Artificial Intelligence Architecture

Artificial intelligence (AI) architecture research focuses on designing efficient and reliable AI systems, addressing challenges like inconsistency, inaccuracy, and the ethical implications of increasingly sophisticated models. Current efforts concentrate on developing explainable AI, integrating symbolic reasoning with neural networks (neurosymbolic AI), and creating distributed architectures for improved scalability and privacy, such as federated learning approaches. These advancements are crucial for expanding AI's capabilities in diverse fields, from optimizing telecommunications networks to enhancing the accuracy and trustworthiness of complex decision-making systems.