Article Series Part 1 – Artificial Intelligence, Machine Learning and Deep Learning in the Real Estate Industry: Understanding the Concepts and Levels

Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are prominent terms in today’s technological landscape. Although often used interchangeably, these words represent distinct, but interconnected concepts in the world of computer science. To illustrate this, let’s think of AI, ML, and DL as the elements of a solar system. AI constitutes the sun, the center of all activity, with ML as the planets orbiting the sun and DL as the moons orbiting those planets.

Artificial Intelligence (AI)

AI, like the sun in our solar system, forms the foundation for everything else. It is a broad term that refers to computer programs or systems that can perform tasks that normally require human intelligence. This includes, but is not limited to, tasks such as problem solving, speech and image recognition, and decision making. AI is categorized into different levels based on its functionality and capability, which we will discuss later.

Machine Learning (ML)

ML, like the planets in our solar system, orbits the central AI sun. It is a subcategory of AI and involves computer programs being trained to learn and improve over time by being exposed to data, rather than being explicitly programmed to perform a specific task. ML algorithms build models based on collected data and use these models to make predictions or decisions without having to be explicitly programmed.

Deep Learning (DL)

DL, like the moons that orbit the planets, is even more specific. It is a subcategory of ML and is based on the concept of neural networks – a computerized model inspired by the human nervous system and brain. Specifically, DL uses deep neural networks with multiple layers of nodes (neurons), enabling the processing and modeling of more complex data structures compared to traditional ML algorithms.

Now that we have differentiated between AI, ML and DL, let’s dive deeper into AI and its different levels.

Narrow AI or Weak AI

Narrow AI, are AI systems that are designed to perform a specific task, such as voice recognition or image analysis. These systems can only perform the specific task they are trained for and have no or limited ability to generalize their skills to other tasks. Most of the AI systems we use today, such as the voice assistants on our phones, are examples of narrow AI.

General AI or Strong AI

General AI represents AI systems that can understand, learn, and apply knowledge in the same way a human brain does. In theory, these systems could perform all the intellectual tasks that a human can. However, at the time of writing, general AI has not yet been achieved.

Super intelligence

The third and most ambitious step in AI development is called superintelligence. These hypothetical AI systems would surpass human intelligence in almost every practically meaningful respect, including creativity, general wisdom, and social skills. However, we are still far from achieving superintelligence, and its potential consequences and ethical issues are still the subject of intense discussion.

Understanding AI, ML and DL, as well as the levels of AI, not only gives us insight into the advancement of technology, but also helps us navigate the future with greater awareness and preparedness.

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