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

Large language models, like ChatGPT, are trained on vast amounts of text data, allowing them to generate human-like responses.

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

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.

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.

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.

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.

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

I think a reasoning model trained around physics would do what Elon is describing, and I salute him for leading the way in areas like Grok language models that allow interaction in ways big companies never would.