According to Andrej Karpathy (@karpathy), nanochat now features a primordial identity and can articulate details about itself—such as being nanochat d32, its $800 cost, and its English language limitations—through synthetic data generation. Karpathy explains that large language models (LLMs) inherently lack self-awareness or a built-in personality, so all such traits must be explicitly programmed. This is achieved by using a larger LLM to generate synthetic conversations that are then mixed into training or fine-tuning stages, allowing for custom identity and knowledge infusion. Karpathy emphasizes the importance of diversity in generated data to avoid repetitive outputs and demonstrates this with an example script that samples varied conversation starters and topics. This customization enables businesses to deploy AI chatbots with unique personalities and domain-specific capabilities, unlocking new customer engagement opportunities and product differentiation in the AI market (Source: x.com/karpathy/status/1980508380860150038).