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What is the difference between artificial intelligence, machine learning, and deep learning?
In today’s tech world, the most commonly used term isn’t necessarily “artificial intelligence.†It’s often said that the cafes in Zhongguancun act as a barometer for the tech industry. If you want to know what’s trending, just listen in on conversations at these coffee shops. However, despite its popularity, many people still struggle to fully grasp what AI truly means. When entrepreneurs talk about AI, they often bring up terms like “machine learning†and “deep learning.â€
So, what exactly is artificial intelligence? What does machine learning mean, and how does deep learning fit into the picture? To help you understand these concepts better, we’ll break them down and explain their relationship.
Artificial Intelligence (AI) refers to systems or devices capable of performing intelligent tasks. Machine Learning (ML) is a subset of AI, and Deep Learning (DL) is a subset of ML. In simple terms, AI is the big picture, ML is a part of it, and DL is a more advanced form of ML. This means that while all deep learning and machine learning fall under AI, not everything labeled as AI uses ML or DL.
The term "artificial intelligence" was first coined by John McCarthy, a cognitive scientist. He believed that any intellectual behavior could be simulated by machines. That idea still holds true today.
Broadly speaking, AI describes how machines interact with the world. Through software and hardware, an AI system can mimic human behavior or perform tasks like a person would. For example, if you have photos of your mom and girlfriend on your phone, AI can help you sort them out. In areas like facial recognition, AI can be more efficient than humans, which is why it's being applied in fields like computer vision, natural language processing, and even cybersecurity.
But how do smartphones recognize faces? The answer lies in "machine learning." Simply put, machine learning is a way to build AI systems. It works by analyzing large amounts of data, identifying patterns, and making predictions. It's similar to how humans learn—by gaining knowledge and applying it. But here, the learner is the machine.
Machine learning relies on complex algorithms, and one of the most powerful among them is deep learning. Over the past decade, deep learning has revolutionized AI, enabling computers to process vast amounts of data and uncover hidden patterns. It mimics the human brain's neural networks, allowing machines to classify data and find correlations without direct human intervention.
For instance, when sorting images of your mom and girlfriend, deep learning automatically analyzes features like age, expression, and posture. Unlike traditional machine learning, which requires manual adjustments, deep learning can extract thousands of parameters from big data, making it far more powerful.
Thanks to advancements in data handling, computing power, and algorithms, AI is now growing rapidly. However, this growth also places new demands on device performance. Qualcomm has been focused on efficiently managing multiple workloads within the constraints of mobile devices. By leveraging different computing engines like CPU, GPU, and DSP, they deliver optimal performance.
Qualcomm’s AI platform now offers a responsive, secure, and intuitive user experience through efficient end-to-end machine learning. And with continuous innovation, the future of AI looks even more promising.