On the Modeling Capabilities of Large Language Models for Sequential Decision Making

Large pretrained models are showing increasingly better performance in reasoning and planning tasks across different modalities, opening the possibility to leverage them for complex sequential decision making problems. In this paper, we investigate the capabilities of Large Language Models (LLMs) for reinforcement learning (RL) across a diversity of interactive domains. We evaluate their ability to …

Transforming how AI systems perceive human hands

Making Artificial Intelligence systems robustly perceive humans remains one of the most intricate challenges in computer vision. Among the most complex problems is reconstructing 3D models of human hands, a task with wide-ranging applications in robotics, animation, human-computer interaction, and augmented and virtual reality. The difficulty lies in the nature of hands themselves, often obscured …

Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts

What distinguishes robust models from non-robust ones? While for ImageNet distribution shifts it has been shown that such differences in robustness can be traced back predominantly to differences in training data, so far it is not known what that translates to in terms of what the model has learned. In this work, we bridge this …

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How Kyndryl integrated ServiceNow and Amazon Q Business

This post is co-written with Sujith R Pillai from Kyndryl. In this post, we show you how Kyndryl, an AWS Premier Tier Services Partner and IT infrastructure services provider that designs, builds, manages, and modernizes complex, mission-critical information systems, integrated Amazon Q Business with ServiceNow in a few simple steps. You will learn how to …