Visualization is vital for understanding complex data, but existing tools require “tidy data,” adding extra steps. Learn how Data Formulator transforms concepts into visuals, promoting collaboration between analysts and AI agents.
This research paper was presented at the 29th ACM Symposium on Operating Systems Principles (opens in new tab) (SOSP 2023), the premier forum for the theory and practice of computer systems software. For millennia, data has woven itself into every facet of our lives, from…
In this issue: Kosmos-2.5: A Multimodal Literate Model; Can vine copulas explain complex relationships of weather variables; New system accelerates the adaptive training process; Structural inequalities and relational labor in the influencer industry.
This position research paper was presented at the 26th ACM Conference on Computer-Supported Cooperative Work and Social Computing (opens in new tab) (CSCW 2023), a premier venue for research on the design and use of technologies that affect groups, organizations, and communities. In the business…
This paper received the outstanding benchmarks track paper award during NeurIPS 2023 (opens in new tab). How trustworthy are generative pre-trained transformer (GPT) models? To answer this question, University of Illinois Urbana-Champaign, together with Stanford University, University of California, Berkeley, Center for AI Safety, and…
Research Focus: Principal researcher Lester Mackey recognized for pioneering statistical and ML techniques; Pareto frontiers in neural feature learning; structural inequality in the influencer industry; new research on cardinality estimation.
A persistent challenge in deep learning is optimizing neural network models for diverse hardware configurations, balancing performance and low latency. Learn how SpaceEvo automates hardware-aware neural architecture search to fine-tune DNN models for swift execution on diverse devices.
HoloAssist is a new multimodal dataset consisting of 166 hours of interactive task executions with 222 participants. Discover how it offers invaluable data to advance the capabilities of next-gen AI copilots for real-world tasks.
A diverse research ecosystem is essential to realizing the promise of AI. Accelerate Foundation Models Research aims to expand access to powerful models, engaging academics outside of computer science to pursue a broad range of important opportunities.
Chunked prefills & decode-maximal batching boost LLM inference; DragNUWA combines text, image, and trajectory for fine-grained video content control; reconstructing images from human brain signals; structural inequalities in creator-audience relationships.
Microsoft researchers are introducing AutoGen, a framework for simplifying the orchestration, optimization, and automation of workflows for large language model (LLM) applications—potentially transforming and extending what LLMs can do.
This research paper was presented at the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (opens in new tab), a premier forum for advances in the theory and practice of reasoning under uncertainty. In the field of reasoning under uncertainty, probabilistic…
