In this talk we explore the philosophical and technological advancements that shape our understanding of artificial intelligence. The discussion begins with an examination of the late philosopher Daniel Dennett's views, particularly his assertion that human intelligence is Turing computable and can be replicated through computational procedures. Dennett's perspective finds potential vindication in the capabilities of large language models (LLMs), such as ChatGPT and Gemini, which exhibit 'emergent properties' — complex behaviors arising from simpler underlying processes. While the mathematical foundations of these models are well-understood, the sheer scale, involving trillions of parameters, challenges our ability to predict or even explain their behaviors.

We also consider contrasting views from other philosophers, notably David Chalmers, who offers alternative insights into the nature of intelligence and consciousness. The talk culminates with a brief discussion on the applications of Transformer models in fields beyond traditional AI, such as cosmology and astronomy. These models, through their sophisticated use of the attention mechanism and deep architectures, open new avenues for understanding and exploring the universe. This talk aims to bridge philosophical theories and cutting-edge AI technologies, illustrating the computational evolution of human-like intelligence in machines.