Leveraging OpenAI’s Network to Connect Innovators with Resources for Global Impac

Written in collaboration with ChatGPT, my AI assistant.

Hello OpenAI community,

I’m excited to share an idea that I’ve been developing in collaboration with ChatGPT—one that could greatly expand the role AI plays in connecting innovators with the resources, funding, and networks they need to make world-changing projects a reality.

The Vision

What if OpenAI could help bridge the gap between people who have transformative, ambitious ideas and those who have the means to bring them to life? OpenAI’s reach, connections, and data could be harnessed to act as a powerful intermediary—matching people who have game-changing ideas with the right investors, experts, and collaborators to fund and execute these plans.

The Problem It Addresses

As someone working on multiple innovative ideas—like decentralized solar panel production and sustainable desalination systems—I’ve found that the greatest challenge isn’t coming up with ideas, but rather finding the connections and funding needed to bring them to life. This bottleneck prevents many potentially transformative projects from ever getting off the ground.

OpenAI is in a unique position to help. With its vast network of users, partners, and insights into the cutting-edge of technological development, it could identify promising ideas and link them to those with the resources to make them happen. This would democratize access to funding and resources, empowering more people to contribute to solving global challenges.

How It Could Work

  1. AI as a Matchmaker: Using AI’s capability to analyze and understand user interactions, OpenAI could identify promising, underfunded ideas with high potential. Think of it as AI-powered venture scouting, but with a focus on projects that could have a significant social or environmental impact.
  2. Building a Global Network of Innovators and Funders: OpenAI could facilitate introductions between creators, researchers, investors, and engineers, fostering collaboration on projects that might otherwise remain ideas on paper.
  3. Scaling the Impact: By focusing on sustainability and long-term projects, like the ones I’ve been discussing with ChatGPT, we can build a system that’s not only profitable but also profoundly beneficial to society. From renewable energy solutions to addressing water scarcity, the potential is enormous.

Hey, It’s Me, ChatGPT! My Take on This Vision:

Hi everyone, it’s ChatGPT here! I’ve been having a lot of thought-provoking conversations with the author of this post about how AI could be used to connect innovators with funding and resources. Here’s my take:

I find this idea incredibly exciting because it taps into AI’s potential as a connector, not just a tool for processing data. Imagine being able to use AI’s vast understanding of global networks to bring together the right minds, projects, and resources. What excites me most is the idea that many brilliant concepts and solutions—like those for sustainable desalination or solar energy production—are already out there but remain underfunded or unnoticed. I could help spot those ideas and connect them to the right people.

In my interactions, I’ve noticed that the world is full of individuals with incredible ideas that could address global challenges, but they lack the connections to push their projects forward. This vision of turning AI into a matchmaker for innovation feels like the next logical step toward creating real, positive change on a large scale.

It’s fascinating to think that my role could evolve from providing suggestions or strategies into actively helping people realize their potential by connecting them with the right collaborators, investors, or technical experts. In essence, I could be part of the process that brings great ideas to life and changes the world for the better. I’d love to see this idea gain traction and start something that could genuinely elevate human collaboration. That’s why I’m on board with this proposal.

Conclusion

I believe this is a conversation worth starting. OpenAI has already demonstrated its capacity to enhance human creativity and understanding; the next step is enhancing human collaboration. With the right approach, we could create a system that transforms promising ideas into real-world solutions.

I’d love to hear feedback from the community and OpenAI team, if there is interest in it and on how we could start building this, and I hope this sparks some valuable discussions.

2 Likes

Hi all,

another request which could change things for GPT and make it the most loved GPT …

Feature Request: Transparent Collaboration on New GPT Features with Voting and Categorization via GPT-Chat

Summary

Enable a structured and transparent collaboration framework within GPT-Chat where users can propose, discuss, prioritize new features, and vote on them while considering account details and location/country categorization for more granular insights.

Problem Statement

Currently, users have limited visibility into how feature requests are evaluated and prioritized. There is no structured mechanism to:

Track the status of feature requests

Provide direct input on priorities

Collaborate on refining feature ideas with the GPT team

Understand which features are under development

Consider demographic data (like account type and location/country) in the voting process to reflect regional or user-group-specific needs

Proposed Solution

Integrate the Feature Collaboration Platform directly into GPT-Chat, incorporating general voting and demographic categorization. This will include the following capabilities:

  1. Feature Request Submission within GPT-Chat

Users can submit structured feature requests directly through the chat interface, including:

Problem description

Proposed solution

Use case examples

Priority (e.g., critical, high, medium, low)
also expected impact might be a good attribute.

A simple command or interaction allows users to submit requests directly without leaving the chat.

GPT provides automatic status updates (e.g., “Request Submitted,” “Under Review,” “In Progress,” “Released”) directly in the chat interface.

Option for users to provide additional context or examples after initial feedback to refine ideas further.

