Following our series of CIMCYC sessions which kicked off last Thursday, 27th March 2025, we are pleased to announce our next AI, Mind and Brain session where we will be discussing the paper whose reference is below. It will certainly be an excellent occasion to share different impressions and reflect on insightful approaches regarding the main topic.
Reference: Sucholutsky, I., Muttenthaler, L., Weller, A., Peng, A., Bobu, A., Kim, B., Love, B.C., Grant, E., Achterberg, J., Tenenbaum, J.B., Collins, K.M., Hermann, K.L., Oktar, K., Greff, K., Hebart, M.N., Jacoby, N., Zhang, Q., Marjieh, R., Geirhos, R., Chen, S., Kornblith, S., Rane, S., Konkle, T., O’Connell, T.P., Unterthiner, T., Lampinen, A.K., Muller, K., Toneva, M., & Griffiths, T.L. (2023). Getting aligned on representational alignment. ArXiv, abs/2310.13018. https://arxiv.org/pdf/2310.13018
This paper is rather long, so you will be expected to read at least part of it (no need to read in detail the entire piece, although you are more than welcome to do so). There is also an available podcast for you to have a general idea of the topic.
Proposed questions to reflect on:
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How might the representational alignment framework facilitate collaboration and methods exchange between cognitive science, neuroscience, and machine learning in the study of information processing systems?
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Given the current limitations in representational alignment, which are the most important future research areas to advance their application to artificial intelligence and the modeling of cognitive and neural systems?
No prior experience in AI is needed –just curiosity and a willingness to discuss ideas. Save the date!
Date: Wednesday, April 23rd, 2025
Location: Seminario 4 - CIMCYC
Time: 10.00 am
Join us online too!: bit.ly/3YsIOqT
Upcoming sessions:
Thursday, May 8th, 2025 - Time-resolved Neuroimaging (EEG +) Session: to be decided.
Thursday, May 22nd, 2025 - AI, Mind and Brain Session: A large-scale examination of inductive biases shaping high-level visual representation in brains and machines (Concrete example with implications for the family of DNNs).