Using LLMs to acquire labels for supervised modelsLabeling data is a critical step in supervised machine learning, but it might be costly to acquire large amounts of labeled data.With zero-shot learning and LLMs, we...
One theory as to why that could be is that nonbinary brown people could have had more visibility within the press recently, meaning their images find yourself in the information sets the...
The OpenAI API pricing model is predicated on the variety of tokens generated by the API. Tokens are individual units of text, resembling words or characters, that the API generates in response to a...
A number of canonical and research-proven techniques to adapt large language models to domain specific tasks and the intuition of why they're effective.EpilogueThis blog post provides an intuitive explanation of the common and effective...
What works, the professionals and cons, and example code for every approachIf among the terminology I exploit here is unfamiliar, I encourage you to read my earlier article on LLMs first.There are teams which...
The second test used a knowledge set designed to ascertain how likely a model is to assume the gender of somebody in a selected career, and the third tested for the way much...
We investigate the potential implications of Generative Pre-trained Transformer (GPT) models and related technologies on the U.S. labor market. Using a latest rubric, we assess occupations based on their correspondence with GPT capabilities, incorporating...