Large language models (LLMs) are primarily designed to regurgitate information based on statistical patterns in the text they've been trained on, which limits their ability to invent new concepts or solutions.

The introduction of large language models (LLMs) provides a language interface for robots, allowing for easier task descriptions and enabling robots to perform generic tasks more effectively.

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

The advancements in large language models (LLMs) have enabled a language interface for robots, allowing them to perform a wider range of tasks more efficiently, such as laundry folding and packing egg crates.

Large Language Models (LLMs) are not effective for predictions; combining them with machine learning models enhances enterprise accuracy.

As LLMs evolve, they are increasingly seen as complex operating systems rather than simple utilities, shaping a new software ecosystem.

The future of software development will involve rewriting a significant amount of code, with LLMs acting as utilities and operating systems.

Many highly skilled professionals are leaving their jobs to start new ventures because they believe large language models (LLMs) are powerful tools for innovation.

The traditional large language models (LLMs) were perceived to be stagnating, but DeepSeek's release has injected new life into the field.