What Kind of Computation is Human Cognition? A Brief History of Thought (Episode 2/2)
Since the naming of the field in 1956, AI has been dominated first by symbolic rule-based models, then early-generation neural (or “connectionist”) models, then probabilistic models operating over symbolic structures, and now deep learning models. The next generation of models, many of us suspect, will be neurosymbolic systems. Projecting the future of the field is aided by understanding the forces that drive this swing of the pendulum between symbolic and neural representation, forces that have their origins in antiquity. In this 2-part series, this struggle for dominance in approaches to modeling intelligence will be viewed in the historical context of the dialectic in theories of human cognition that has opposed empiricist and rationalist perspectives. This is actually just one of over a dozen oppositions in theories of intelligence that collectively define the search space in which cognitive theory development plays out.
(These lectures were commissioned as a 2-hour synopsis of a course: Foundations of Cognitive Science. They do not present current research, but are primarily pedagogical.)
- 日期:
- 演讲者:
- Paul Smolensky
- 所属机构:
- Microsoft Research
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Paul Smolensky
Partner Researcher
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Sean Andrist
Principal Researcher
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系列: Microsoft Research Talks
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Decoding the Human Brain – A Neurosurgeon’s Experience
Speakers:- Pascal Zinn,
- Ivan Tashev
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Galea: The Bridge Between Mixed Reality and Neurotechnology
Speakers:- Eva Esteban,
- Conor Russomanno
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Current and Future Application of BCIs
Speakers:- Christoph Guger
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Challenges in Evolving a Successful Database Product (SQL Server) to a Cloud Service (SQL Azure)
Speakers:- Hanuma Kodavalla,
- Phil Bernstein
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Improving text prediction accuracy using neurophysiology
Speakers:- Sophia Mehdizadeh
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DIABLo: a Deep Individual-Agnostic Binaural Localizer
Speakers:- Shoken Kaneko
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Recent Efforts Towards Efficient And Scalable Neural Waveform Coding
Speakers:- Kai Zhen
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Audio-based Toxic Language Detection
Speakers:- Midia Yousefi
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From SqueezeNet to SqueezeBERT: Developing Efficient Deep Neural Networks
Speakers:- Sujeeth Bharadwaj
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Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
Speakers:- Monojit Choudhury
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'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
Speakers:- Peter Clark
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Checkpointing the Un-checkpointable: the Split-Process Approach for MPI and Formal Verification
Speakers:- Gene Cooperman
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Learning Structured Models for Safe Robot Control
Speakers:- Ashish Kapoor
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