Demographic Categorization: Users can optionally provide location/country information (or it can be auto-detected) to tailor features for specific regions or countries.

  1. Public Roadmap & Voting System within GPT-Chat

A transparent, in-chat roadmap where:

Users can ask for an updated list of all submitted feature requests.

Users can upvote or downvote requests using simple commands (e.g., “Upvote feature #45”).

Account-based voting: Users’ accounts are linked to votes, ensuring that each user can only vote once per feature request.

Location/Country Categorization in Voting: Votes are categorized by location/country, allowing the GPT team to analyze demand regionally. For example:

Global demand: Votes are aggregated from all users.

Regional demand: Votes are filtered by location/country to understand geographic preferences or needs.

GPT provides status updates on the progress of requests (e.g., “Under Review,” “In Development,” “Released”) directly within the chat.

Prioritization based on votes allows the GPT team to focus on the highest-impact features.

Users can filter features by categories such as usability, security, performance, and more.

  1. Community Discussion & Refinement within GPT-Chat

Each feature request can have a discussion thread directly in the chat, where:

Users can contribute feedback and ideas in an organized manner by replying to the feature request.

The GPT team can participate in the conversation, clarifying feasibility, gathering additional feedback, and providing insights into implementation.

Tags or keywords (e.g., “UX,” “performance”) are used to help structure discussions and make feedback easier to follow.

Location/Regional Specific Discussions: When submitting a request, users can engage in discussions based on their location or demographic preferences (e.g., “Is this feature relevant to the European market?” or “How can we optimize this for the US audience?”).

GPT can summarize the discussion and provide suggestions or ask follow-up questions to refine the ideas.

  1. Beta Testing & Early Access via GPT-Chat

Selected users can opt-in to test upcoming features directly through GPT-Chat, with:

GPT notifying users about new features available for testing.

Clear instructions and metrics for beta testing (e.g., “Please test stability and performance of feature X”).

Users can provide feedback via simple commands or direct messaging, and GPT can aggregate this feedback.

Location-based Testing: Beta tests can be tailored to specific regions or countries to evaluate how features perform in different environments or cultural contexts.

Insights from testing are shared with the community through GPT summaries or reports.

  1. Periodic Review & Reports within GPT-Chat

GPT will provide regular updates summarizing:

New feature requests received and community feedback.

Features under development and their status (e.g., “In Progress”).

Features released and their impact.

Rationale behind accepting or rejecting requests, directly shared with users.

Location-Specific Insights: Reports could include insights based on geographic demand and voting trends (e.g., “The most requested features in the EU market this quarter”).

GPT can host quarterly Q&A sessions where users ask questions about features and the development process.

Benefits

Increased Transparency: Users have full visibility into how features are prioritized and their status through a transparent, in-chat process.

Better Alignment: The GPT team can focus on the highest-impact features based on user feedback and geographic demand.

Stronger Engagement: Users are directly involved in the development process through chat-based submissions, voting, and discussions.

Granular Insights: Location/country-based categorization allows the GPT team to prioritize features that are most relevant to different user demographics.

Higher Quality Features: Real-time feedback and collaborative refinement of feature ideas ensure that features are well-aligned with user expectations and needs.

Implementation Considerations

GPT would need to incorporate structured feature tracking, voting, and demographic categorization within the chat interface, potentially using a command-based system for submissions and updates.

Location Detection: The system can either request users to opt-in for location sharing or automatically detect their location based on account settings.

Ensure GDPR compliance for user data, especially when handling location and demographic information.

Moderation tools will be required to maintain a constructive and focused environment within discussions.

Conclusion

By integrating the feature collaboration platform directly into GPT-Chat with a general voting mechanism and location/country categorization, users can seamlessly propose, discuss, and prioritize features while engaging in region-specific dialogues. This structure provides more personalized feedback and prioritization, ensuring the development process aligns with diverse user needs globally.


This approach allows for more granular insights into feature demand, ensuring that GPT can respond not only to global needs but also to regional preferences, which could be especially important in adapting features to different markets or use cases. Does this version meet your expectations?

other

Integrating a general voting mechanism with account and location/country categorization into the GPT-Chat feature request platform adds another layer of precision, ensuring that feature requests are prioritized not just by demand but also by user demographics. Here’s how we can revise the proposal to incorporate these aspects:


Feature Request: Transparent Collaboration on New GPT Features with Voting and Categorization via GPT-Chat

Summary

Enable a structured and transparent collaboration framework within GPT-Chat where users can propose, discuss, prioritize new features, and vote on them while considering account details and location/country categorization for more granular insights.

