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Mission and objectives
The UNDP Sustainable Energy Hub is a network of partners that work alongside countries to transform energy systems though an integrated agenda focused on the policy, technology and financial shifts that shape sustainable economic development. We help countries build net-zero, people-centered societies driven by a just, sustainable energy transition. Our core principle is to promote an integrated agenda that supports energy for development, including by mobilizing partners to enable 500 million additional people to have access to sustainable, reliable, affordable energy by 2025, leaving no-one behind. The global transformation of energy systems has already started, but is being altered by the current geopolitical context. However, this transformation must be accelerated, and it must be done in a way that advances the Sustainable Development Goals. The Sustainable Energy Hub is UNDP’s answer to these challenges. To drive the systems-level change needed, the Sustainable Energy Hub aims to bring about a completely new way of thinking, doing business, connecting people and knowledge. UNDP’s 2022-2025 Strategic Plan has put sustainable energy at the heart of a joint corporate mission, and UN-Energy has pledged to reaching key energy milestones by 2025. UNDP will focus efforts on mobilizing partners and catalzing action to provide access to sustainable, affordable, and reliable energy – both electricity and clean cooking – to 500 million people by 2025, focusing on the world’s poorest communities. UNDP will not do this alone – our role here is to mobilize strong, meaningful, impactful partnerships to deliver action on the ground. We aim to bring about a new way of thinking about energy and advocate for an integrated, inclusive approach, where all stakeholders participate meaningfully in its design.
Context
In the pursuit of sustainable energy solutions and informed decision-making, the Sustainable Energy AI in development by the UNDP Sustainable Energy Hub combines recent advances in LLMs with a robust energy knowledge graph to create a powerful new tool to support access to insights on energy. The Energy AI synthesizes insights from a comprehensive database of compiled publications, national policies, real-time APIs, and a database of indicators. This approach can provide access to knowledge and intelligence which can empower policymakers, researchers, and development practitioners with accurate, transparent, and contextually rich information for technical capacity-building and data-driven decision-making.The AI is an ensemble model with access to a compilation of resources and datasets, rather than an LLM only approach. This approach provide advantages and limitations. Rather than a single language model that can provide text responses directly to queries, this approach involves more steps to first identify the most relevant documents and datasets within the database, directly access this information, augment it with insights from the curated knowledge graph, and then compile an answer from these results. This allows a more targeted approach to respond to certain user needs and provide answers directly linked to the original literature, which increases transparency and ability to cite sources and allows a more mechanistic approach to building a model to respond to a very specific set of types of questions for certain stakeholders.
Task description
The Sustainable Energy Hub team is looking for an online volunteer to support with web developmentfor theEnergy Moonshot AI, a new online too for interacting with a database of documents and datasets through a language interface. This AI tool is designed to support stakeholders in sustainable energy through access to the most recent information and insights. The ideal candidate for this position has experience in frontend development especially in single page application built using ReactJs. Our tool is already far along so the primary assignment is to advance the tool by adding new features, visual components, and functionality as we develop new backend components of our Retrieval Augmented Generation AI framework.
