Abstract: A majority of existing research in large language models and generative AI systems focuses on scaling and engineering. In this talk, I argue that…
Abstract: Today, access to high-quality data has become the key bottleneck to deploying machine learning. Often, the data that is most valuable is locked away…
Abstract: As babies, we begin to grasp the world through spontaneous observations, gradually developing generalized knowledge about the world. This foundational knowledge enables humans to…
Abstract: We consider the problem of sorting a set of items having an unknown total order by doing binary comparisons of the items, given the…
Abstract: AI has revolutionized the way we interact online. Despite this, it hasn't quite made the leap when it comes to tasks like cooking dinner…
Abstract: The emergence of powerful, ever more universal models such as ChatGPT, and stable Diffusion, made generative modeling (GM) undoubtedly a focal point for modern…
Abstract: Large language models (LLMs) have soared in popularity in recent years, thanks to their ability to generate well-formed natural language answers for a myriad…
Abstract: Balancing performance and safety are crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but…
Abstract: Massive scale has been a recent winning recipe in natural language processing and AI, with extreme-scale language models like GPT-4 receiving most attention. This…
Abstract: When robots are to be deployed over long time scales, optimality should take a backseat to “survivability”, i.e., it is more important that the…
Abstract: Acoustic imaging leverages sound to form visual products with applications including biomedical ultrasound and sonar. In particular, synthetic aperture sonar (SAS) has been developed…
Abstract: In this talk, we will delve into the multifaceted challenge of multi-agent deployment for critical applications such as area surveillance, wireless communication coverage, and…