With the advent of modern technologies, new words have appeared that we hear all the time. However, we may not know the differences between one and the other. In this post, we will discuss the difference between Artificial Intelligence and Machine Learning, two technologies that have made our lives more comfortable.
What is Artificial Intelligence?
Artificial Intelligence (AI) is a term that describes devices capable of learning from previous experiences. It uses that learning to make decisions based on those experiences. Artificial Intelligence can be broad or narrow depending on its use. AI is a much broader term than Machine Learning.
The main goal of Artificial Intelligence is to make machines as intelligent as humans. That is, it focuses on making devices think and behave like humans. AI-powered devices are trained to solve problems and learn. Robots and autonomous cars are the best examples of AI in today’s world.
AI can fulfill three main business needs:
- Business automation. Most back-office administrative and financial activities can be easily automated through Robotics Process Automation (RPA) solutions. Processes such as transferring data from the call center system or emails to a customer management solution, replacing lost ATM or credit cards, or extracting provisions by reading contracts can be streamlined. Extracting provisions by reading contracts and other legal documents using natural language processing.
- Data collection and analysis. Some companies use AI-based algorithms (to be more precise, Machine Learning models) to detect and interpret regular patterns such as predicting follow-up purchases, identifying card fraud, or automating ad targeting.
- Customer engagement. Natural Language Processing (NLP) chatbots, intelligent agents and Machine Learning models drive many businesses today. Some companies use AI solutions for employees (e.g., Becton, a U.S. medical technology company, uses Amelia as an internal help desk agent), while others leverage AI technologies to better serve their customers through recommender systems that provide more personalized care plans.
What is Machine Learning?
Machine Learning (ML) is the ability of a machine to learn using advanced algorithms. Over time, we can teach machines to recognize patterns, objects, and other input data that we provide to a device. To have Artificial Intelligence, Machine Learning is the main component.
Machine Learning algorithms have no competition when it comes to anomaly detection. They do this by looking for events that differ significantly from each other. This technology is frequently used in the banking sector. For example, Stripe uses ML-based anomaly detection to identify fraudulent actions.
Many of the products we use every day also use Machine Learning models. Apple, Google, Amazon voice assistants (Siri, Alexa, Cortana) work with Machine Learning models. They are used in different situations, from text prediction to app recommendation.
Amazon leverages it to recommend items to consumers. Its recommendation engine works based on the purchase of a product that people make on the platform. Facebook and Google use ML models to adjust which ads to show users based on their last search query.
The difference between Artificial Intelligence and Machine Learning
In conclusion, Artificial Intelligence solves tasks that require human intelligence, while Machine Learning is a subset of AI that solves specific tasks by learning from data and making predictions.
This means that all Machine Learning is Artificial Intelligence, but not all Artificial Intelligence is Machine Learning.
We have exposed what Artificial Intelligence and Machine Learning are composed of and how they differ, as well as the specific uses that can be given to each of them.
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