Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
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27 - What do Neural Machine Translation Models Learn about Morphology?, with Yonatan Belinkov
Manage episode 182282356 series 1452120
Content provided by NLP Highlights and Allen Institute for Artificial Intelligence. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by NLP Highlights and Allen Institute for Artificial Intelligence or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
ACL 2017 paper by Yonatan Belinkov and others at MIT and QCRI. Yonatan comes on to tell us about their work. They trained a neural MT system, then learned models on top of the NMT representation layers to do morphology tasks, trying to probe how much morphological information is encoded by the MT system. We talk about the specifics of their model and experiments, insights they got from doing these experiments, and how this work relates to other work on representation learning in NLP. https://www.semanticscholar.org/paper/What-do-Neural-Machine-Translation-Models-Learn-ab-Belinkov-Durrani/37ac87ccea1cc9c78a0921693dd3321246e5ef07
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Manage episode 182282356 series 1452120
Content provided by NLP Highlights and Allen Institute for Artificial Intelligence. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by NLP Highlights and Allen Institute for Artificial Intelligence or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
ACL 2017 paper by Yonatan Belinkov and others at MIT and QCRI. Yonatan comes on to tell us about their work. They trained a neural MT system, then learned models on top of the NMT representation layers to do morphology tasks, trying to probe how much morphological information is encoded by the MT system. We talk about the specifics of their model and experiments, insights they got from doing these experiments, and how this work relates to other work on representation learning in NLP. https://www.semanticscholar.org/paper/What-do-Neural-Machine-Translation-Models-Learn-ab-Belinkov-Durrani/37ac87ccea1cc9c78a0921693dd3321246e5ef07
…
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Similar to NLP Highlights
Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
…
continue reading
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…
continue reading
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…
continue reading
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…
continue reading
Unseeable forces control human behavior and shape our ideas, beliefs, and assumptions. Invisibilia—Latin for invisible things—fuses narrative storytelling with science that will make you see your own life differently.
…
continue reading
Artificial Intelligence has suddenly gone from the fringes of science to being everywhere. So how did we get here? And where's this all heading? In this new series of Science Friction, we're finding out.
…
continue reading
We humans could have a bright future ahead of us that lasts billions of years. But we have to survive the next 200 years first. Join Josh Clark of Stuff You Should Know for a 10-episode deep dive that explores the future of humanity and finds dangers we have never encountered before lurking just ahead. And if we humans are alone in the universe, if we don't survive intelligent life dies out with us too.
…
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