The future of AI may involve models communicating in a more efficient, nuanced language that humans cannot easily understand.

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 shift from language processing to planning and strategy in AI indicates that future systems will manage entire business processes autonomously, communicating with each other in English.

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

Large language models are becoming significantly larger and smarter, with AI labs adopting a strategy of scaling more parameters, data, and compute to improve model performance.

Achieving human-level AI will not be possible by merely scaling up existing large language models; a fundamental shift in approach is necessary to reach that goal.

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.

The evolution of programming languages and tools will continue, and AI will likely play a role in shaping that future, especially if natural language can be used in programming, which opens the door for many more people to become programmers and leads to a significant increase in software creation and maintenance needs.

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.