Infrastructure

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ADVANCE AND ENHANCE YOUR INFRASTRUCTURE NOW

Science for research & development and the advancement of human-centered infrastructure.

MACHINE LEARNING X DOING INFRASTRUCTURE

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THE FUTURE OF BUILDING IS NOW

Machine Learning X Doing Infrastructure for rigorous data-driven design, social impact and extending basic services to the last mile

Machine learning and AI are powerful innovations, with implications on building and sustaining infrastructure in a more cost-effective way than ever before.

Machine Learning X Doing Infrastructure focuses on using data, ethics and social impact to responsibly improve all infrastructure for everyone. What we need to change the world is AI based on what it means to be human.

AI must lead to data-driven infrastructure and help improve human productivity, standards of living, and community well-being: all in a cost-effective manner.

Next-level AI focuses on integrating the nuances of human behaviors into infrastructural decision making to keep policy makers ahead of issues using best-in-class ethics principles.

By anticipating community concerns and quantifying impact, policy makers have the insights needed to prioritize, finance, deploy and manage infrastructure to be financially sustainable.

That potential is here now. Next-level AI

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It is up to us all to make the world a better place, starting with the infrastructural impact of your organization

Introducing the next-generation of AI, designed around the fundamental question of what it means to be human

Together, we will inspire change in the world, by first introducing your organization to its true potential

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Kweku Opoku-Agyemang, Ph.D.


Kweku Opoku-Agyemang, Ph.D., is former faculty at the University of California, Berkeley in development economics and a former computer science researcher at Cornell University. He has advised Google scientists, given talks at Facebook, presented to government officials from 12 countries and others.

A former session Chair at the Canadian Economic Association, Kweku believes that his next-generation Machine Learning x Doing approach can help organizations and countries to do better by their people by meeting or exceeding their potential. He is based in Toronto, Canada.