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...
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...
The model relies on Meta AI’s LLaMA and stays significatively smaller than GPT-3.5.Despite the impressive capabilities of Alpaca, the model still exhibits among the classic limitations of instruction following models akin to toxicity, hallucinations...
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...
OpinionIs GPT-4 the following big step in AI we were all waiting for?While I used to be scrolling this countless stream of tweets, the words of Sam Altman, CEO of OpenAI, were floating in...
We’ve trained language models which can be a lot better at following user intentions than GPT-3 while also making them more truthful and fewer toxic, using techniques developed through our alignment research. These InstructGPT models, that...