Hoffman argues that philosophy trains individuals to grapple with foundational questions essential for innovation, especially in fast-evolving fields like AI. He critiques oversimplified ethical models like trolley problems for relying on unrealistic assumptions, advocating instead for reasoning grounded in real-world complexity. The conversation explores how AI challenges traditional philosophical debates—particularly between essentialism and nominalism—with language models reflecting nominalist tendencies by deriving meaning from usage rather than fixed definitions. Embeddings and large language models mirror late Wittgenstein’s idea of language as a dynamic, context-driven game. While current LLMs lack lived experience, training on structured data enhances their reasoning, enabling them to function as collaborators in intellectual inquiry. Technology, far from being separate from humanity, actively reshapes how we think and evolve culturally. Hoffman emphasizes that psychological research is often limited by its WEIRD biases, while tools like ChatGPT democratize access to knowledge. Ultimately, AI didn’t emerge from philosophy because the field often neglects technological embodiment—yet now, it offers a powerful way to engage with philosophical thinking interactively.