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A technical dialogue between Scott Alexander and Eliezer Yudkowsky exploring why AI alignment is difficult, covering the inapplicability of human moral development analogies, the nature of AI consequentialism, and skepticism about acausal trade as a safety mechanism.
Scott Alexander examines GPT-3's capabilities, improvements over GPT-2, and potential implications for AI development through scaling.
Scott Alexander plays chess against GPT-2, an AI language model, and discusses the broader implications of AI's ability to perform diverse tasks without specific training.
Scott Alexander humorously describes AI-generated content simulating humans pretending to be robots pretending to be humans on Reddit.
Scott Alexander examines AI-generated poetry produced by Gwern's GPT-2 model trained on classical poetry, highlighting its strengths and limitations.
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.
Read Scott like a free app: tap then Add to Home Screen. Read Scott like a free app: tap then Add app to Home screen. Add Read Scott Alexander to your home screen to read it like an app.