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EFTA01121228 | EFTA01121230 All of these systems (and many more like them) would: • observe a user as he or she works online - tracking both what the user is doing and parsing user-entered information • proactively offer help, advice, and feedback as appropriate, drawing from a memory of expert and peer experience • query the user when his or her preferences or actions are ambiguous • answer questions, especially in response to system-provided advice • expand its knowledge base by posing questions it cannot answer to external human experts and automatically adding their responses to its memory • learn the user's specific preferences and tailor the interaction accordingly. Such an Interactive Intelligent Advisor would be a "real" Al system that could learn who its user is and what they are doing, and respond appropriately in light of the user's needs, actions, and preferences. All or these Advisors will be based on a general Al architecture comprising mechanisms for comprehending natural language, maintaining a world model, and accessing expert advice and experience. This architecture can be instantiated to create specific Advisors for a range of domains. Through use, each advisor learn more about its users and its domain, improving the quality of help and advice it provides. We would welcome the opportunity to tell you more about our vision and our experience. EFTA01121230
May 10, 2026 at 3:22 AM