For many decades, artificial intelligence (AI) has been a hot topic in the field of computer science. However, there has been a resurgence of interest in AI in recent years, particularly in the field of deep learning.
Deep learning is a subset of machine learning, which is a branch of AI. It is based on the concept of creating artificial neural networks that are modeled after the structure and function of the human brain. These neural networks can learn to recognize patterns and make predictions based on large amounts of data.
One of the reasons for the resurgence of AI through deep learning is the availability of vast amounts of data and the increasing computational power to process it. With the rise of the internet and the proliferation of smartphones, data is being generated at an unprecedented rate. This data can be used to train deep learning models, making them more accurate and powerful. Additionally, the development of powerful hardware such as graphics processing units (GPUs) has made it possible to train large neural networks quickly.
Deep learning has been used to achieve state-of-the-art results in a variety of applications, including image and speech recognition, natural language processing, and even self-driving cars. It has also been used to create new technologies such as generative models, which can generate new images, videos, and even text.
It's important to note that despite the advancements and the hype around AI, it's still a field in development and the future is uncertain. However, the potential of deep learning is significant and it is likely to continue to have a major impact on many areas of our lives. As students, learning about deep learning and AI can open up a wide range of career opportunities in fields such as computer science, robotics, and healthcare.