Open Discussion: Bi-Directional Prompting (aka, agency or intent)

[Mario4272]

I've been thinking about this for a while now. How can we make it so that the model has the ability to prompt us or initiate conversations?

[Mario4272]

I have found a few things in the way of "answers" to how this might be approached. So I created this discussion to get the folks here thinking about how this may be accomplished.

Negative:
oobabooga/text-generation-webui#3848

Positive:
GenAI Response:
Building an AI Model to Initiate Conversations
Building an AI model capable of initiating engaging conversations requires a multi-pronged approach. Here's a breakdown of the key steps:
1. Define the Goal and Scope:
Purpose:
What kind of conversations should the model initiate? (e.g., casual, informative, customer service)
Target Audience:
Who will the model be interacting with? (e.g., specific demographics, interests)
Context:
Where will the conversations take place? (e.g., online chat, social media, virtual assistant)
2. Data Acquisition and Preprocessing:
Collect large amounts of conversational data relevant to the chosen purpose and audience.
Clean and pre-process the data, including removing noise, identifying keywords, and labeling intents.
3. Model Selection and Training:
Choose a suitable AI model architecture, such as a recurrent neural network (RNN) or a transformer-based model.
Train the model on the preprocessed data, focusing on aspects like topic identification, sentiment analysis, and natural language generation.
4. Conversation Flow Design:
Define the structure of the conversation, including opening lines, response strategies, and techniques to keep the user engaged.
Implement mechanisms for handling user interruptions, irrelevant responses, and maintaining context across multiple interactions.
5. Evaluation and Refinement:
Evaluate the model's performance through user testing and feedback.
Continuously refine the model by adjusting parameters, adding more data, and incorporating new conversation strategies.
Additional Considerations:
Personality and Tone:
Imbue the model with a specific personality and tone to suit the target audience and context.
Humor and Creativity:
Incorporate humor and creative language generation to make the conversations more engaging.
Ethical Considerations:
Ensure the model is unbiased, respectful, and avoids generating harmful or offensive content.
Available Tools and Platforms:
Google Dialogflow CX: Provides pre-built conversation flows and tools for building custom conversational experiences.
Microsoft Azure Bot Service: Offers a comprehensive platform for building, deploying, and managing conversational AI solutions.
Amazon Lex: A service for building conversational interfaces powered by deep learning.
By following these steps and leveraging available tools, you can build an AI model capable of initiating natural and engaging conversations.