Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are buzzwords in the tech industry, with companies and developers discussing their adoption. However, it’s crucial to understand that AI encompasses all these concepts. AI refers to the overall field of making machines smarter, while ML is a subcategory that involves systems that learn and improve on their own through algorithms. Deep Learning (DL) is a type of ML that specifically focuses on large data sets. Most AI advancements involve ML as it is crucial for creating intelligent systems
AI
Since the inception of technology, humans have been captivated by automation. AI gives machines the ability to think and make decisions without human involvement. It is a wide field within computer science and encompasses three types of systems: ANI (Artificial Narrow Intelligence), designed to perform a single task; AGI (Artificial General Intelligence), capable of learning, comprehending, and mimicking human intelligence in specific situations; and ASI (Artificial Super Intelligence), a theoretical type of AI where machines surpass human intelligence to an incredible extent.
ML
Machine Learning (ML) is a part of the Artificial Intelligence (AI) field that utilizes statistical algorithms to create intelligent systems. ML systems can learn and evolve without explicit programming. For instance, the recommendation systems in music and video streaming services are examples of ML. The ML algorithms are categorized into three types: supervised, unsupervised, and reinforcement learning.
DL
Deep Learning (DL) is a sub field of AI that emulates the human brain’s information filtering process. It is centered around learning through examples. DL systems enable a computer model to filter input data through multiple layers to make predictions and classify information, much like the human brain. It is utilized in technologies such as self-driving cars. The DL network structures are divided into Convolutional Neural Networks, Recurrent Neural Networks, and Recursive Neural Networks.