Dis-Cover AI Minds to Preserve Human Knowledge

Modern AI technologies make use of statistical learners that lead to self-empiricist logic, which, unlike human minds, learned non-symbolic representations. Nevertheless, it seems is not the right way progress in AI. The structure symbols—the operations by which intellectual solution realized—and search for strategic reference points evoke important issues analysis Studying how knowledge can be represented through methods theoretical generalization and empirical observation only latest step a long process evolution. For many years, humans, seeing language as innate, have carried out symbolic theories. Everything skipped ahead with advent Machine Learning. In this paper, after history, rule-based learning-based vision, we would investigate syntax possible meeting point between different learning Finally, propose new vision models based on combination rules, learning, knowledge.