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AI Advance 2: AI Data, Feedback, and Optimizations

Self-Optimizing Infrastructure for Global Personal Growth

(2:10 reading time)
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AI Data Reliability Issues: Scientists' confusion, poisoning AI training data, lack of data

AI Pain Point:

AI’s reliability issues arise because scientists do not understand and cannot explain how LLMs work, using AI’s open output poisons AI training causing model collapse, and there is insufficient new high quality AI training data.

Data Lifecycle: Continuous optimization of AI assistance through real-world interactions

Expandiverse IP Advance:

Expandiverse IP’s data lifecycle continuously optimizes AI assistance with visible “quantitative funnels” that use real-world interactions to optimize content, choices, and solutions — continuously improving accuracy, safety, and quality.

Optimizations use quantitative funnels and anonymous data
Low-Cost Computing: Lookups of proven 'best solutions' produce efficiency and effectiveness

The Big Idea:

Expandiverse IP continuously enhances the content and choices that AI presents privately across a user’s devices, learns from their interactions, and clearly reports each user’s progress toward their goals.

How does Self-Optimization work? Expandiverse IP’s quantitative funnels enhance AI with anonymous data from real interactions, to continuously improve content and choices for user goals, increasing real-time speed, personalization, and effectiveness.

What’s the Difference? This approach employs low-cost computing lookups of proven “best solutions” instead of generating new uncontrollable AI responses. This personalizes the AI experience across devices and accelerates its real-time speed — while growing its accuracy, safety, and user satisfaction.

Aligns AI solutions with users’ goals, ensuring personalization and improving outcomes. AI cost reduction from less reliance on data centers and increasing on-device processing.

aI's next level:

Here’s how Active Knowledge drives real-time insights and user empowerment:

  • User Goals Automation: Aligns AI solutions with users’ goals, ensuring personalization and improving outcomes.
  • Real-Time Data Insights: Learns from real-world user interactions to produce continuous improvements.
  • Cost Reduction: Reduces reliance on data centers by increasing and optimizing on-device processing, increasing privacy while reducing environmental impact.
  • Personalized Progress: Reports individual achievements and remaining gaps, enhancing user engagement, gamification, and satisfaction.

The Big Picture: Expandiverse IP transforms AI into a scalable people-first platform, driving personal and global growth.

Monetization:

Struggling with unreliable AI data? Expandiverse IP’s data lifecycle turns this problem into new revenue streams by aligning AI solutions with users’ personal goals, to turn user choices into transactions:

  • Data-Driven Revenues: With a continuous improvement loop for AI solutions driven by user interactions, increasingly accurate and effective solutions create deeper connections between people’s wants and responsive vendors.
  • Market-Leading Data Insights: Expandiverse IP learning provides vendors with insights derived anonymously from goals-focused users, enhancing these vendors’ competitive offerings and relationships.
  • Personalized AI Solutions: These tailored AI solutions and services adapt to user desires, providing higher satisfaction and retention rates.
  • AI-Powered Innovating: Expandiverse IP ecosystems provide data-accelerated innovations, producing tailored products and services that fit evolving user needs.
Continuous improvement loop for AI solutions: Driven by private user interactions. Deeper connections between people’s wants and solutions presented
Inclusive personal growth for all drives sustainable private markets at world scale

Scenarios:

Explore the broad potential of real-world data impacts on the climate crisis:

  • User Scenario: A user chooses sustainable food as a goal and switches to eco-friendly grocery products and sees their impact, then shares the goal on social media for others to adopt.
  • Business Scenario: Food companies track sustainability goals and collective market transitions, prioritizing the right sustainable features to stay in front of consumer trends and grow market share.
  • Global Scenario: Industry leaders see the growing sustainability competition and its impact on market shares, prompting major industry shifts toward more sustainable products, and major business shifts toward a more sustainable economic system.

The Bottom Line: 

Integrating Expandiverse IP enables AI providers to solve data challenges and reduce AI costs, by helping lift billions daily — kick-starting a Global AI Renaissance.

Connect with us today to explore how Expandiverse IP can transform AI data challenges into new revenue streams with global opportunities.

Benefits for AI provider: Solving data challenges and reducing AI costs lifts the world, with opportunities for billions of transactions in private markets

For more on the Expandiverse IP quantitative process, see the AI Revenues page.

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Personal Goals

Dan Abelow,
Expandiverse Innovator and Founder

3-minute Bio: Click to view full size

 

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