What is Artificial Intelligence (AI)?
Artificial Intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI combines computer science and robust datasets to enable problem-solving and encompasses technologies such as machine learning, natural language processing, robotics, and more.
AI can be used for various applications, including customer service automation, document processing and data capture automated at scale, Google-quality search and product recommendations, speaking with customers and assisting human agents, and much more.
AI systems are designed to analyze and interpret large amounts of data, recognize patterns, and make informed decisions or predictions based on available information. They can be classified into two main types:
- Narrow AI (also known as Weak AI): this type of AI is designed to perform specific tasks within a limited domain. Examples include voice assistants like Siri and Alexa, recommendation systems, and image recognition software. Narrow AI is focused on solving specific problems and cannot generalize its knowledge to other areas.
- General AI (also known as Strong AI or Artificial General Intelligence): refers to AI systems that can understand, learn, and apply knowledge across various tasks and domains, similar to human intelligence. General AI remains a theoretical concept, and scientists and researchers are actively working towards achieving this level of AI capability.
AI techniques include machine learning, where algorithms are trained on data to improve their performance over time, and deep learning, which utilizes artificial neural networks to mimic the structure and function of the human brain.
The applications of AI are diverse and can be found in various fields, including healthcare, finance, transportation, manufacturing, education, and entertainment. AI has the potential to automate repetitive tasks, enhance decision-making processes, enable personalized experiences, and contribute to scientific advancements. However, it also raises ethical concerns and challenges related to privacy, bias, job displacement, and the impact on society.