Hippo AI Foundation

Hippo AI's regenerative AI framework aims to eliminate global health inequalities and promote equilibrium to the global digital health economy. This is in stark contrast to the extractive AI that has fueled information asymmetries due to our dependence on platforms. Embracing Hippo AI enables healthcare providers to leverage state-of-the-art medical AI technology, resulting in enhanced autonomy and increased efficiency.

You can follow Regenerative AI developments here.

The application of open-source principles in the industry parallels the concept of open science in the scientific community. Hippo AI operates as a collaborative AI development and governance framework that utilizes open-source practices. This approach has gained widespread adoption in the global software industry and serves as a powerful engine for digital innovation while fostering digital sovereignty.

Hippo AI advocates for common ownership of medical AI models and their artefacts. This will nurture equality and generate more possibilities for individuals and communities to apply these tools to local economies. By providing access to the source code, individuals and communities can gain a better understanding of how AI models function, resulting in a boost in innovation and the development of new local tools and applications, without increasing dependencies. This approach empowers communities to take charge of their own healthcare needs and advances the progress of medical AI for the common good.

The Hippo AI Foundation encourages corporations to prioritize social responsibility and ethical conduct by investing in data-sharing and open-sourced medical AI. By doing so, companies can contribute to the Regenerative AI principles and receive health data solidarity (offsetting) certificates that reflect their impact in terms of Quality Adjusted Life Years (QALYs) gained and the number of patients reached (Social Impact).

Additionally, Hippo AI promotes reusability in AI development which leads to more efficient projects, reduced duplication of work, and minimized resource wastage, all of which have a positive effect on environmental concerns (Ecological Impact).