Programs and Clusters

This is the second part in a special year-long program on large language models and transformers that spans the 2024–2025 academic year. This program's overarching goal is to try to understand the ongoing revolution in transformers and large language models through a wide lens, in a relaxed setting that facilitates discussion, debate, and intellectual cross-pollination.

This is the first part in a special, yearlong program on large language models and transformers that spans the 2024–2025 academic year. This program's overarching goal is to try to understand the ongoing revolution in transformers and large language models through a wide lens, in a relaxed setting that facilitates discussion, debate, and intellectual cross-pollination.

This program will taxonomize and analyze areas of contemporary machine learning where methods generalize well — meaning they perform eerily well on new inputs, rather than merely performing well on old inputs they were trained on — but for no known mathematical reason.

This extended monthlong reunion is for long-term participants from the program on the Theoretical Foundations of Computer Systems, held in the Spring 2021 semester.

This cluster brings together AI, psychology, and neuroscience researchers dedicated to discovering the pillars of intelligence. The goal is twofold: 1) to understand and model natural forms of intelligence using tools from AI and 2) to build AI grounded in the real world. 

This summer program brings together researchers from various areas of sublinear algorithms to explore new topics, tools, and connections between models, as well as promising future directions for the field.

This program brings together researchers from computer science, physics, chemistry, and mathematics to address current challenges in quantum computing, such as the efficiency of protocols for fault-tolerant quantum computation, scalable proofs of quantumness, demonstrations of quantum advantage, and the development of quantum algorithms.

This program brings together an interdisciplinary group of researchers to explore the frontiers of the theory and practice of error-correcting codes.

This program studies the interaction between logic and the algorithms that they inspire, with applications to databases, complexity theory, and knowledge representation.

This program will bring together researchers in dynamic graphs, sketching, and optimization towards the common goals of obtaining provably faster algorithms, finding new connections between the areas, and making new advances at their intersection. 

The Summer Cluster on Quantum Computing will bring together researchers from academia and industry to explore topics from quantum complexity theory and cryptography to quantum algorithms, error-correction and fault tolerance, and benchmarking.

This program will study new approaches for analysis of functions over the Boolean hypercube and beyond, with the aim of making progress on fundamental problems in complexity, algorithms, and discrete mathematics.

This extended reunion is for long-term participants in the program Satisfiability: Theory, Practice, and Beyond, held in the Spring 2021 semester. It will provide an opportunity to meet old and new friends. Moreover, we hope that it will give everyone a chance to reflect on the progress made during the semester and since, and sketch in which directions the field should go in the future.

This program will bring together researchers in computational complexity, proof complexity, cryptography, and learning theory to make progress on fundamental problems in those areas using the framework of "meta-complexity" — i.e., complexity of computational tasks that are themselves about complexity.

This program aims to develop algorithms for sequential decision problems under a variety of models of uncertainty, with participants from TCS, machine learning, operations research, stochastic control and economics.

This program will bring together experts from various fields to study networks, from graph limits, to modeling and estimation, to processes on networks. Application areas include epidemics, spread of information and other economic and social processes.

This cluster will aim to develop the theoretical foundations of deep learning, particularly the aspects of this methodology that are very different from classical statistical approaches.

This summer program aims to bring together computational and applied researchers to address key challenges in bioinformatics.

Convenes an interdisciplinary group of scholars to develop firm theoretical and philosophical foundations for addressing some major issues concerning the interpretability of machine learning⁠–based models.

This cluster focuses on the growing concerns regarding the future of individuals, groups, societal institutions and values shaped, manipulated, and challenged by the imperatives of AI.