Opening — Why this matters now For decades, modeling and simulation lived in a world of equations, agents, and carefully bounded assumptions. Then large language models arrived—verbose, confident, and oddly persuasive. At first, they looked like narrators: useful for documentation, maybe scenario description, but not serious modeling. The paper behind this article argues that this view is already outdated. ...
Finance may seem like the crown jewel of modern institutions—replete with contracts, algorithms, and global markets. But what if its deepest logic predates banks, money, and even language? In a compelling new paper, Finance as Extended Biology (arXiv:2506.00099), Egil Diau argues that the cognitive substrate of finance is not institutional architecture but reciprocity—a fundamental behavioral mechanism observed in primates and ancient human societies alike. Credit, insurance, token exchange, and investment, he contends, are not designed structures but emergent transformations of this ancient cooperative logic. ...
Social simulations are entering their uncanny valley. Fueled by generative agents powered by Large Language Models (LLMs), recent frameworks like Smallville, AgentSociety, and SocioVerse simulate thousands of lifelike agents forming friendships, spreading rumors, and planning parties. But do these simulations reflect real social processes — or merely replay the statistical shadows of the internet? When Simulacra Speak Fluently LLMs have demonstrated striking abilities to mimic human behaviors. GPT-4 has passed Theory-of-Mind (ToM) tests at levels comparable to 6–7 year-olds. In narrative contexts, it can detect sarcasm, understand indirect requests, and generate empathetic replies. But all of this arises not from embodied cognition or real-world goals — it’s just next-token prediction trained on massive corpora. ...