뇌인지과학과에서는 다음 주 수요일에 세계적인 석학을 초빙하여 BCS 10-10 Focus Lecture Series 행사를 개최합니다.

Uri Hasson 교수는 인간 두뇌 사이의 커뮤니케이션과 자연 언어 처리 및 발달 과정에서 자연어의 습득 등과 관련된 뇌인지과학적 기전을 연구하는 세계적 석학입니다. 특히 심층 언어 모델을 이론적 틀로 활용하여 인간 뇌의 자연어 처리과정을 모델링하고자 노력하는 연구는 자연지능과 인공지능의 공통점과 차이점에 대한 중요한 통찰을 제공해 줄 것입니다.

관심있는 여러분의 많은 참여를 부탁드립니다.

ㅣ일시 : 6월 11일(수) 오후 4시

ㅣ장소 : 25-1동 국제회의실(1층)

ㅣ연사 : Uri Hasson, Ph.D (Professor, Dept. of Psychology and the Neuroscience Institute, Princeton University)

ㅣ주제 : "Deep language models as a cognitive model for natural language processing in the human brain"

ㅣ초록 : Naturalistic experimental paradigms in cognitive neuroscience arose from a pressure to test, in real-world contexts, the validity of models we derive from highly controlled laboratory experiments. In many cases, however, such efforts led to the realization that models (i.e., explanatory principles) developed under particular experimental manipulations fail to capture many aspects of reality (variance) in the real world. Recent advances in artificial neural networks provide an alternative computational framework for modeling cognition in natural contexts. In this talk, I will ask whether the human brain's underlying computations are similar or different from the underlying computations in deep neural networks, focusing on the underlying neural process that supports natural language processing in adults and language development in children. I will provide evidence for some shared computational principles between deep language models and the neural code for natural language processing in the human brain. This indicates that, to some extent, the brain relies on overparameterized optimization methods to comprehend and produce language. At the same time, I will present evidence that the brain differs from deep language models as speakers try to convey new ideas and thoughts. Finally, I will discuss our ongoing attempt to use deep acoustic-to-speech-to-language models to model language acquisition in children.