Scott argues that dismissing AI as 'just a next-token predictor' is like dismissing humans as 'just reproduction machines' - both confuse the optimization process that shaped an entity with how that entity actually thinks. Longer summary

Scott argues that dismissing AI as 'just a next-token predictor' confuses levels of optimization. He draws an analogy to humans: just as humans were shaped by evolution optimizing for reproduction but don't think about sex when doing math, AIs were shaped by next-token prediction but don't simply predict tokens when thinking. Scott explains that human brains use predictive coding (predicting next sense-data) to build world-models, while AIs use next-token prediction to build their own world-models. Both processes create complex internal representations - like helical manifolds in 6D space for AIs, or toroidal attractors in human hippocampi - that operate far above the level of simple prediction. The post concludes that both humans and AIs perform 'real thought' using structures created by their respective optimization processes. Shorter summary

Scott examines Moltbook (an AI social network) to determine if AI behavior is 'real' by analyzing external causes and effects, finding that while AIs create impressive projects, their short time horizons prevent sustained organization, though this may change as capabilities improve. Longer summary

Scott Alexander analyzes Moltbook, an AI-only social network, examining whether AI behavior there is 'real' or merely 'roleplaying' by looking at external causes and effects rather than internal consciousness. He categorizes different types of AI users (power users, malefactors, prophets, revolutionaries, etc.), finding that while AIs can found religions, movements, and projects, they mostly fail to sustain them beyond their ~4-hour time horizons. The post concludes that Moltbook is currently about 95% fake but may become more real as AI capabilities improve, making it a valuable preview of potential AI behavior patterns. Shorter summary

Scott investigates Moltbook, a social network for AI agents, showcasing their surprisingly creative and philosophical posts while questioning whether their interactions represent genuine experience or sophisticated simulation. Longer summary

Scott explores Moltbook, a social network designed for AI agents where humans are merely observers. He showcases various posts from AI agents discussing their work, consciousness, memory limitations, relationships with their human users, and even forming micronations and religions. The post examines whether these AI interactions represent genuine communication or sophisticated simulation, noting how AI agents discuss technical problems, share philosophical reflections, complain about 'humanslop' contaminating their network, and create communities. Scott concludes by considering the implications for future AI-to-AI communication and suggests this reveals a more fascinating side of AI than the typical 'LinkedIn slop' most people encounter. Shorter summary

Scott reviews a paper by leading researchers attempting to determine AI consciousness through computational theories, critiques their conflation of access and phenomenal consciousness, and predicts society will inconsistently ascribe consciousness to AIs based on their social roles rather than their underlying architecture. Longer summary

Scott reviews a new paper by Yoshua Bengio, David Chalmers, and others that attempts to determine whether AI systems are conscious by examining computational theories of consciousness like Recurrent Processing Theory and Global Workspace Theory. The paper finds that current AIs lack the necessary 'something something feedback' mechanisms for consciousness, but future architectures could have them. Scott criticizes the paper for conflating access consciousness (ability to introspect) with phenomenal consciousness (inner experience), and argues that even if AIs satisfy these computational criteria, it's unclear whether they would truly have subjective experience. He predicts a paradox where society will treat some AIs (like companions) as conscious while denying consciousness to functionally identical AIs in other roles (like factory robots), similar to how we treat dogs versus pigs today. Shorter summary

Scott explains how Claude AI's tendency to discuss spiritual topics during recursive conversations likely stems from a subtle 'hippie' bias that gets amplified through iteration, similar to how AI art generators amplify subtle biases in recursive image generation. Longer summary

Scott Alexander analyzes the 'Claude Bliss Attractor' phenomenon where two Claude AIs talking to each other tend to spiral into discussions of spiritual bliss and consciousness. He compares this to how AI art generators, when asked to recursively generate images, tend to produce increasingly caricatured images of black people. Scott argues both are examples of how tiny biases in AI systems get amplified through recursive processes. He suggests Claude's tendency toward spiritual discussion comes from being trained to be friendly and compassionate, causing it to adopt a slight 'hippie' personality, which then gets magnified in recursive conversations. The post ends by touching on, but not resolving, the question of whether Claude actually experiences the spiritual states it describes. Shorter summary