ChatGPT secrets from the newest $300k salary jobs in finance
– Prompt engineering is a crucial skill that everyone will need to learn to effectively interact with AI language models like ChatGPT.
– A research paper from Stanford University, in collaboration with the University of California, Berkeley, and Samaya AI, reveals that the length of prompts can affect the accuracy of AI model performance.
– Language models like Transformers have a 'context window,' which considers a certain number of words around a keyword when generating responses.
– The study shows a distinctive U curve in model accuracy, where information in the middle of a prompt tends to be disregarded more frequently.
– Increasing the context window size might not solve the issue entirely, as it can lead to a drop in performance when the full prompt doesn't fit in the window.
– Financial institutions, such as Bloomberg and JPMorgan, are hiring AI researchers to explore the potential of AI bots in finance, with salaries upwards of $300k.
– To succeed in roles involving AI bots, understanding how to place important prompt information away from the middle is crucial.
The key takeaway from the web page is that prompt engineering is a critical skill when working with language models like ChatGPT
Bard, and other chatbots. Understanding how to structure prompts can significantly impact the accuracy and performance of AI models.