts of data. Machine learning algorithms, which are at the heart of AI, require vast amounts of data to learn from in order to improve their performance. The explosion of data from sources such as the internet and connected devices has provided researchers and companies with more data than ever before, allowing them to train and improve their models at a rapid pace.
Another reason for the faster progress of AI is the advances in hardware specifically designed for AI tasks. Graphics Processing Units (GPUs) are particularly well-suited to the kinds of matrix and vector operations required by deep learning algorithms, and companies like NVIDIA and Google have been investing in developing new hardware specifically designed for AI tasks, known as TPU and Tensor Core which are helping to speed up the training of deep learning models.
Finally, the increase in investments and research in AI by companies like Google, Facebook, and Baidu, as well as by governments and academic institutions around the world, has led to a rapid acceleration of progress in the field.
In conclusion, while Moore’s Law has been a powerful driver of the advancement of technology for many decades, the progress of AI is now being driven by a combination of hardware advancements, software innovations, the availability of large amounts of data and the specialised hardware, as well as increased investments and research. This has led to a rapid acceleration of progress in the field of AI, resulting in it to progress faster than Moore’s Law.