Having an AI assistant to help me work feels incredible. I used to spend my time thinking about how to convey the right tone to feel professional yet personable at the same time. Combing over words with strained eyes to find mistakes is a pain, one that is now avoided thanks to my team of personal AI assistants.
Each AI assistant has a role. Gemini is best for emotionally-intelligent writing. Claude has the greatest creativity. ChatGPT is most likely to be correct with math and coding. Experience-backed testing and prodding at the extremes of the AI's abilities is necessary after each update to see how the new model performs.
Gemini likes to add sporadic spacing. Claude likes to talk about itself (when really not appropriate) with fervor. ChatGPT forgets its instructions after ten rounds.
AI is limited by an entity who feed its data with new learning material. Raw data alone cannot teach an AI. Poor quality data is abundant throughout the internet and from public data. Exceptional Quality Data is paired with actionable advice coming from a structured, personalized review of an AI's performance drawn from raw data.
Here's what it looks like with a real dataset.
To draw insights for this AI model performance, the 50 prompt and response sets are placed into one or more appropriate categories.
Each AI response is given two ratings: a quality rating on a five-point scale and a comparative rating with an equivalent human-written response.
An AI is a developing mind, and a developing mind needs guidance. Personal education, experience, and guidance are the necessary methods for advancement.