Large language models, like ChatGPT, demonstrate that language can self-generate based on its internal structure, indicating that the principles governing human language generation may be the same as those in these models.

Large language models like ChatGPT can answer questions, write stories, and engage in conversation, but to build a business using this technology, you need to customize it for your specific use case to differentiate it from existing solutions.

Generative AI and large language models, like ChatGPT, are incredibly powerful technologies that will soon become even more powerful.

One major challenge with pre-trained models like ChatGPT is their tendency to confidently generate incorrect information, which can mislead users into trusting their outputs.

The evolution of language models, particularly with the introduction of GPT-3, has demonstrated a significant leap in their ability to perform language tasks, even though they do not possess real-world knowledge.

Research indicated that previous models like GPT-3 were undertrained; despite their size, they hadn't been trained on enough text to reach their full potential. For instance, Chinchilla, a model smaller than GPT-3, outperformed larger models by being trained on four times more data.

I believe that if Tesla were tasked with creating a large language model, it would outperform existing models like ChatGPT, given our computing power and resources.

The project that led to ChatGPT began as Web GPT, which utilized retrieval to provide information and cite sources, ultimately evolving into ChatGPT due to its unique dialogue capabilities.

The emergence of large language models has allowed us to create a conversational partner that we couldn't build before, enhancing the user experience.