The New Language Model Stack

Before we know it, saying a product “uses AI” will seem as silly and obvious as saying a product “uses a database.” Today, the average developer might not know how a query planner works, but they definitely use a database. Similarly, we don’t expect the average developer in five years to know how a transformer works. But we guarantee they will know... See more

Transformers and NLP more generally are still nascent in application today but will likely be a crucial wave over the next 5 years. As the models scale and natural language understanding grows stronger one can expect the enterprise to be transformed. Much of the world of an enterprise is effectively pushing around bits of language - legal contracts... See more

So right now, LLMs (Large Language Models) are all the rage. But in the future, it’s possible that the way we get things done is composing things with a combination of LLMs, SMMs (Small, Mighty Models), agents and tools.

It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).

This is how we... See more

The existence of AI models means that openness is a bigger liability for user-generated content companies. The existence of a successful company in some category indicates demand for the content, so these are the easiest business models to drop into AI. "Quora, but there's no cold-start problem because our LLM can offer an instant answer" is one of... See more

Interface > Data > Model: The “interface” and “data” layers will further distinguish market leaders while the “models” layer becomes increasingly commoditized and pushed to the edge. As a growing number of our everyday use-cases of powerful GenerativeAI models fall below the frontier of “the best models,” they will be enabled by cheaper commoditize... See more