Post by /dev/color

Rigorous research in AI-powered education exists, but getting it into the real-world products serving students every day is a different challenge entirely. That's why we partnered with the Gates Foundation to explore how AI-enabled public goods can bridge the gap between sound research and real-world adoption. In early June, /dev/color deployed 14 senior Technical and Research Fellows to accelerate learnings on what it takes to scale open-source AI public goods designed to support STEM learning. Developed by Stanford University's Ideal Learning Lab and Cornell's National Tutoring Observatory, these research-grounded tools were explored alongside five organizations: Arizona State University, The Concord Consortium, Edmentum, ETS, and Purdue Global. Our model: 🔍 Discovery research with each participating organization to understand real-world contexts: unique tech stacks, AI governance, student populations, and what integration would actually require 🤝 Embedded partnership during three days in Seattle: our Fellows working within each team, supporting technical integration, testing LLM models, prototyping, and capturing real-time signal ⚙️ Pressure testing at the market level: surfacing the blockers, integration requirements, and data and security conditions that stand between promising research and real-world adoption /dev/color goes beyond building a community of technical expertise. We bring industry-leading technical leaders across sectors to ensure that responsible, equitable AI doesn't just get built, but that it's also adopted with mission-aligned communities. Thank you to Nancy Otero and the Gates Foundation, Dr. Shima Salehi and Stanford University's Ideal Learning Lab, the Cornell National Tutoring Observatory, and all participating organizations for your partnership.