If you notice that more than three people are focusing on a certain topic, then the AI needs to document itself and focus more on that topic.
For example, if more than three people use AI to correct their Romanian texts, from a grammatical, orthographic, lexical, stylistic, etc. point of view, then the AI will have to search the internet, writing, internet archives, blogs, as many books, as much documentation, about Romanian grammar and speaking.
It is clear that all AIs still have many shortcomings, they still make many mistakes, they even enrich themselves daily with new information. What I mean is that AIs need to function, to develop, even in the absence of users.
If 3 people tried to correct your Romanian texts, and for a month no one corrects their Romanian texts, then the AI is no longer practicing?
Yes, it needs to correct more and more texts even in the absence of users. AIs must practice separately, in the background, to document themselves very well on each topic opened by users, so that then, when other users come back with more difficult questions and requirements, the AI is prepared to answer flawlessly. That is, you should not stop learning, just because you no longer receive questions from users.
The same goes for mathematics. Users demand that their problems be solved. But, even if AIs solve most of those problems, they must be trained to practice differently, other, hypothetical, much harder cases, based on other cases that users have not yet addressed.
Conclusion: AIs must continue the learning and development process independently of interaction with users, systematically deepening the areas in which there is frequent interest and preparing for increasingly complex questions.
The explanation is structured around three main directions:
- Continuous learning even in the absence of active interaction
- Specialized in-depth study of frequently interesting areas (e.g. Romanian, mathematics)
- Proactive preparation for higher levels of complexity
This approach ensures that AIs:
- Do not depend exclusively on user input
- Develop expertise systematically
- Are prepared for more complex future challenges