How do AI and Machine Learning differ?

How do AI and Machine Learning differ?

AI and Machine learning are two of the many powerful tools that are changing the course of business for corporations of all sizes, especially the ones dealing with data and analyses. Today SMEs dealing with products that need to be smarter, more intelligent and deliver next-generation results are opting for intelligent systems and tools streamlined by artificial intelligence.

What is Artificial Intelligence?

The very basic definition of AI is when a machine or a system using behavioral data can replicate and mimic human-like behavior, acting more smartly. In the early days of AI, this technology allowed computers to play board games but today’s era of AI can be seen in the active functioning of devices like SIRI, ALEXA, etc. The Digital revolution has entered its AI phase, where it can deliver quality and data analyses, speech-to-text services, and even automated actions like driverless cars, etc.

AI or Artificial Intelligence allows machines and objects powered by IOT to work with high efficiency, deliver a more result-oriented approach and analyze data swiftly and organized way.

“Technology of Artificial Intelligence creates an intelligent and smarter system that simulates or mimics human intelligence.”

Types of AI

Currently, Artificial intelligence falls into three types, Weak AI, General AI and Strong AI. With the world moving towards 5G revolution, the future is expected to revolve with strong AI as a major force in it.

What is Machine Learning?

Machine learning is more or less a segment or part of AI and it works by using data-driven knowledge. Machine learning depends highly on the vast amount of useful data to make a decision, perform actions or predict an outcome. Machine learning is a system fed with a particular data and for its operation, but any change in data feed can alter the outcome.

Machine learning is all about developing a pattern or recognition, based on data, and thus it helps in making accurate predictions. Machine learning technology keeps on learning and makes changes as per the data it is exposed it. This form of AI is useful in the automation of any analysis-based process or prototype.

Today Machine learning is used in Google search algorithms, Facebook auto friend tagging, email spam filters, online recommendations, etc.

Types of Machine learning

There are three types of machine learning:

  • Supervised machine learning
  • Reinforcement machine learning
  • Unsupervised machine learning

Top 5 differences between AI and Machine Learning (ML)

AI - Artificial intelligence makes a machine simulate or mimic particular human intelligence or human behavior.
ML - Machine learning is part of AI that makes a machine or system learn from historical or past data by being programmed.
AI - The objective of the technology of Artificial intelligence is to make computers or machines so smart and humanlike that they can solve complex issues.
ML - The goal of machine learning is to make accurate predictions and output, based on its continuous learning from fed data.
AI - AI is focused on achieving the highest possibility of task success.
ML - ML is limited to making accurate predictions and predicting patterns.
AI - Artificial intelligence is all about creating intelligent machines to do any task as done by a human.
ML - Machine learning can only learn from the data at its end, to do only specific tasks for delivering accuracy-based results.
AI - Applications using Artificial intelligence or AI are SIRI, online gaming, a humanoid robot, Alexa, catboats based customer support, etc
ML - Applications using Machine learning or ML are Google search algorithms, online recommender systems, Facebook auto friend tagging suggestions, etc.

The growing need of AI in enterprises

While ML is a limited part of AI, Artificial Intelligence, on the whole, is powerful in offering the most advanced computing and digital operations. Enterprise-ready AI is a thing that can’t be ignored, with its power to analyze data to deliver the most optimized and efficient results. Today organizations are depending on AI for customer service, security, data analyses, etc.