AI vs Machine Learning: Key Differences

In contrast, data-driven AI systems are built using machine learning algorithms that learn from data and improve their performance over time. Deep learning is a subset of machine learning that deals with algorithms inspired by the structure and function of the human brain. Deep learning algorithms can work with an enormous amount of both structured and unstructured data. Deep learning’s core concept lies in artificial neural networks, which enable machines to make decisions.

One of the most common tasks given to reinforcement learning systems is mapping routes. Since there are many possible solutions to a simple point A to point B route on a map, the system has to find an optimal route. Hence, it will be geared towards finding a route with the least time taken and distance traveled. As the name suggests, reinforcement learning is a type of machine learning wherein outputs are tweaked based on maximizing rewards.

Thanks to Deep Learning, AI Has a Bright Future

The problem is that these situations all required a certain level of control. At a certain point, the ability to make decisions based simply on variables and if/then rules didn’t work. Instead of engineers teaching or programming computers to have what they need to carry out tasks that perhaps computers could teach themselves – learn something without being explicitly programmed to do so. ML is a form of AI where based on more data, and it can change actions and responses, which will make it more efficient, adaptable, and scalable. Deep learning is a subset of machine learning, which is a subset of AI.

Of late, some researchers believe that we’ve made strides toward the first AGI system with GPT-4. As you can see in the screenshot below, it can use logical reasoning to answer hypothetical questions, even without explicit training on the subject. Moreover, it’s primarily designed to function as a large language model but can solve math, write code, and plenty more.

Machine Learning vs. AI: What’s the Difference?

But the depictions of AI you’ve probably seen in movies are known as general AI, or Artificial General Intelligence (AGI). In a nutshell, general AI can emulate the human mind to learn and perform a wide range of tasks. Some examples include critiquing essays, generating art, debating psychological concepts, and solving logical problems. Generally speaking, anything that can mimic the decision-making abilities of a human can be classified as an AI. Banks, for example, use AI to analyze markets and perform risk analysis based on a set of rules.

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