The review examines Daniel Everett's 'How Language Began', which challenges Chomsky's linguistic theories and proposes an alternative view of language as a gradual cultural invention.

A review of 'Why Machines Will Never Rule the World', presenting its arguments against AGI based on complexity and computability, while critically examining its conclusions and relevance.

A fictional game show story explores the blurred lines between human and AI intelligence through philosophical debates and personal anecdotes.

Scott Alexander explores the concept of AI as 'simulators' and its implications for AI alignment and human cognition.

Scott examines how AI language models' opinions and behaviors evolve as they become more advanced, discussing implications for AI alignment.

Scott Alexander bets that AI models will quickly overcome current limitations, based on how GPT-3 improved on GPT-2's shortcomings identified by Gary Marcus.

Scott Alexander examines GPT-3's capabilities, improvements over GPT-2, and potential implications for AI development through scaling.

Scott Alexander examines AI-generated poetry produced by Gwern's GPT-2 model trained on classical poetry, highlighting its strengths and limitations.

Scott Alexander presents a series of nested dialogues exploring the nature of understanding and meaning, from AI to humans to angels to God, questioning what true understanding entails.

Scott Alexander explores GPT-2's unexpected capabilities and argues that it demonstrates the potential for AI to develop abilities beyond its explicit programming, challenging skepticism about AGI.

Scott Alexander draws parallels between OpenAI's GPT-2 language model and human dreaming, exploring their similarities in process and output quality.