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From customer service chatbots to extremely sophisticated autopilot driving machines, artificial intelligence (AI) is undoubtedly having an impact on the world around us.
As this technology continues to become more and more present in our everyday lives, there’s a good chance you’ve thought about how you could put AI to work in your business.
But what is AI? Maybe you know a bit about what AI can do, but have yet to find an understandable definition. On top of this, when people talk about AI, other phrases pop up that sound similar and yet aren’t interchangeable – namely, machine learning and data science.
Don’t despair. We’ve got you covered. Pretty soon, you’ll be confidently chatting about AI adoption with the best of them.
Ready to get started? Here’s our quick-and-easy breakdown:
AI is the science of designing machines that can complete tasks that normally require human intelligence – such as reasoning, strategizing and problem-solving.
Essentially, AI enables computers to act intelligently.
For example:
Machine learning is a part of AI – the part that’s being adopted into industry at the highest rate. It works by taking a set of examples, building a statistical model based on those examples, and then using that model to make predictions about future samples.
Essentially, ML uses data, algorithms and computation to enable machines to learn.
For example:
Data science combines domain expertise, programming skills, math and statistics to extract meaningful insights from data. While there is some overlap between data science and machine learning, data science is often focused on explaining the data that exists, whereas machine learning is focused on predicting future data.
Essentially, data science makes sense of data.
For example:
To recap:
Get a crash course in artificial intelligence and machine learning in our monthly Machine Learning Foundations 1!
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