Several misconceptions are related to the words Artificial Intelligence and Machine Learning, many think these both are the same, and well these words are very closely related to each other. But there are few differences too.
In this article, let’s understand the basic differences between AI and machine learning
Artificial Intelligence (AI) is the process of transmitting data, information to machines; so that the machines can function the same way as human intelligence. Its main goal is to build self-reliant machines that think and act like human beings. These machines can copy human behavior and do tasks by learning and problem-solving. Almost all of the systems simulate natural intelligence to solve complex problems.
AI focuses on doing 3 cognitive skills just like a human – learning, reasoning, and self-correction. It is divided into 2 broad categories. They are:
v Type-1: Based on Capabilities
There are 3-kinds of AI based on their capabilities.
- Artificial Narrow Intelligence: This is also called ‘Weak AI’ that can program the machines to perform specific tasks, but in a much better way than a human.
- Artificial General Intelligence: The AI that can do tasks of an array of intellectual/intelligent works with the equal accuracy level as a human being does.
- Artificial Super Intelligence: This is the most advanced form, also called ‘Active AI’. It can outperform humans in certain tasks with better accuracy and speed in less time.
v Type-2: Based on functionality
These are of 4-types, which are dependent on the working functionality of machines.
- Reactive machines: These are the systems that solely react. These systems don’t consist of memories, and also don’t use any previous experiences for taking new decisions.
- Limited memory: These systems reference the past, and information is added over a while. The referenced information is short-lived.
- Theory of mind: This covers systems, which can understand human emotions and how they affect decision-making. They are trained to adjust their behavior based on it.
- Self-awareness: These systems are designed and created to be aware. They have the caliber to understand their internal states, predict other people’s feelings, and act appropriately.
Currently, AI is been used in several ways. A few of them include:
- Chatbots which answer questions based on user input
- Machine translation such as Google Translate
- Self-driving vehicles that include Google’s Waymo
- AI Robots that include Sophia and Aibo
- Speech Recognition based applications such as Apple’s Siri, Google Assistant, Alexa, and Cortana
- Several different facial recognition systems
AI and machine learning are very closely related to one another, the ML is a subset of the AI. ML is an area of computer science that uses computer algorithms and analytics to develop predictive models or take decisions from past data or experiences without being explicitly programmed and helps solve business problems. ML uses a large amount of structured and semi-structured data so that the ML model can get accurate results or provide predictions depending on the data. The ML is mainly used in the following places:
- Sales forecasting for different products
- Fraud analysis in banking
- Product recommendations
- Stock price prediction
As the applications of Artificial Intelligence and Machine Learning continue to increase, the jobs available are more in these fields. A few of the job opportunities and their average salaries are:
- AI engineer – Are problem-solvers who develop, test, and apply different models of artificial intelligence and effectively manage the AI infrastructure. They use ML algorithms and possess knowledge of the neural network to create better AI models.
Average salary per annum – $116,540 (Glassdoor)
- ML engineer – The machine learning engineer develops and takes care of self-running software which facilitates machine learning initiatives. They work with huge amounts of data and have extraordinary data management traits.
Average salary per annum – $121,106 (Glassdoor)
Individuals who choose a career path in ML and AI can prove their skills by doing machine learning certification through several learning institutions.
The demand for individuals who have done machine learning certification has risen because several firms consider the certifications as a benchmark to evaluate the skills of an individual in the process of hiring.
If an individual is planning to pursue ML and AI then make sure they are ready with the right skill set and certifications. By, doing certifications in ML and AI one can improve their chances to get into a better job.