Allyson Ettinger's guest appearances

Allyson Ettinger

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

NLP Highlights

Scientific Sense ®

Burr Settles

Hal Daumé III

Emily Bender

Sebastian Ruder

Thomas Wolf

Sameer Singh

Ines Montani

Alona Fyshe

Hal Daumé

Tim Rocktäschel

Marion Nestle

Sanmi Koyejo

Chelsea Finn

Dario Amodei

Jianxiong Xiao

OwlTail

Today we continue our ICLR ‘21 series joined by Allyson Ettinger, an Assistant Professor at the University of Chicago. One of our favorite recurring conversations on the podcast is the two-way street that lies between machine learning and neuroscience, which Allyson explores through the modeling of cognitive processes that pertain to language. In our conversation, we discuss how she approaches assessing the competencies of AI, the value of control of confounding variables in AI research, and how the pattern matching traits of Ml/DL models are not necessarily exclusive to these systems. Allyson also participated in a recent panel discussion at the ICLR workshop How Can Findings About The Brain Improve AI Systems?, centered around the utility of brain inspiration for developing AI models. We discuss ways in which we can try to more closely simulate the functioning of a brain, where her work fits into the analysis and interpretability area of NLP, and much more!The complete show notes for this episode can be found at twimlai.com/go/483. 

Today we continue our ICLR ‘21 series joined by Allyson Ettinger, an Assistant Professor at the University of Chicago. One of our favorite recurring conversations on the podcast is the two-way street that lies between machine learning and neuroscience, which Allyson explores through the modeling of cognitive processes that pertain to language. In our conversation, we discuss how she approaches assessing the competencies of AI, the value of control of confounding variables in AI research, and how the pattern matching traits of Ml/DL models are not necessarily exclusive to these systems. Allyson also participated in a recent panel discussion at the ICLR workshop <a href="https://iclrbrain2ai.github.io/" rel="nofollow" target="_blank">How Can Findings About The Brain Improve AI Systems?</a>, centered around the utility of brain inspiration for developing AI models. We discuss ways in which we can try to more closely simulate the functioning of a brain, where her work fits into the analysis and interpretability area of NLP, and much more!The complete show notes for this episode can be found at <a href="https://twimlai.com/go/483" rel="nofollow" target="_blank">twimlai.com/go/483</a>.

What the Human Brain Can Tell Us About NLP Models with Allyson Ettinger - #483

Brain waves and Natural Language Processing,  N400 amplitude and vector space model behavior,  Contextual embeddings in words, Composition in Sentence Vector Representations, and BERT, what it is Not. Dr. Allyson Ettinger is a computational linguist and an assistant professor in the Department of Linguistics at the University of Chicago, working on natural language processing and computational cognitive modeling. Her interdisciplinary work draws on methods and insights from cognitive science, linguistics, and computer science to examine meaning-extraction and predictive processes executed during language processing in humans and in artificial intelligence systems.   ---   Send in a voice message: https://podcasters.spotify.com/pod/show/scientificsense/message Support this podcast: https://podcasters.spotify.com/pod/show/scientificsense/support

Brain waves and Natural Language Processing,  N400 amplitude and vector space model behavior,  Contextual embeddings in words, Composition in Sentence Vector Representations, and BERT, what it is Not. Dr. Allyson Ettinger is a computational linguist and an assistant professor in the Department of Linguistics at the University of Chicago, working on natural language processing and computational cognitive modeling. Her interdisciplinary work draws on methods and insights from cognitive science, linguistics, and computer science to examine meaning-extraction and predictive processes executed during language processing in humans and in artificial intelligence systems. --- Send in a voice message: <a href="https://podcasters.spotify.com/pod/show/scientificsense/message" rel="nofollow" target="_blank">https://podcasters.spotify.com/pod/show/scientificsense/message</a> Support this podcast: <a href="https://podcasters.spotify.com/pod/show/scientificsense/support" rel="payment nofollow" target="_blank">https://podcasters.spotify.com/pod/show/scientificsense/support</a>

Dr. Allyson Ettinger, Assistant professor in the Department of Linguistics at the University of Chicago

Sudha Rao

How robust is your NLP system? High numbers on common datasets can be misleading, as most systems are easily fooled by small modifications that would not be hard for humans to understand. Allyson Ettinger, Sudha Rao, Hal Daumé III, and Emily Bender organized a workshop trying to characterize this issue, inviting participants to either build robust systems, or try to break them with targeted examples. Allyson and Sudha come on the podcast to talk about the workshop. We cover the motivation of the workshop, what a "minimal pair" is, what tasks the workshop focused on and why, and what the main takeaways of the workshop were.https://www.semanticscholar.org/paper/Towards-Linguistically-Generalizable-NLP-Systems-A-Ettinger-Rao/8472e999f723a9ccaffc6089b7be1865d8a1b863

How robust is your NLP system? High numbers on common datasets can be misleading, as most systems are easily fooled by small modifications that would not be hard for humans to understand. Allyson Ettinger, Sudha Rao, Hal Daumé III, and Emily Bender organized a workshop trying to characterize this issue, inviting participants to either build robust systems, or try to break them with targeted examples. Allyson and Sudha come on the podcast to talk about the workshop. We cover the motivation of the workshop, what a "minimal pair" is, what tasks the workshop focused on and why, and what the main takeaways of the workshop were. <a href="https://www.semanticscholar.org/paper/Towards-Linguistically-Generalizable-NLP-Systems-A-Ettinger-Rao/8472e999f723a9ccaffc6089b7be1865d8a1b863" rel="nofollow" target="_blank">https://www.semanticscholar.org/paper/Towards-Linguistically-Generalizable-NLP-Systems-A-Ettinger-Rao/8472e999f723a9ccaffc6089b7be1865d8a1b863</a>

45 - Build It, Break It workshop, with Allyson Ettinger and Sudha Rao