Businesses are focusing on data-driven insights more than ever before as data become intrinsically connected to every aspect of our lives. Artificial Intelligence (AI) has rapidly become a necessity for businesses to thrive in data-driven markets. Artificial Intelligence enables computer systems to use a combination of data, logic, and mathematical and statistical methods to solve problems and make decisions. There are many subsets of artificial intelligence such as cognitive learning, machine learning, neural networks, and deep learning.

While AI can be leveraged in several ways to optimize products and services to meet customer demands and expectations, AI remains a complex subject. In popular media, the term ‘AI’ is used to describe a wide range of technologies, tools, and techniques. It is important to understand the nuances of the different branches of artificial intelligence. Some of the most popular subsets of artificial intelligence are as follows:

Cognitive Learning enables computer systems to mimic human behavior when engaging in human interaction-related applications. The most well-known application of AI is cognitive learning, which people encounter most often in their daily lives. A good example of cognitive learning is voice assistants found on many mobile devices and smart home devices.

Machine Learning (ML) enables computer systems to actively learn from data by employing statistical tools and techniques when engaging in data-related applications. A good example of ML is a search engine that uses data to identify the most relevant results when a user searches for something online.

Neural networks also called artificial neural networks (ANNs), rely on a type of machine learning algorithm that enables computer systems to replicate the human brain’s processing ability. Human brains use an interconnected network of neurons to transmit and process information. Similarly, neural networks use networks of interconnected artificial neurons, also called nodes, that mimic the behavior of a human brain. A good example of neural networks is facial recognition software used by mobile phones to recognize authorized users.

Businesses are actively seeking to take advantage of data, artificial intelligence, and machine learning capabilities. However, implementing an artificial intelligence and machine learning system is challenging because it requires extensive knowledge and expertise. Hence, AI & ML experts are some of the most highly sought-after professionals. AIPI3 consists of a collection of professionals who are Subject Matter Experts in the AI & ML arena. We are committed to empowering businesses to stay competitive with reliable data applications, optimal algorithms, knowledge, and the expertise necessary required to implement artificial intelligence and machine learning systems.