By allowing models to think longer, large language models can leverage more compute on the fly, enhancing their intelligence for complex problems.

The new technology of large language models is creating unprecedented opportunities for startups, enabling tasks that previously required extensive research teams to be accomplished more easily.

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.

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.

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

With the release of GPT-3, it seems the sky is the limit for this new paradigm of scaling large language models.

Large language models should be referred to as large event models because they are not only effective in language but also applicable in pharmaceuticals and various other fields.

As we scale large language models (LLMs), we will eventually encounter a data wall, which limits the effectiveness of current scaling techniques.

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