According to Andrej Karpathy on X, Simile launched a platform focused on exploring the native personality space of large language models instead of fixing a single crafted persona, enabling multi-persona interactions for richer dialogue and alignment testing. As reported by Karpathy, this under-explored dimension could power differentiated applications in customer support, creative writing, market research, education, and agent orchestration by dynamically sampling and composing diverse LLM personas. According to Karpathy’s post, he is a small angel investor, signaling early expert validation and potential access to top-tier LLM stacks for experimentation. The business impact includes improved user engagement via persona diversity, lower prompt-engineering costs through reusable persona templates, and better safety evaluation by stress-testing models against varied viewpoints, according to Karpathy’s announcement.