Nuclear fusion using magnetic confinement, in particular in the tokamak configuration, is a
promising path towards sustainable energy. A core challenge is to shape and maintain a high-…

Inspired by progress in large-scale language modeling, we apply a similar approach towards
building a single generalist agent beyond the realm of text outputs. The agent, which we …

Generative AI systems produce a range of risks. To ensure the safety of generative AI
systems, these risks must be evaluated. In this paper, we make two main contributions toward …

This paper investigates how generative AI can potentially undermine the integrity of collective
knowledge and the processes we rely on to acquire, assess, and trust information, posing …

Generative AI systems produce a range of ethical and social risks. Evaluation of these risks
is a critical step on the path to ensuring the safety of these systems. However, evaluation …

We provide a framework for incorporating robustness -- to perturbations in the transition
dynamics which we refer to as model misspecification -- into continuous control Reinforcement …

Advances in algorithmic fairness have largely omitted sexual orientation and gender identity.
We explore queer concerns in privacy, censorship, language, online safety, health, and …

Queerness and queer people face an uncertain future in the face of ever more widely
deployed and invasive artificial intelligence (AI). These technologies have caused numerous …

Collecting and automatically obtaining reward signals from real robotic visual data for the
purposes of training reinforcement learning algorithms can be quite challenging and time-…

Robots must know how to be gentle when they need to interact with fragile objects, or when
the robot itself is prone to wear and tear. We propose an approach that enables deep …