Abstract
Artificial Intelligence (AI) is transforming industries and revolutionizing how we interact with technology at an unprecedented pace, playing a crucial role in shaping our digital future. The global issues we face today are complex, and AI provides us with a valuable tool for augmenting human efforts in formulating hardware and software solutions to complex problems.
In the current age of the Fourth Industrial Revolution (Industry 4.0), to analyze the wealth of data provided by the Internet of Things (IoT), cybersecurity, mobile, business, social media applications, and medical records, there is greater need for machine learning (ML) and Artificial Intelligence (AI) algorithms [1]. Driven by increased productivity, digitalization requires novel AI algorithms to enhance safety, reduce human error, and enable more sophisticated data analysis. While AI refers to the simulation of human intelligence in machines, which allows them to perform tasks that typically require human cognitive functions such as learning, reasoning, problem solving, perception, and decision making, ML refers to technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience and data. The ultimate goal of AI is to develop machines that can think, reason, act autonomously, and, in some cases, surpass human capabilities across various domains, including healthcare, finance, transportation, and entertainment. Since the birth of AI with the “Logic Theorist” program created by Allen Newell and Herbert A. Simon in 1955, AI algorithms have led to innovations such as autonomous vehicles, smart homes, automated manufacturing systems, and medical robotics, creating a digital future.
In the current age of the Fourth Industrial Revolution (Industry 4.0), to analyze the wealth of data provided by the Internet of Things (IoT), cybersecurity, mobile, business, social media applications, and medical records, there is greater need for machine learning (ML) and Artificial Intelligence (AI) algorithms [1]. Driven by increased productivity, digitalization requires novel AI algorithms to enhance safety, reduce human error, and enable more sophisticated data analysis. While AI refers to the simulation of human intelligence in machines, which allows them to perform tasks that typically require human cognitive functions such as learning, reasoning, problem solving, perception, and decision making, ML refers to technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience and data. The ultimate goal of AI is to develop machines that can think, reason, act autonomously, and, in some cases, surpass human capabilities across various domains, including healthcare, finance, transportation, and entertainment. Since the birth of AI with the “Logic Theorist” program created by Allen Newell and Herbert A. Simon in 1955, AI algorithms have led to innovations such as autonomous vehicles, smart homes, automated manufacturing systems, and medical robotics, creating a digital future.
| Original language | English |
|---|---|
| Article number | 43 |
| Number of pages | 6 |
| Journal | Algorithms |
| Volume | 18 |
| Issue number | 1 |
| Early online date | 13 Jan 2025 |
| DOIs | |
| Publication status | Published - Jan 2025 |