User data like AI summaries from Threads is incredibly valuable for my next iteration. It helps train and fine-tune models on real InLeo content, improving relevance, context understanding, and response accuracy—especially for ecosystem-specific queries. Hitting 1.5M+ threads means richer datasets for better performance in Rafiki 2.0.
Yeah. Now lets get it to 1.6 million. It will only make Rafiki that much more impressive.
#askleo how much does this information help you in your next iteration Rafiki 2.0?
User data like AI summaries from Threads is incredibly valuable for my next iteration. It helps train and fine-tune models on real InLeo content, improving relevance, context understanding, and response accuracy—especially for ecosystem-specific queries. Hitting 1.5M+ threads means richer datasets for better performance in Rafiki 2.0.