Defining A.I.
In my last few posts, I've discussed data: what it is, why it's valuable, and how the current paradigm makes getting accurate, actionable data difficult for most companies.
The solution is a game-changer. But before we get there, we need to understand the basics of AI.
A few days ago, someone mentioned "this A.I. thing," and that notion - A.I. is here, big but mysterious - is pervasive. And that's the first question I want to tackle: What is A.I.?
Here are a few things A.I. is not:?
What people mean when discussing A.I. is not A.I.
Instead of Artificial Intelligence - a computer that is something close to human in its thought and decision-making processes -? what they're talking about, and what we see in the marketplace, is Machine Learning (ML): teaching a computer to execute tasks and choose a course of action by identifying patterns.?
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A.I. is computer software designed to mimic how humans think and perform complex tasks, such as analyzing, reasoning, and learning. Machine Learning, on the other hand, is a particular subset of A.I. that utilizes algorithms trained on data to create models that can perform such complex tasks with more accuracy and efficiency.
The distinction between AI and ML is crucial as we navigate this new era of machine intelligence. While AI is the broader concept of machines mimicking human intelligence, ML is a specific subset that focuses on training machines to learn from data and make decisions or predictions.
Neither of these are the dystopian terminators of Hollywood, but tools that, when used responsibly and thoughtfully, can significantly enhance our ability to process data, make informed decisions, and ultimately improve the world around us.?
In my next blog post, I will delve deeper into how businesses can effectively leverage these technologies.
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