CS Colloquium Speaker Speaker: Ari Holtzman, University of Washington Date: Thursday, March 23 Time: 12:30pm EST Location: CS 105 Host: Danqi Chen Event page: https://www.cs.princeton.edu/events/26350 Title: Controlling Large Language Models: Generating (Useful) Text from Models We Don’t Fully Understand Abstract: Generative language models have recently exploded in popularity, with services such as ChatGPT deployed to millions of users. These neural models are fascinating, useful, and incredibly mysterious: rather than designing what we want them to do, we nudge them in the right direction and must discover what they are capable of. But how can we rely on such inscrutable systems? This talk will describe a number of key characteristics we want from generative models of text, such as coherence and correctness, and show how we can design algorithms to more reliably generate text with these properties. We will also highlight some of the challenges of using such models, including the need to discover and name new and often unexpected emergent behavior. Finally, we will discuss the implications this has for the grand challenge of understanding models at a level where we can safely control their behavior. Bio: Ari Holtzman is a PhD student at the University of Washington. His research has focused broadly on generative models of text: how we can use them and how can we understand them better. His research interests have spanned everything from dialogue, including winning the first Amazon Alexa Prize in 2017, to fundamental research on text generation, such as proposing Nucleus Sampling, a decoding algorithm used broadly in deployed systems such as the GPT-3 API and academic research. Ari completed an interdisciplinary degree at NYU combining Computer Science and the Philosophy of Language. Quantum Seminar Speaker Speaker: Kaitlin (Kate) Smith, Super.tech Date: Thursday, March 23 Time: 4:30pm EST Location: B205 EQuad Host: Andrew Houck Event page: https://www.cs.princeton.edu/events/26356 Title: An Architect’s Perspective on Quantum Computer Scaling: Why, What, and How? Abstract: Quantum computation has potential to solve problems that are out of reach for today’s classical computers. Many of the proposed applications for quantum computers (QCs), such as those in chemistry, material science, and optimization, are capable of substantial human impact. However, the full promise of quantum will only be realized if better qubits and QCs emerge that are capable of large-scale computation. The roadmap to QC scaling does not only contain a single path but many that run in parallel. In addition to pursuing devices with more qubits, quantum researchers must 1) co-design software that pushes the frontier of existing machines and 2) build models that guide future QC design toward optimized performance. In this talk, I discuss the why, what, and how involved with scaling today’s QCs. First, I motivate the pursuit of quantum computing and introduce fundamental concepts. Next, I present a case study that explores optimized quantum circuit compilation, reducing decoherence via circuit slack. I show how quantum algorithms can adapt to the unique characteristics of today’s QCs through optimized gate scheduling, leading to significant improvements in success during runtime. In the third part of this talk, hardware challenges that restrict the number qubits on-chip are highlighted. With a focus on fixed-frequency transmon QCs, I explore the viability of modular architectures to scale quantum devices, presenting promising results in terms of yield, gate performance, and application-based analysis. Finally, an outlook is given on future directions in QC software and hardware co-design that aim to accelerate progress toward achieving practical quantum machines. Bio: Kaitlin is a quantum software manager at Super.tech, a software division of Infleqtion. From 2020-2022, she was an IBM and Chicago Quantum Exchange Postdoctoral Scholar in the University of Chicago’s Department of Computer Science, advised by Prof. Fred Chong. Kaitlin is a co-author of the 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA) Best Paper, named a 2021 MIT EECS Rising Star, and the recipient of the 2021 IEEE Computer Society Technical Committee on Multiple Valued Logic (TC-MVL) Kenneth C. Smith Early Career Award in Microelectronics.