Difference Between Artificial Intelligence and Machine Learning

Most people think Artificial Intelligence and machine learning are the same as both belong to the computer science domain. Surely, these two fields are correlated with each other. But when you take a closer look, AI and machine learning are two completely different technologies. Both technologies are trending high, and both are used for creating intelligent systems. Although the two are closely intertwined and technologically related, sometimes people think that the two are synonymous with each other. When you choose the specialization of your degree or courses, you can choose AI ML courses as per your choices. Both specializations are booming and trending, as the demand for professionals in both these fields is too high all over the globe.

What are AI and ML?

Artificial intelligence refers to a computer imitating human functions such as learning and problem-solving. With the help of Artificial intelligence, a computer can calculate maths and logic, just like how a human being learns new information and make a decision. Artificial Intelligence is widely used in the Robotics industry; personal Assistants Such as Google home by Google, Siri by Apple, and Alexa by Amazon. These technological products allow users to discover information and do things such as book hotels, add events to calendars, ask questions and answers, schedule meetings, send messages and emails, etc., without human assistance.

Machine learning is a subset that comes under Artificial intelligence, and it is used in mathematical models for gathering and processing data to help computers learn without human interaction and instructions. Machine learning will help computer systems to continue learning and improving on their own based on experience. Most e-commerce websites and portals use these machine learning tools to recommend products based on historical data. Using the Machine Learning tool, these websites also recommend things that you have liked, added to your cart, viewing history, or any other related behaviors. This tool is also used widely in filtering email spam, Malware filtering automatically in your mailboxes.

Even though both are co-related to the computer science department, there are differences between Artificial intelligence and Machine Learning. AI solves the problems which require human intelligence, and ML is an integral part of AI which solves specific tasks by learning from the database, and it makes predictions. So, AI and ML are not the same. While all ML comes under the AI, all AI need not come under the ML. Their capabilities, benefits and environments are different.

Features of AI and ML

Looking at the capabilities of AI and ML, every industry is opting for these technologies. Every company is discovering new opportunities through AI and ML. Machine learning helps a company with predictive analytics of trends, customer behavioral patterns, relationship data, etc. Computer systems identify words from speech using artificial intelligence. This is called natural language understanding (NLU). Moreover, it can calculate and understand commands, recognize faces, objects, and actions in images and videos, and implement various functions.

Differences between AI and ML

AI: AI acquires and applies the knowledge. It is defined as the acquisition of knowledge and intelligence.
ML: ML acquisition of knowledge or skill set.
AI: AI aims to increase the chances of success, not accuracy. It works like a computer program, and it also works as an intelligent program.
ML: Ml aims to increase accuracy. Ml doesn’t care about success. ML takes the data, and it learns from the data.
AI: The goal of AI is to function as a natural intelligence to solve complex problems and make its own decisions.
ML: Ml’s goal is to learn from data on certain tasks to maximize the performance on that task. It allows systems to learn new things from databases.
AI: AI is developing a system that enacts humans in solving problems, acts without human presence, and finds the optimal solutions.
ML: Ml creates self-learning algorithms, and it will go for a solution, whether it is optimal or not.
AI: Machine learning and deep learning are the two main subsets of AI, and it has a wide range of scope when it comes to job opportunities.
ML: Deep learning is the main subset of machine learning, and it has a limited scope when it comes to job opportunities compared to AI.
AI: AI is widely used in online games, intelligent humanoid robots, expert systems, personal assistants like Siri and Alexa, customer support via catboat, and many more.
ML: ML is widely used in e-commerce portals, online recommender systems, Google search algorithms, auto recommendations in online shopping portals, and many more.
AI: AI includes learning, reasoning, and self-correction. It deals with raw data, structured data, and semi-structured data.
ML: ML includes learning and self-correction only when it gets introduced to new data. It will process structured and semi-structured data.

AI is an essential system that seems smart. It includes the behaviors of problem-solving, learning, and planning. These can be easily achieved through analyzing the data and identifying patterns within the data to replicate these behaviors. On the other hand, ML is a type of artificial intelligence that is more powerful than AI. AI gives the overall appearance of being smart, but in AI, the machine takes the data, and it learns things from the data, which would be difficult for humans to do. At the same time, ML can go beyond human intelligence, as it processes a large quantity of structured and semi-structured data within a period through the algorithms.

Both AI and Ml have their own weightage when it comes to career prospects. AI and Ml professionals have a huge demand and are offered high salary packages all over the globe. The demand for these professionals is rising day by day as the demand for AI and ML is increasing. Both these technologies are used widely in all sectors such as the army, banking, healthcare, e-commerce, IT, Networking industry, and many more.