Systems and methods of artificial intelligence based recommendation are disclosed herein. The system can include: a user device including: a network interface; and an I/O subsystem. The system can include an artificial intelligence engine that can provide a remediation dialogue. The system can include a content management server that can: receive a user identification identifying a user from the user device; retrieve user information from a memory; identify and deliver a question to the user device based on the retrieved user information; receive a response to the delivered question from the user device; determine that the received response is incorrect; trigger the launch of the artificial intelligence engine; receive an indication of completion of the dialogue; and provide a second question after receipt of the indication of completion of the dialogue.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An artificial intelligence based recommendation system comprising: a user device comprising: a network interface configured to exchange data via the communication network; and an I/O subsystem configured to convert electrical signals to user interpretable outputs via a user interface; an artificial intelligence engine configured to receive inputs from at least the user device and to: launch a dialogue based on the received inputs; identify remediation dialogue based on received user inputs; and terminate the dialogue based on at least one halting criterion; and a content management server, wherein the content management server is configured to: receive a user identification identifying a user from the user device; receive data indicative of a user pattern of interaction; generate a trigger value characterizing the user pattern of interaction; trigger the launch of the artificial intelligence engine; receive an indication of completion of the dialogue; and provide second content after receipt of the indication of completion of the dialogue. 2. The system of claim 1, wherein the content management server is further configured to receive an indication of an updated user skill level with the indication of completion of the dialogue. 3. The system of claim 2, wherein the content management server is configured to select the second content based on the user skill level. 4. The system of claim 3, wherein the remediation dialogue comprises multiple levels of interrogation and response. 5. The system of claim 4, wherein at least some of the levels of interrogation comprise a question and delivered content. 6. The system of claim 5, wherein the delivered content corresponds to the user skill level as identified in a user model at the time of selection of the delivered. 7. The system of claim 6, wherein the delivered content corresponds to a request received from the user as part of the remediation dialogue. 8. The system of claim 6, wherein the artificial intelligence engine is configured to reevaluate the user skill level subsequent to each level of interrogation and response. 9. The system of claim 8, wherein the reevaluation of the user skill level comprises application of a natural language processing algorithm to the received response. 10. The system of claim 9, wherein the natural language processing algorithm comprises at least one of: a speech recognition algorithm; and natural language understanding algorithm. 11. The system of claim 1, wherein launching the dialogue comprises launching a user interface on the user device, wherein the user interface is configured to display dialogue content and receive user responses to the displayed dialogue content. 12. A method for artificial intelligence based content recommendation and provisioning, the method comprising: receiving at a content management server a user identification from a user device, wherein the user identification identifies a user; receiving data indicative of a user pattern of interaction; generating a trigger value characterizing the user pattern of interaction; triggering the launch of an artificial intelligence engine; launching a dialogue based on the received inputs with the artificial intelligence engine; identifying remediation dialogue with the artificial intelligence engine based on received user inputs; terminating the dialogue with the artificial intelligence engine; receiving an indication of completion of the dialogue with the content management server; and delivering second content to the user device after receipt of the indication of completion of the dialogue. 13. The method of claim 12, wherein the dialogue is terminated based on at least one halting criteria. 14. The method of claim 13, wherein the halting criteria comprises a termination threshold, and wherein terminating the dialogue comprises generating a user performance metric indicative of at least one of: a skill level; a correct response; and an incorrect response; and comparing the user performance metric to the termination threshold. 15. The method of claim 12, further comprising: receiving an indication of an updated user skill level with the indication of completion of the dialogue at the content management server. 16. The method of claim 15, further comprising selecting the second content with the content management server, wherein the second content is selected based on the user skill level. 17. The method of claim 16, wherein the remediation dialogue comprises multiple levels of interrogation and response. 18. The method of claim 17, wherein at least some of the levels of interrogation comprise a question and delivered content, wherein the delivered content corresponds to the user skill level as identified in a user model at the time of selection of the delivered content, and wherein the delivered content corresponds to a request received from the user as part of the remediation dialogue. 19. The method of claim 17, further comprising reevaluating the user skill level subsequent to each level of interrogation and response with the artificial intelligence engine. 20. The method of claim 19, wherein reevaluating the user skill level comprises application of a natural language processing algorithm to the received response. 21. The method of claim 20, wherein the natural language processing algorithm comprises at least one of: a speech recognition algorithm; and natural language understanding algorithm. 22. The method of claim 21, wherein launching the dialogue comprises launching a user interface on the user device, wherein the user interface is configured to display dialogue content and receive user responses to the displayed dialogue content. 23. The method of claim 12, further comprising: retrieving with the content management server user information from a memory, wherein the user information identifies progress by the user through a content progression; identifying and delivering a question to the user device based on the retrieved user information; receiving a response to the delivered question from the user device; determining that the received response is incorrect. 24. The method of claim 23, wherein the second content comprises a second question. 25. The method of claim 12, wherein the launch of the artificial intelligence engine is triggered via at least one triggering condition, wherein the triggering condition delineates between patterns of user interaction.