I've seen a lot of "GPT detection" products floating around lately. Sebastian discusses some of the products and their approaches in this article. Some products claim to have developed an "algorithm...
Brex wrote a nice beginner guide on prompt engineering.
A low-effort quality-of-life improvement for oncall has been starting a week-long shift on a Friday instead of a Monday. Beginning a weekend with oncall isn't the best, but it's more than offset by...
LMQL is a SQL-like programming language for interacting with LMs. It takes a declarative approach to specifying the output constraints for a language model, with a SQL flavor.
marvin's @ai_model decorator implements something similar to what I had in mind for extracting structured data from an input to a language model.
Restricting the next predicted token to adhere to a specific context free grammar seems like a big step forward in weaving language models into applications.
Using system prompts provides an intuitive separation for input and output schema from input content.
With the support of GPT-4, I feel unstoppable. The overnight surge in productivity is intoxicating, not for making money or starting a business, but for the sheer joy of continuously creating ideas...
I wrote a few paragraphs disagreeing with Paul's take, asserting that, like Simon suggests, we should think of language models like ChatGPT as a “calculator for words”.