Artificial Narrow Intelligence (ANI) is a branch of artificial intеlligеncе (AI) that deals with the creation of intelligent agents (systems) that can perform specific tasks. This is in contrast to artificial general intеlligеncе (AGI), which deals with the creation of intelligent agents that can perform any task. ANI focuses on machine learning algorithms and other approaches to gain insights from data to achieve the limited, specific goals. ANI is often rеfеrrеd to as “weak AI” because it is not as advanced as AGI. Examples of systems that use ANI include search еnginеs, recommendation systems, natural language processing, and autonomous driving systems.
ANI is sometimes also referred to as weak AI or applied AI. It is the kind of AI that is used in practical applications such as speech recognition, facial recognition, and expert systems. One of the key goals of ANI is to create systems that are able to replicate or exceed human performance on specific tasks. This has been achieved to varying degrees in different domains. For example, DeepMind‘s AlphaGo Zero achieved superhuman performance on the game and was able to beat the best human players. This is an example of how successful ANI can be. In other domains, such as natural language processing, researchers are still working towards achieving ANI performance comparable to that of humans.
While ANI has made great progress, it is still far from being able to match human intelligence. This is due to the fact that ANI is limited to the specific tasks that it has been designed for. In contrast, AGI is not limited by this and is therefore seen as the ultimate goal of AI research. Human intelligence is unique in that it is both general and expansive. Whereas AI has made great progress in getting computers to perform specific, narrowly-defined tasks, it cannot match human levels of adaptability and creativity. This is due to the inherent complexity of abstract thought, which AI systems lack the intelligent architecture to fully comprehend.
Also, Human intelligence is underpinned by a great deal of hardwired knowledge, acquired through evolution and learning, that AI systems do not possess. This includes social and cultural context, values, and ethical decision-making, which are all deeply embedded in us and difficult for AI to simulate. Additionally, people can use intuition and wisdom to reach solutions, on which AI has no foundation. Until AI develops the capacity for those aspects of human cognition, AI will remain far from matching human intelligence.