Building a pipeline of AI talent and projects requires technical as well as educational merit. For this, AI centres of excellence led by world-renowned scientific advisors are necessary. Stronger AI ecosystems emerge when government to grassroots initiatives get involved. AI ecosystems materialize as value networks. They redesign the entry margin for stakeholders to start their journey into AI, offering them a path to participate.

The US's new National AI Research Resource aims to provide a shared computing and data infrastructure. The AI hub is intended to democratize access and help to fuel research and development. Lessons learned in the US can support global AI innovation across the public and private sectors.

In a government AI value network, there are eight stakeholders that include upstream resources, downstream channels and resource providers supporting a shared goal to build the next generation of talent to populate ecosystems. To effectively execute government AI strategies, we must solve the AI education problem where those with and without an AI education need a pathway to achieve their goals. A virtual platform can operationalize government and grassroots AI policies to build talent by creating connections and sharing knowledge that benefits the whole ecosystem.

There’s a demand for a generation of workers skilled in AI, and it’s my mission to build that by focusing on 3 areas: 1. Operationalizing Federal, State, & Local Govt AI strategies. 2. Building a pipeline of talent & projects as a Government to Grassroots AI value network. 3. Redesigning the entry margin into AI & allowing the non-consumers of AI to participate.

Effectively developing a national strategy on privacy-preserving data sharing and analytics, and associated policy initiatives requires: 1. Operationalizing the strategy at a Federal, State, & Local Government using a software / infrastructure layer. 2. Building a pipeline of talent & projects as a Government to Grassroots AI value network to execute on this strategy. 3. Redesigning the entry margin for verified stakeholders, marginalized and underrepresented groups along with the non-consumers to have a way to participate

El nuevo National AI Research Resource (Recurso Nacional de Investigación sobre Inteligencia Artificial) de EE. UU. pretende proporcionar una infraestructura informática y de datos compartida. El centro de IA pretende democratizar el acceso y contribuir a impulsar la investigación y el desarrollo. Las lecciones aprendidas en EE. UU. pueden servir de apoyo a la innovación mundial en IA en los sectores público y privado.