AI refers to the human-like intelligence in machines, enabling them to perform tasks that typically require human cognition, such as learning, problem-solving, pattern recognition, and decision-making. It involves techniques like machine learning and natural language processing.
Although AI has been around for decades, recent advances in computational power, large-scale data availability, and breakthroughs in algorithms have accelerated its development.
AI models still face significant challenges in areas such as natural language understanding, generalization across different tasks, and ethical concerns like bias in decision-making. These problems arise from limitations in data quality, model interpretability, and real-world complexity.
Robots are widely used in sectors like manufacturing, healthcare, and logistics. They are employed to increase productivity, reduce human error, and perform tasks that are either dangerous or too complex for humans.
The convergence of AGI and fully autonomous robotics could have a transformative impact. AGI, which refers to machines with human-like intelligence, is still in its early stages. However, if achieved, it could revolutionize industries by enabling robots to autonomously learn and adapt to a wide range of tasks.