Throwing Down the Visual Intelligence Gauntlet

Type
Book Chapter

Authors
Tan, Cheston
Leibo, Joel Z.
Poggio, Tomaso

Date
2013

Abstract
In recent years, scientific and technological advances have produced artificial systems that have matched or surpassed human capabilities in narrow domains such as face detection and optical character recognition. However, the problem of producing truly intelligent machines still remains far from being solved. In this chapter, we first describe some of these recent advances, and then review one approach to moving beyond these limited successes – the neuromorphic approach of studying and reverse-engineering the networks of neurons in the human brain (specifically, the visual system). Finally, we discuss several possible future directions in the quest for visual intelligence.

Citation
Tan C, Leibo JZ, Poggio T (2013) Throwing Down the Visual Intelligence Gauntlet. Studies in Computational Intelligence: 1–15. Available: http://dx.doi.org/10.1007/978-3-642-28661-2_1.

Acknowledgements
This report describes research done at the Center for Biological & Computational Learning, which is in the McGovern Institute for Brain Research at MIT, as well as in the Dept. of Brain & Cognitive Sciences, and which is affiliated with the Computer Sciences & Artificial Intelligence Laboratory (CSAIL). This research was sponsored by grants from DARPA (IPTO and DSO), National Science Foundation (NSF-0640097, NSF-0827427), AFSOR-THRL (FA8650-05-C-7262). Additional support was provided by: Adobe, Honda Research Institute USA, King Abdullah University of Science and Technology grant to B. DeVore, NEC, Sony and especially by the Eugene McDermott Foundation.

Publisher
Springer Nature

Journal
Studies in Computational Intelligence

DOI
10.1007/978-3-642-28661-2_1

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