Andre Carpathy, a founding member of OpenAI, explains in "State of GPT" the process of training GPT, an emerging ecosystem of large language models. It starts with pre-training with large datasets that generate the base model through tokenization and translation. Andre also explains that the power of Llama, a smaller model, is more powerful than GPT3 despite containing fewer parameters. The speaker discusses the training of Transformer models for language modeling, followed by the evolution of base models that have arisen since GPT-2. The training process consists of pre-training, supervised fine-tuning, reward modeling, and reinforcement learning. The speaker also talks about improving the performance of Transformers by prompting them, using self-consistency, and prompt engineering. Finally, the speaker addresses the limitations of LLMs, including biases and reasoning errors, and suggests using them in low-stakes applications with human oversight.