I believe we are nearing the upper limits of large language models, as the future will likely involve many smaller, specialized models rather than a few large ones. We're at the upper end of large language models, and they're rapidly becoming a commodity as they mature.

We're in a period of high uncertainty regarding the evolution of AI model capabilities, particularly in multimodality, which will continue to improve.

Elon Musk mentioned that we're seeing a 100x increase in computational and algorithmic efficiencies per year, which aligns with the progress we've made in large language models over the past two years.

We've entered the era of 'Software 3.0,' where large language models (LLMs) serve as a new kind of computer, programmed in English.

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

Future breakthroughs in large language models will likely include extending context windows, allowing for more information to be processed and enhancing capabilities.

The AI field is approaching diminishing returns with large language models, as the amount of natural text data available for training is becoming limited, which may hinder future advancements.

The fundamental work we're doing involves taking natural language and transforming it into structured output, which became possible in mid-2024.

Developers are increasingly finding that a significant portion of their code is being generated by large language models, which raises questions about the future impact of these models on society.