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Imagine, for example, an AI that’s trained to identify cows in images. Ideally, we’d want it to learn to detect cows based on their shape and colour. But what if the cow pictures we put in the training dataset always sho...
115. Irina Rish - Out-of-distribution generalization is an episode from Towards Data Science by The TDS team . Imagine, for example, an AI that’s trained to identify cows in images. Ideally, we’d want it to learn to detect cows based on the...
This episode belongs to Towards Data Science.
Use the player on this page to stream the episode online.
Published Mar 9, 2022, 00:50:12 long, audio available.
Imagine, for example, an AI that’s trained to identify cows in images. Ideally, we’d want it to learn to detect cows based on their shape and colour. But what if the cow pictures we put in the training dataset always show cows standing on grass? In that case, we have a spurious correlation between grass and cows, and if we’re not careful, our AI might learn to become a grass detector rather than a cow detector. Even worse, we could only realize that’s happened once we’ve deployed it in the real world and it runs into a cow that isn’t standing on grass for the first time. So how do you build AI systems that can learn robust, general concepts that remain valid outside the context of their training data? That’s the problem of out-of-distribution generalization, and it’s a central part of the research agenda of Irina Rish, a core member of the Mila— Quebec AI Research institute, and the Canadian Excellence Research Chair in Autonomous AI. Irina’s research explores many different strategies that aim to overcome the out-of-distribution problem, from empirical AI scaling efforts to more theoretical work, and she joined me to talk about just that on this episode of the podcast. *** Intro music : - Artist: Ron Gelinas - Track Title: Daybreak Chill Blend (original mix) - Link to Track: *** Chapters: 2:00 Research, safety, and generalization 8:20 Invariant risk minimization 15:00 Importance of scaling 21:35 Role of language 27:40 AGI and scaling 32:30 GPT versus ResNet 50 37:00 Potential revolutions in architecture 42:30 Inductive bias aspect 46:00 New risks 49:30 Wrap-up
You can listen to 115. Irina Rish - Out-of-distribution generalization online on Radio and Podcast. Open the player on this page to stream the available audio.
115. Irina Rish - Out-of-distribution generalization is an episode from Towards Data Science by The TDS team .
This episode is 00:50:12 long.
This episode was published on Mar 9, 2022.
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115. Irina Rish - Out-of-distribution generalization is from Towards Data Science by The TDS team .
Published Mar 9, 2022 and 00:50:12 long