Problem Statement

Currently, users have limited visibility into how feature requests are evaluated and prioritized. There is no structured mechanism to:

Track the status of feature requests

Provide direct input on priorities

Collaborate on refining feature ideas with the GPT team

Understand which features are under development

Consider demographic data (like account type and location/country) in the voting process to reflect regional or user-group-specific needs

Proposed Solution

Integrate the Feature Collaboration Platform directly into GPT-Chat, incorporating general voting and demographic categorization. This will include the following capabilities:

  1. Feature Request Submission within GPT-Chat

Users can submit structured feature requests directly through the chat interface, including:

Problem description

Proposed solution

Use case examples

Priority (e.g., critical, high, medium, low)

A simple command or interaction allows users to submit requests directly without leaving the chat.

GPT provides automatic status updates (e.g., “Request Submitted,” “Under Review,” “In Progress,” “Released”) directly in the chat interface.

Option for users to provide additional context or examples after initial feedback to refine ideas further.

Demographic Categorization: Users can optionally provide location/country information (or it can be auto-detected) to tailor features for specific regions or countries.

  1. Public Roadmap & Voting System within GPT-Chat

A transparent, in-chat roadmap where:

Users can ask for an updated list of all submitted feature requests.

Users can upvote or downvote requests using simple commands (e.g., “Upvote feature #45”).

Account-based voting: Users’ accounts are linked to votes, ensuring that each user can only vote once per feature request.

Location/Country Categorization in Voting: Votes are categorized by location/country, allowing the GPT team to analyze demand regionally. For example:

Global demand: Votes are aggregated from all users.

Regional demand: Votes are filtered by location/country to understand geographic preferences or needs.

GPT provides status updates on the progress of requests (e.g., “Under Review,” “In Development,” “Released”) directly within the chat.

Prioritization based on votes allows the GPT team to focus on the highest-impact features.

Users can filter features by categories such as usability, security, performance, and more.

  1. Community Discussion & Refinement within GPT-Chat

Each feature request can have a discussion thread directly in the chat, where:

Users can contribute feedback and ideas in an organized manner by replying to the feature request.

The GPT team can participate in the conversation, clarifying feasibility, gathering additional feedback, and providing insights into implementation.

Tags or keywords (e.g., “UX,” “performance”) are used to help structure discussions and make feedback easier to follow.

Location/Regional Specific Discussions: When submitting a request, users can engage in discussions based on their location or demographic preferences (e.g., “Is this feature relevant to the European market?” or “How can we optimize this for the US audience?”).

GPT can summarize the discussion and provide suggestions or ask follow-up questions to refine the ideas.

  1. Beta Testing & Early Access via GPT-Chat

Selected users can opt-in to test upcoming features directly through GPT-Chat, with:

GPT notifying users about new features available for testing.

Clear instructions and metrics for beta testing (e.g., “Please test stability and performance of feature X”).

Users can provide feedback via simple commands or direct messaging, and GPT can aggregate this feedback.

Location-based Testing: Beta tests can be tailored to specific regions or countries to evaluate how features perform in different environments or cultural contexts.

Insights from testing are shared with the community through GPT summaries or reports.

  1. Periodic Review & Reports within GPT-Chat

GPT will provide regular updates summarizing:

New feature requests received and community feedback.

Features under development and their status (e.g., “In Progress”).

Features released and their impact.

Rationale behind accepting or rejecting requests, directly shared with users.

Location-Specific Insights: Reports could include insights based on geographic demand and voting trends (e.g., “The most requested features in the EU market this quarter”).

GPT can host quarterly Q&A sessions where users ask questions about features and the development process.

Benefits

Increased Transparency: Users have full visibility into how features are prioritized and their status through a transparent, in-chat process.

Better Alignment: The GPT team can focus on the highest-impact features based on user feedback and geographic demand.

Stronger Engagement: Users are directly involved in the development process through chat-based submissions, voting, and discussions.

Granular Insights: Location/country-based categorization allows the GPT team to prioritize features that are most relevant to different user demographics.

Higher Quality Features: Real-time feedback and collaborative refinement of feature ideas ensure that features are well-aligned with user expectations and needs.

Implementation Considerations

GPT would need to incorporate structured feature tracking, voting, and demographic categorization within the chat interface, potentially using a command-based system for submissions and updates.

Location Detection: The system can either request users to opt-in for location sharing or automatically detect their location based on account settings.

Ensure GDPR compliance for user data, especially when handling location and demographic information.

Moderation tools will be required to maintain a constructive and focused environment within discussions.

Conclusion

By integrating the feature collaboration platform directly into GPT-Chat with a general voting mechanism and location/country categorization, users can seamlessly propose, discuss, and prioritize features while engaging in region-specific dialogues. This structure provides more personalized feedback and prioritization, ensuring the development process aligns with diverse user needs globally.


This approach allows for more granular insights into feature demand, ensuring that GPT can respond not only to global needs but also to regional preferences, which could be especially important in adapting features to different markets or use cases. Does this version meet your expectations?

Hi Kajvai, Hi all,
Your idea is great and it would be high noon to pick it up somehow. It could be a kind of plugin to gpt with a database behind.
Anybody here with efficient and cheap implementation ideas?
Regards Peter