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The future of materials science lies in the seamless integration of molecular precision, functional performance, and nanoscale understanding. This session brings together leading MIT researchers whose work spans the full spectrum of advanced materials innovation—from the bottom-up design of molecular architectures to the real-world deployment of materials and the tools that reveal their behavior at the atomic scale.
Modern-day transmission electron microscopes show us the position and nature of the individual atoms within a material. But better still, we can record movies that show how atoms are rearranged during chemical reactions. This is especially relevant to energy-related materials, where energy storage is often accompanied by changes in atomic configuration; in microelectronics, where processing must create precisely defined nanostructures; in structural materials such as cement during hydration, and in quantum materials, where the details of atomic structure determine how well a qubit will work. Through these and other examples, I will show how time-resolved electron microscopy helps us develop new materials and optimize the performance of materials we already know.
The Agentic Web holds transformative promise for the democratization of AI, serve as antidote to AGI and unlock trillions of dollars of economic benefits. But it faces threats of fragmentation and centralization as the Internet of AI Agents evolves. Universal interoperability, permissionless innovation, and user sovereignty over data and agents will require transparent protocols and rapid advances to reconcile the needs of a diverse field.
Networked AI Agents in Decentralized Architecture (NANDA) at MIT offers a three-phase roadmap for this emerging landscape. Phase 1 establishes foundation elements—secure agent identity, discovery indices, and interoperability—via open protocols designed to support trust and accountable governance. Phase 2 introduces economic structures such as knowledge pricing, decentralized marketplaces, and reputation-based transactions, enabling agents to coordinate and exchange value at scale. Phase 3 aims for the emergence of agent societies, fostering large-scale co-learning, adaptive population models, and collaborative networks to tackle complex real-world tasks.
This framework is informed by academic work from the Raskar Lab, including algorithmic advances in Automated Machine Learning (AutoML) tailored for distributed health data, split learning for privacy-preserving model training, formal methods for dynamic knowledge valuation, and techniques for co-learning and collaborator selection in decentralized settings. Ensuring the agentic web remains open, safe, and transparent, NANDA’s development builds upon open standards, participatory governance, and research-driven safeguards.
Growing satellite constellations in Low Earth Orbit are taking advantage of the lower cost of launch and commercial electronics and components. They leverage intersatellite connectivity and increased onboard compute capability to improve communications and Earth observations. We discuss overcoming the challenges of the space environment and enabling technologies for the future, such as laser communications, dynamic tasking algorithms, direct to cellular, and in-space robotic assembly.