LOW-LATENCY CONVERSATIONAL ARTIFICIAL INTELLIGENCE (AI) ARCHITECTURE WITH A PARALLELIZED IN-DEPTH ANALYSIS FEEDBACK LOOP

1 . A method, comprising:

initiating, by an artificial intelligence executed by one or more processors, a conversation with a human, the artificial intelligence configured to complete a checklist during the conversation;

receiving, by the artificial intelligence, a portion of a first human response from the human;

generating, by the artificial intelligence, multiple possible responses to the portion of the received first human response;

selecting, by the artificial intelligence, based at least in part on receiving additional portions of the first human response from the human, a first artificial intelligence response from the predicted multiple possible responses;

providing, by the artificial intelligence, the first artificial intelligence response to the human; and

based at least in part on determining, by the artificial intelligence, that the checklist has been completed, ending the conversation with the human.

2 . The method of claim 1 , wherein the artificial intelligence includes a safety engine configured to:

based at least in part on determining that a kickout condition has occurred, transfer a conversation between the human and the artificial intelligence to a medical professional; and

provide the medical professional with a text-based summary of the conversation, including why the conversation was initiated and what information the human has provided.

3 . The method of claim 1 , wherein the artificial intelligence includes a task completion engine that is configured to:

complete tasks included in the checklist after discussing a peripheral matter with the human during the conversation.

4 . The method of claim 3 , wherein the peripheral matter comprises answering a question posed by the human.

5 . The method of claim 1 , wherein the artificial intelligence, after receiving the first human response from the human, the method comprises:

providing the first human response to a second artificial intelligence to determine additional factors associated with the human in parallel with providing, by the artificial intelligence, the first artificial intelligence response to the human.

6 . The method of claim 1 , wherein the artificial intelligence is trained using multi-turn reinforcement learning through human feedback (RLHF).

7 . The method of claim 1 , wherein the artificial intelligence includes a retrieval augmented generation (RAG) module configured to access external sources of knowledge to supplement the artificial intelligence.

8 . A server comprising:

one or more processors; and

one or more computer-readable storage media to store instructions executable by the one or more processors to perform operations comprising:

initiating, by an artificial intelligence, a conversation with a human, the artificial intelligence configured to complete a checklist during the conversation;

receiving, by the artificial intelligence, a portion of a first human response from the human;

generating, by the artificial intelligence, multiple possible responses to the portion of the received first human response;

selecting, by the artificial intelligence, based at least in part on receiving additional portions of the first human response from the human, a first artificial intelligence response from the predicted multiple possible responses;

providing, by the artificial intelligence, the first artificial intelligence response to the human; and

based at least in part on determining, by the artificial intelligence, that the checklist has been completed, ending the conversation with the human.

9 . The server of claim 8 , wherein generating, by the artificial intelligence, multiple possible responses to the portion of the received first human response comprises:

predicting one or more possible human responses; and

predicting one or more answers, individual answers of the one or more answers corresponding to individual responses of the one or more possible human responses.

10 . The server of claim 8 , wherein the artificial intelligence comprises a tone detection module to:

determining a tone of utterances of the human;

correlate the tone with a particular mood; and

adjust, based on the particular mood, an audio data output by the artificial intelligence.

11 . The server of claim 10 , wherein determining the tone of the utterances comprises:

determining a pitch of the utterances;

determining a volume of the utterances;

determining a particular word in the utterances determining a particular phrase in the utterances; or

any combination thereof.

12 . The server of claim 10 , wherein adjusting the audio data output of the artificial intelligence comprises:

changing a pitch of the audio data output by the artificial intelligence;

changing a volume of the audio data output by the artificial intelligence;

inserting a particular word into the audio data output by the artificial intelligence;

inserting a particular word into the audio data output by the artificial intelligence; or

any combination thereof.

13 . The server of claim 8 , wherein after receiving, by the artificial intelligence, the first human response from the human, the operations comprise:

providing the first human response to a second artificial intelligence to determine additional factors associated with the human in parallel with providing, by the artificial intelligence, the first artificial intelligence response to the human.

14 . The server of claim 8 , wherein the checklist comprises at least one of:

verifying an identity of the human;

confirming a date and a time of a visit to a medical facility;

providing an arrival time associated with the visit;

providing information about an arrival site associated with the visit;

checking for conditions that, when present, may cause the visit to be delayed;

confirming procedures to travel to and from the medical facility;

providing information as to what can and cannot be consumed by the human prior to the visit;

reviewing preparation instructions associated with the visit;

providing a call back number;

summarizing next steps;

outputting at least a portion of the conversation in a form suitable for input to an electronic health records (EHR) platform; or

any combination thereof.

15 . A non-transitory memory device to store instructions executable by one or more processors to perform operations comprising:

initiating, by an artificial intelligence, a conversation with a human, the artificial intelligence configured to complete a checklist during the conversation;

receiving, by the artificial intelligence, a portion of a first human response from the human;

generating, by the artificial intelligence, multiple possible responses to the portion of the received first human response;

selecting, by the artificial intelligence, based at least in part on receiving additional portions of the first human response from the human, a first artificial intelligence response from the predicted multiple possible responses;

providing, by the artificial intelligence, the first artificial intelligence response to the human; and

based at least in part on determining, by the artificial intelligence, that the checklist has been completed, ending the conversation with the human.

16 . The non-transitory memory device of claim 15 , wherein the artificial intelligence engages in a task that includes one or more of:

a preventative screening;

a intake-related task;

a scheduling-related task;

a pre-op related tasks;

a discharge-related task;

a chronic care related task; or

any combination thereof.

17 . The non-transitory memory device of claim 15 , wherein the operations further comprise:

incorporating, by the artificial intelligence, one or more conversational strategies comprising open-ended questions, feedback loops, active listening techniques, or any combination thereof.

18 . The non-transitory memory device of claim 15 , wherein the operations further comprise:

determining, by the artificial intelligence, that the human exhibits mild cognitive impairment; and

employing one or more adaptive techniques comprising using a simplified language, using a visual aid, repeating information, summarizing information, providing reminders, or any combination thereof.

19 . The non-transitory memory device of claim 15 , wherein generating, by the artificial intelligence, multiple possible responses to the portion of the received first human response comprises:

predicting one or more possible human responses; and

predicting one or more answers, individual answers of the one or more answers corresponding to individual responses of the one or more possible human responses.

20 . The non-transitory memory device of claim 15 , the operations further comprising:

outputting at least a portion of the conversation in a form suitable for input to an electronic health records (EHR) platform; and

complying with relevant healthcare regulations, including Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR).