ML vs AI: what's behind AI-enabled machine learning

ML vs AI: what’s behind AI-enabled machine learning

It’s hard to avoid the hype around machine learning and artificial intelligence happening right now. Just type in a phrase “ML vs AI” in your browser search line and you will get thousands discussions about what machine learning is and how it differs from artificial intelligence. People want to know the difference and get a better idea of these emerging technologies. What’s going on out there? What makes AI-powered machines? Can computers think and act like humans do? Let’s find out.

AI and ML in simple words

Artificial intelligence is a branch of computer science about creating intelligent machines that can think and act like humans. It is a set of technologies to utilize data, processing power, programming and algorithms to train computers for certain human-inherent traits such as problem solving, planning, learning, reasoning, perception.

AI and ML in simple words
AI techniques train computers for certain human-inherent traits
source: pixabay.com

Machine learning is an application of AI about creating algorithms that allow computers to make more accurate predictions by analyzing big data and finding patterns, without being explicitly programmed by humans. AI-powered computers sort through large sets of data (this process is called “data mining”) to forecast outcomes (this process is called “predictive modeling”). In other words, machines learn from analyzing data by using advanced algorithms.

As it comes from the definitions, it is not correct to compare ML vs AI because machine learning is a technique of artificial intelligence, and computers use this technique to learn from experience and become more intelligent.

When talking about AI and ML, it makes sense to point out how exactly AI makes machines learn. Let’s find it out.

What makes machines learn

Today machine learning is the most popular technique as compared to NLP, Neural Networks and other AI techniques because it provides faster and better results in making computers intelligent. Why does it happen? And what allows computers to get smarter?

There are 4 reasons why machines learn and become more intelligent today:

  • Large data sets and reduced cost of data storage
  • Server Infrastructure and high processing power
  • Simple and advanced algorithms
  • Data scientists and businesses implementing AI systems at commercial scale

Thanks to the advancements in data, infrastructure, algos and AI commercialization, today AI can be found just about everywhere – in your smartphone, computer or even your vacuum cleaner. Read this guide “AI 101” to learn more.

Machine learning can easily be automated as computers use an iterative approach to analyze and learn from data. Iterations are performed through the incoming data until a robust pattern is found, so the machine can learn something new from this experience.

Why ML and AI matter for business

How are businesses integrating machine learning in their strategy and operations? The nine leading innovation companies – Google, Apple, Facebook, Amazon, IBM, Microsoft, Tencent, Baidu, and Alibaba – design and train their proprietary AI systems (e.g. IBM Watson for digital marketing and Google Translate) using machine learning techniques.

What about other businesses? ML lets collect valuable insights from big data (that human would never be able to do themselves), to allow businesses to work more efficiently and gain an advantage over competitors. See these 5 US-based startups employ AI techniques to offer better services for marketing and sales teams.

Here’s how machine learning helps businesses across 5 industries of choice:

machine learning for 5 industries of choice

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