What is artificial intelligence? There are two types of AI:
Applied AI is here, and it is already impacting the way commercial real estate professionals do their jobs and the way investors, buyers and tenants use properties. Understanding AI will help you better serve your clients. Here’s what you need to know now.
Machine learning refers to a computer’s ability to learn through experience without being explicitly programmed, and it’s the most common type of AI in use today. Through machine learning, computers look at patterns in data to find insights and make “choices.” A constructed system allows the computer to experiment and improve until it finds an optimal solution to a problem that humans perhaps had never considered.
Artificial neural networks are a common software architecture used to build machine learning systems. They’re designed to process information the same way the human brain does.
Neural networks recognize patterns and can learn through multiple layers, meaning they’re more complex than other methods of AI. Neural networks therefore offer the most promise for achieving AGI through machine learning.
Examples of AI made possible through machine learning include:
Natural language processing (NLP) is defined as the automatic (or semi-automatic) processing of human language. Through NLP, we’re able to communicate with computers in the same way we communicate with one another and receive answers to questions or solutions to problems.
Technologies that use NLP are already used widely today, and they’re going to keep advancing. Apple’s Siri, Amazon’s Alexa, digital translators and speech-to-text tools are common examples.
Machine perception is the processing of sight, sound and touch through technology. Artificial intelligence with machine perception capabilities can take in data from the world around it and respond accordingly. NLP falls into the category of machine perception, but perceptive AI can also interact with and evaluate other sounds and objects beyond constructed language.
Facial recognition, handwriting analysis, and perhaps most impressively, disease diagnosis tools use machine perception technology to analyze objects or surroundings.
Predictive analytics uses algorithms to process information, discover trends in data and make recommendations or predictions.
Netflix’s “recommended for you” suggestions, which are generated through algorithms, are a prime example of this. Pandora and Spotify’s music recommendations, which are based on your previous listening history, also come to mind. Fraud detection even uses predictive analytics to monitor credit card purchases, decide whether certain purchases are in line with a customer’s behavior, and alert them if something is suspicious.
In CRE specifically, site selection provides property recommendations based on user preferences.
Automated planning and scheduling uses data and algorithms to set something in motion and complete an action.
The most popular current example of a technology that uses automated planning and scheduling is the self-driving car. Another prominent example is the Mars Exploration Rover, which uses automated planning and scheduling to generate command sequences.
These AI technologies are interesting, but how will they affect the way commercial real estate professionals work and the way their buyers, investors and tenants operate? The answers might surprise you. Access our new resource to find out: Demystifying the future of artificial intelligence: commercial real estate and the tech of the future.