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July 1, 2026

Community Update: AI For Good, Geneva

Join the AIEng4D Community at AI for Good Global Summit 2026

Screenshot 2026-07-01 at 8.20.46 AM.png We’re excited to share that members of our community will be contributing to the 2026 AI for Good Global Summit in Geneva this July through a keynote, a Youth Stage talk, and an expert workshop focused on AI engineering, Edge AI, robotics education, and global capacity building.

AI for Good is the United Nations’ leading platform on Artificial Intelligence. Established by the International Telecommunication Union (ITU), the UN agency for digital technologies, AI for Good brings together governments, academia, industry, civil society, and UN partners to unlock AI’s potential to serve humanity through skills, standards, partnerships, and practical AI solutions.

This year, our sessions focus on a question central to our work:

How do we move from AI promise to AI systems that actually work — reliably, sustainably, and equitably — in the real world?

Keynote: AI Engineering for Good: Why Intent Is Not Enough

Speaker: Vijay Janapa Reddi
Date: 8 July 2026
Time: 11:30–12:00 CEST
Location: Town Hall, AI for Good Global Summit, Geneva Link: AI Engineering for Good: Why Intent Is Not Enough

In his keynote, Vijay Janapa Reddi will argue that safe, equitable, and trustworthy AI requires more than ethical intent, regulation, or model performance. It requires engineering capacity. The talk frames AI engineering as a distinct discipline focused on reliability, interpretability, sustainability, and deployment — especially in settings where cost, energy, latency, and connectivity are core constraints.

Youth Stage Talk: The Maker100 Leaders Robotics Framework

Speaker: Jeremy Ellis
Date: 8 July 2026
Time: 13:30–14:00 CEST
Location: Youth Stage, AI for Good Global Summit, Geneva
Link: The Maker100 Leaders Robotics Framework

Jeremy Ellis will present the Maker100 Leaders Robotics Framework, a hands-on, zero-lecture curriculum that helps students build AI engineering intuition through grassroots Edge AI. Using accessible microcontrollers, sensors, actuators, and IoT modules, students connect machine learning predictions to physical systems. The framework is designed to scale from classrooms to small cohorts, including environments with limited internet or specialized instruction.

Expert Workshop: Intelligence at the Edge

Speakers Include: Marco Zennaro, Vijay Janapa Reddi, Thomas Basikolo, and David Cuartielles
Date: 10 July 2026
Time: 09:00–12:15 CEST
Location: Room S, AI for Good Global Summit, Geneva
Link: Intelligence at the Edge

The “Intelligence at the Edge” workshop will explore how Edge AI is changing where intelligence happens. Instead of relying on high-bandwidth cloud connectivity, Edge AI enables models to run directly on local hardware, supporting lower latency, reduced energy use, offline functionality, and stronger data privacy.

The session will cover practical requirements for deploying lightweight machine learning models on resource-constrained devices, with discussion around federated learning, explainability at the edge, sustainable AI, open-source tools, and educational initiatives such as TinyML4D.

Together, these sessions reflect the broader mission we are working toward: expanding access to AI engineering education, supporting educators and learners around the world, and helping build the technical capacity needed for AI systems that are reliable, open, and globally inclusive.

If you’ll be attending AI for Good in Geneva, we would love to see you at these sessions.

If you won’t be attending in person, please note that we’ll also host a special remote Academic Session and community gathering this month focused on growing the academic network and supporting the Global South through AI engineering content. Stay tuned for details on the date and time.

The future of AI for Good depends not only on what we imagine, but on what we can responsibly build.

Screenshot 2026-07-01 at 8.29.25 AM.png


Machine Learning Systems is building the foundation for AI Engineering.
A free, open textbook and community for understanding how AI systems work.

👉 https://mlsysbook.ai

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