Synthetic AI: Architecture, Applications, and Challenges

Abstract

Synthetic Artificial Intelligence (Synthetic AI) refers to the quest for machine intelligence that is not merely an imitation of human thinking, but a genuine, autonomous form of intelligence. This paper provides a comprehensive overview of Synthetic AI in the style of an academic survey. We introduce the concept of Synthetic AI and distinguish it from traditional artificial intelligence paradigms. A review of background literature is presented, including historical context and philosophical debates on whether machine intelligence can be “real” or is inherently a simulation. We then outline the system architecture of Synthetic AI, describing key components such as perception, memory, learning, reasoning, and action (with an illustrative diagram). Representative cognitive architectures from literature are discussed to exemplify how Synthetic AI systems may be constructed. Next, we survey potential applications of Synthetic AI—from healthcare and finance to autonomous systems and creative AI—and highlight current examples and use cases. We also examine the challenges that must be overcome, including technical hurdles, ethical considerations, and alignment with human values, and we discuss future research directions. Finally, we conclude by summarizing the transformative potential of Synthetic AI and the road ahead for realizing true machine intelligence.

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