AI has become an integral part of our lives and various industries. It is necessary to understand that AI, ML and deep learning are closely related to each other, but are not the same and cannot be used interchangeably. It can be understood through three circles nested inside each other. Know more in the attached article, the beginner – level guide by AI
Artificial Intelligence (AI) is the broadest term, covering the whole field of building machines that can perform tasks requiring human intelligence, such as reasoning, learning, and decision-making. AI is the umbrella, and everything else discussed here sits within it. An AI system does not necessarily have to learn from data; early AI included hand-coded rules and expert systems. AI is the goal, while machine learning and deep learning are two powerful ways to achieve it.
Machine Learning: Learning From Data
Machine Learning is a part of AI. In Machine Learning, the programme is not explicitly written with every rule; instead, it learns from data. Earlier, humans wrote strict instructions for computers to follow, whereas today machines can learn from the data provided and identify patterns on their own.
An email app that learns to spot spam from past examples is using machine learning; no one has to code a separate rule for every possible spam message.
Deep Learning: Learning With Neural Networks
Deep Learning (DL) is a part of Machine Learning and works on structures called artificial neural networks, which are inspired by the way the human brain processes information. Deep learning uses multiple layers that allow systems to learn complex patterns directly from large amounts of raw data.
Deep learning powers many advanced AI technologies today, including computer vision, speech recognition, large language models, and generative AI. The labs at Parul University and the NVIDIA Lab provide students with exposure to the infrastructure and technologies used for these areas.
What is the relationship among all
The relationship is linked; it can be explained as AI being the largest circle, where all the fields of AI and intelligent machines are included. Machine learning is a part of AI that reads the given data, learns from it and then works accordingly. Deep learning is part of machine learning; it is learning through multi-layered neural networks. It can be said that all deep learning is machine learning, and all of machine learning is AI, but not all AI is machine learning, and not all machine learning is deep learning.
FAQs
How to differentiate between AI, ML and Deep Learning?
There is a difference between all of these. AI is a wide field of machines, systems and how they perform intelligent tasks. Machine learning is about making systems learn from given data instead of programming it exclusively. It is a subset of AI. Deep learning is a subset of machine learning that has more than one layer, multi-layer neural networks to learn complex patterns. They are like level, deep learning part of machine learning, and ML is part of AI.
How is machine learning part of AI?
Machine learning is part of AI; it is a subset of AI. The work focuses on systems that learn patterns from the given data and improve with experience, rather than following set rules. All ML is AI but AI has more than ML; it has non-learning parts too, like expert systems.
What are uses of deep learning?
Deep learning is part of machine learning. It powers advanced AI applications, including computer vision, speech recognition, NLP, large language models, and generative AI. It uses powerful GPUs as it uses multi-layered neural networks, and it also trains on large datasets.
