The next wave of innovation is being shaped by AI systems that don’t just respond; they act. From agentic AI that collaborates and makes decisions autonomously to decentralized architectures that push intelligence to the edge, MIT researchers are leading the charge. They are reimagining how organizations secure, interpret, and operationalize data. This track brings together thought leaders from across MIT to explore the strategic, organizational, and human implications of AI at scale. Topics will include quantum-safe infrastructure, explainable AI, cyber-physical resilience, agent-based platforms, and the role of trust, transparency, and ethics in intelligent systems. For enterprises navigating an era defined by autonomy, agility, and risk, this track connects frontier research with real-world impact.
As AI becomes increasingly autonomous and decentralized, global enterprises must rethink how intelligence is built, governed, and scaled. This closing discussion brings together corporate, academic, research, and entrepreneurial perspectives to explore practical strategies for integrating agentic and distributed AI systems across complex organizations. Attendees will gain insight into how leading thinkers are addressing questions of trust, transparency, and control, balancing innovation with accountability to create resilient, adaptive, and competitive enterprises in a future defined by intelligent autonomy.
Generative programming is a paradigm that takes decades of theoretical research and practical experience in algorithms and software engineering and applies it to the way we interact with LLMs. Instead of developing prompts by trial and error, which usually results in long and complex prompts, generative programs combine known and well-tested control flows and design patterns, such as divide and conquer, with short, consumable prompts. I will describe Mellea, an open-source library for writing generative programs, replacing brittle prompts with structured, maintainable, robust, and efficient AI workflows. I will then discuss some challenges and proposed solutions for efficiently handling multiple models and LLMs’ internal memory management within a generative program.
Life sciences are no longer confined to the realm of biology—they have evolved into a multidisciplinary frontier. This session examines the dynamic intersection of biology, engineering, and computational science, where bold ideas give rise to transformative innovation. By integrating AI, advanced technologies, and foundational biological research, the session will highlight how cross-disciplinary collaboration accelerates the path from scientific discovery to real-world application at MIT. Emphasizing the translation of visionary research into impactful solutions, this track invites participants to reimagine what becomes possible when disciplines converge to shape the future.
Antibody–drug conjugates (ADCs) are the gold standard for targeted drug delivery systems, but their chemical design imposes constraints that, if addressed, could enable a new generation of cancer therapeutics and imaging modalities. For example, due to bioconjugation limitations, the payload scope of ADCs is restricted to highly potent payloads with inherently unselective mechanisms of action, leading to narrow therapeutic windows and resistance. This seminar will introduce a new platform called Antibody–Bottlebrush prodrug Conjugates (ABCs) that can potentially address these challenges. ABCs feature a modular design that allows drug-to-antibody ratios (DARs) from ~1–135 while maintaining strong target binding, efficient cellular uptake, and favorable pharmacokinetics and biodistribution. Leveraging their capability to access very high DARs, ABCs can carry payloads (e.g., 10-fold less potent than existing ADC payloads) that are insufficiently potent to be used in traditional ADCs, thereby enabling new mechanisms-of-action. Moreover, ABCs are readily amenable to using various payload combinations, release mechanisms, and non-drug (e.g., imaging) agents. ABCs display efficacies on par with or superior to clinical ADCs in preclinical tumor models at clinically relevant payload doses, motivating their further clinical translation.
Global electricity demand is projected to nearly double by 2050, driven by the rapid electrification of buildings, transportation, and manufacturing. Compounding this pressure is the exponential growth of AI. While AI offers transformative potential across industries, it is also emerging as a significant energy consumer. Data centers, the digital engines powering AI, have more than doubled their electricity consumption since 2018 and now account for 4.4% of global demand. In the U.S., they are expected to consume up to 12% of total electricity by 2028.
This track will explore how the world can meet rising energy needs through the rapid expansion of sustainable energy production. From fusion and next-generation nuclear to renewables, grid-scale storage, decentralized systems, and forward-looking policies, we will examine the innovations and frameworks critical to building a resilient, low-carbon energy future. Addressing this challenge will require a bold vision, accelerated technological advancement, and unprecedented global collaboration.
Building on Principal Research Scientist Charles Forsberg’s research in advanced reactors and high-temperature energy systems, this talk highlights base-load nuclear reactors replacing the gas turbine to provide dispatchable electricity and heat to industry. There are two strategies. The first strategy stores heat from the reactor when low demand for dispatchable heat to industry or dispatchable electricity. Heat storage may exceed 200 hours. The second strategy converts low-price electricity into high-temperature (1700 °C) heat stored in firebrick. Air flows through the firebrick to provide hot air to industry or thermodynamic topping cycles for nuclear reactors, so that peak power is more than twice the base-load electricity output. Both options are enabled by recent inventions and developments.
Sergey Paltsev will explore the future of sustainable energy in a “power-hungry” world, focusing on the interplay between global energy systems, economic forces, and climate policy. Drawing on integrated global economic modeling, his talk will examine pathways for decarbonization, technology deployment, and policy interventions that can balance energy demand, environmental constraints, and economic growth. Attendees will gain insights into how strategic decisions at the intersection of technology, policy, and economics can shape a sustainable energy future.
Engineering principles and biological insights can open up new capabilities for biotechnology. This talk will highlight two solutions to challenges faced in improving patient care. First, applying basic principles in chemical engineering to the limitations in blood-based cancer diagnostics today led to new approaches to enhance the amounts of cell-free DNA recovered using a novel 'enhancing agent' similar to contrast agents used in other diagnostics. Second, leveraging biological insights to recast the engineering operations required to enable small biomanufacturing systems for distributed and lower capital-intensive production.
Contact
Assistant