Machine learning and artificial intelligence (AI) are two parts of computer science that are almost co-related to each other. These two technologies are favoured by companies to create smart programs for others to use. AI Seed offers investment support to machine learning and AI startups. In 2020, people benefit from many AI-powered programs like Uber, Google Maps, and many other applications. However, there is some confusion in what consists of machine learning and how it differs from artificial intelligence. They are not exactly the same, but the perception that they are can lead to confusion.
Both terms come up in on a day-to-day basis when it comes to Big Data analysis, and the broader aspects of technological change sweeping through our world. The short answer to both these terms is:
Practical: Machine learning and artificial intelligence are interchangeable terms and used in supervised learning.
Theoretical: Machine learning is a branch of AI or is a way of implementing AI.
Although both are related technologies that people sometimes use as a synonym for each other, there are differences between them.
Below are some significant differences between these two terms, along with an overview of both:
The word artificial intelligence is made up of two words “artificial” and “intelligence.” Artificial refers to anything made by human hands or non-natural thins, and intelligence means the ability to understand and think. A common misconception is that AI development is a system, but in fact, it is not a system rather an implementation of it. One of the most explicit definitions of AI is the ability granted to computers to think and make decisions on their own better than present humans do. Hence, AI is the intelligence where we want to add all the capabilities of humans in machines.
Machine learning enables a system to make predictions based on data and is a valuable part of AI development systems. It takes data as information to make predictions without being explicitly programmed. Machine learning utilizes a large amount of structured or semi-structured data to produce accurate results or forecasts. The machine learning model has self-learning algorithms that make use of historical data and works in specific domains. Machine learning is used in a number of applications like email spam filters, Google search algorithms, auto friend tagging in Facebook, etc.
Major Differences between Machine Learning and Artificial Intelligence
|Machine learning is a subset of AI that uses historical data for prediction without programming||AI technology mimics human intelligence and simulates human behaviour|
|Aim of machine learning is to learn from past data to give an accurate result||Aim of AI is to make a smart system like humans to solve complex problems|
|In machine learning, humans teach machines to use data to generate results||AI make intelligent systems that think like humans|
|Deep learning is a subset of machine learning||Machine learning and deep learning are subsets of AI|
|Machine learning allows the system to learn new things from data provided||AI system makes a decision on its own|
|It involves the creation of self-learning algorithms||It is the development of a human mimicking system to respond in different scenarios.|
|Machine learning goes for just a solution, not discerning whether it is optimal or not||Artificial intelligence goes for optimal solutions|
|Machine learning leads to knowledge||Artificial intelligence leads to wisdom|
|Machine learning is concerned with accuracy and patterns||Artificial intelligence is concerned with maximizing chances of success|
|Primary applications of machine learning are Google search algorithms, Facebook auto friend tagging, etc.||Primary applications of AI programs are SIRI, online gaming platforms, humanoid robots, and automatic chatbots,|
|Machine learning can be divided into supervised, unsupervised and reinforced learning||Artificial intelligencg can be divided into weak AI, strong AI, and general AI|
|Machine learning deals with only structured and semi-structured data||AI deals with structured, semi-structured and unstructured data|
The points as mentioned above are some of the key differences between these two terms. While machine learning and AI programs may look one and the same, these differences show that there are details that make them change from one other. However, both these technologies have become a significant aspect of today’s innovation and developmental issues. AI Seed offers investment support to machine learning and AI startups; contact us today if you would like AI PhDs to join your startup, or need a workspace at a subsidised rate, or want to find brilliant minds to work for you, etc.