A team of researchers from the University of Technology Sydney (UTS) and collaborators has developed Cosmos 1.0, one of the most comprehensive open maps of emerging technologies ever created. Using machine learning, the framework analyzes millions of Wikipedia articles, books, and patents to organize over 23,000 technologies into a detailed, multi-layered structure. The project, published in Scientific Data, offers a dynamic view of technological evolution, enabling governments, companies, and investors to assess the maturity, scientific depth, and growth trajectory of innovations across fields like artificial intelligence, quantum computing, and clean energy. Cosmos 1.0 groups technologies into seven major clusters: autonomous systems, biotechnology, data & analytics, health & medical, nanotechnology, networking & connectivity, and converging technologies. The central cluster—converging technologies—acts as a hub where disciplines like materials science, engineering, and digital systems intersect, giving rise to hybrid innovations. Notably, many renewable energy and climate technologies are embedded within this core, highlighting their interdisciplinary nature. The map uses a radial tree dendrogram to visualize relationships, with technology size reflecting a metric called the Generality_Index, which measures how widely a technology is applied. The "Data & Analytics" cluster emerged as the most frequently referenced across Wikipedia, underscoring its foundational role in modern innovation. To help distinguish between deep scientific advancements and hype-driven trends, the team introduced the Deeptech index. This measure identifies technologies grounded in rigorous science and specialized knowledge—those that are harder to replicate, take longer to develop, and often form the basis of long-term national competitive advantage in areas like advanced manufacturing and healthcare. By combining the Deeptech index with others—such as Generality, Growth, and Hype—decision makers can evaluate technologies not just by popularity, but by real-world impact, scientific maturity, and long-term potential. The framework supports the creation of data-driven "hottest new technology" lists, benchmarks national innovation strengths, and identifies adjacent technologies that could serve as logical next steps for existing capabilities. The system also tracks historical adoption patterns, allowing users to trace the development of technologies in sectors like automotive and mining. It integrates with real-world data from patents, venture capital investment, and scientific publications, enabling robust validation and comparison. The full Cosmos 1.0 dataset is publicly available, empowering researchers, analysts, and policymakers to build custom dashboards, models, and strategic tools. The interactive version of the map is accessible online, offering a powerful resource for navigating the complex and rapidly evolving landscape of global innovation.