Karpathy joins rivals, local AI doomed

• Simile's models are based on data from hundreds of thousands of study participants, with plans to scale to 8 billion population-level simulations[1] • The platform uses generative agents trained on real human data to simulate individual and collective behavior with claimed high accuracy[4] • Current applications include earnings call rehearsal, litigation outcome modeling, and policy change testing[4] • Simile's approach differs fundamentally from local LLMs: it focuses on behavioral simulation rather than language generation or inference optimization[1][4] • Karpathy's 'agentic engineering' concept involves AI agents autonomously writing code with human oversight, distinct from local LLM inference[2][3]

Karpathy's Simile venture represents a pivot toward large-scale societal simulation rather than competition with local LLM ecosystems. The distinction between population-behavior simulation and local language models suggests the Reddit post may mischaracterize the competitive landscape. Karpathy's continued emphasis on 'agentic engineering' and agent-based systems indicates the AI industry is moving toward orchestrated multi-agent architectures rather than monolithic model approaches, which could reshape how both cloud and local AI systems are deployed[1][2][3]