Artificial intelligence with the efficiency of natural intelligence
PI: Carl Vondrick
Co-PI: Jianbo Shi, UPenn; Nikolaus Kriegeskorte, Columbia
Abstract
Today's AI vision systems have memorized an astonishing range of information and patterns. When given infinite computing power, the danger of AI is that it can override logic. For many ordinary tasks, this logic override is rare, since models are trained on vast amounts of data and have effectively memorized the answers. However, when faced with an unfamiliar or complex task, this pattern-checking style of learning turns against them, and AI resorts to hallucination, while humans can reason on the fly: resample the environment to gather information, efficiently balancing between checking and looking (searching).
Publications
- Yang, H., Xu, K., Lu, A., Grossberg, M., Bai, Y., & Shi, J. (2026). Vibe Spaces for Creatively Connecting and Expressing Visual Concepts. CVPR 2026. Poster. https://arxiv.org/html/2512.14884v1
- Lu, A., Liao, W., Wang, L., Yang, H., & Shi, J. (2025). Artifacts and Attention Sinks: Structured Approximations for Efficient Vision Transformers. arXiv. https://doi.org/10.48550/ARXIV.2507.16018
- Yang, H., Gee, J., & Shi, J. (2024). AlignedCut: Visual Concepts Discovery on Brain-Guided Universal Feature Space. arXiv. https://doi.org/10.48550/ARXIV.2406.18344
Resources
In progress
