Felix Hill's guest appearances

Felix Hill

Talus Media Talks

Humans of AI: Stories, Not Stats

Fantasy Pints Podcast

The Embodied AI Podcast

Justin Moore

Ayanna Howard

Noah Smith

Heather Smith

Karen Litzy

James Spencer

Joe Donnelly

Charles Isbell

Carlos Guestrin

Ken Olson

James Elliott

Clinton Baptiste

Jeff Dean

Shirley Sahrmann

Heidi Jannenga

OwlTail

Felix is a research scientist at DeepMind. He is interested in grounded language understanding and natural language processing (NLP). After finding out about Felix's background, we bring up compositionality and explore why natural language is NonCompositional (also, the name of Felix's blog). Then, Felix tells us a bit about his work in Cambridge on abstract vs concrete concepts and gives us a quick crash course on the role of recurrent neural networks (RNNs), long short-term memory (LSTMs), and transformers in language models. Next, we talk about Jeff Elman's landmark paper 'Finding Structure in Time' and how neural networks can learn to understand analogies. After, we discuss the core of Felix work: Training language agents in 3D simulations, where we raise some questions on language learning as an embodied agent in space and time, and Allan Paivio's dual coding theory implemented in the memory of a language model. Next, we stick with the theme of memory retrieval and discuss Felix and Andrew Lampinen's work on 'mental time travel' in language models. Finally, I ask Felix on some good strategies on how to get into DeepMind and the best way to learn NLP.  Timestamps: (00:00) - Intro (07:57) - Compositionality in natural language (16:42) - Abstract vs concrete concepts (24:03) - RNNs, LSTMs, Transformers (34:12) - Prediction, time and Jeff Elman (48:04) - Neural networks &amp; analogies (56:32) - Grounded language, 3D simulations, babies, (01:05:20) - Keeping vision and language data separate (01:13:51) - NeuroAI and mental time travel (01:21:47) - Getting into DeepMind and learning NLP  Felix Website (good overview for his papers) https://fh295.github.io/ Abstract vs concrete concepts paper https://onlinelibrary.wiley.com/doi/full/10.1111/cogs.12076 Jeff Elman (1990): Finding structure in time https://onlinelibrary.wiley.com/doi/pdf/10.1207/s15516709cog1402_1 Analogies paper https://openreview.net/pdf?id=SylLYsCcFm Dual coding theory paper https://arxiv.org/abs/2009.01719 Mental Time Travel paper https://arxiv.org/abs/2105.14039  My Twitter https://twitter.com/Embodied_AI My LinkedIn https://www.linkedin.com/in/akseli-ilmanen-842098181/

Felix is a research scientist at DeepMind. He is interested in grounded language understanding and natural language processing (NLP). After finding out about Felix's background, we bring up compositionality and explore why natural language is NonCompositional (also, the name of Felix's blog). Then, Felix tells us a bit about his work in Cambridge on abstract vs concrete concepts and gives us a quick crash course on the role of recurrent neural networks (RNNs), long short-term memory (LSTMs), and transformers in language models. Next, we talk about Jeff Elman's landmark paper 'Finding Structure in Time' and how neural networks can learn to understand analogies. After, we discuss the core of Felix work: Training language agents in 3D simulations, where we raise some questions on language learning as an embodied agent in space and time, and Allan Paivio's dual coding theory implemented in the memory of a language model. Next, we stick with the theme of memory retrieval and discuss Felix and Andrew Lampinen's work on 'mental time travel' in language models. Finally, I ask Felix on some good strategies on how to get into DeepMind and the best way to learn NLP. Timestamps: (00:00) - Intro (07:57) - Compositionality in natural language (16:42) - Abstract vs concrete concepts (24:03) - RNNs, LSTMs, Transformers (34:12) - Prediction, time and Jeff Elman (48:04) - Neural networks &amp; analogies (56:32) - Grounded language, 3D simulations, babies, (01:05:20) - Keeping vision and language data separate (01:13:51) - NeuroAI and mental time travel (01:21:47) - Getting into DeepMind and learning NLP Felix Website (good overview for his papers) <a href="https://fh295.github.io/" rel="nofollow" target="_blank">https://fh295.github.io/</a> Abstract vs concrete concepts paper <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/cogs.12076" rel="nofollow" target="_blank">https://onlinelibrary.wiley.com/doi/full/10.1111/cogs.12076</a> Jeff Elman (1990): Finding structure in time <a href="https://onlinelibrary.wiley.com/doi/pdf/10.1207/s15516709cog1402_1" rel="nofollow" target="_blank">https://onlinelibrary.wiley.com/doi/pdf/10.1207/s15516709cog1402_1</a> Analogies paper <a href="https://openreview.net/pdf?id=SylLYsCcFm" rel="nofollow" target="_blank">https://openreview.net/pdf?id=SylLYsCcFm</a> Dual coding theory paper <a href="https://arxiv.org/abs/2009.01719" rel="nofollow" target="_blank">https://arxiv.org/abs/2009.01719</a> Mental Time Travel paper <a href="https://arxiv.org/abs/2105.14039" rel="nofollow" target="_blank">https://arxiv.org/abs/2105.14039</a> My Twitter <a href="https://twitter.com/Embodied_AI" rel="nofollow" target="_blank">https://twitter.com/Embodied_AI</a> My LinkedIn <a href="https://www.linkedin.com/in/akseli-ilmanen-842098181/" rel="nofollow" target="_blank">https://www.linkedin.com/in/akseli-ilmanen-842098181/</a>

#5 Felix Hill: Grounded Language, Transformers, and DeepMind 

Dhruv Batra

Felix Hill is a Research Scientist at Google DeepMind. Find out more about him at his homepage. Humans of AI: Stories, Not Stats is an interview series with AI researchers to get to know them better as people. We don't talk about AI or their work or the stats of their life like what college they went to. They share what they think about, what they are insecure about, what they get excited about. They share the stories of their day-to-day life. Videos of these interviews are available at humanstories.ai. The host of this episode is Dhruv Batra, an Associate Professor in the School of Interactive Computing at Georgia Tech and a Research Scientist at Facebook AI Research (FAIR). Find out more about him at his homepage or follow him on Twitter. This interview was recorded on 26th April 2021.--- Send in a voice message: https://podcasters.spotify.com/pod/show/humanstoriesai/message

Felix Hill is a Research Scientist at Google DeepMind. Find out more about him at his <a href="https://fh295.github.io/" rel="nofollow" target="_blank">homepage</a>. Humans of AI: Stories, Not Stats is an interview series with AI researchers to get to know them better as people. We don't talk about AI or their work or the stats of their life like what college they went to. They share what they think about, what they are insecure about, what they get excited about. They share the stories of their day-to-day life. Videos of these interviews are available at <a href="http://humanstories.ai/" rel="nofollow" target="_blank">humanstories.ai</a>. The host of this episode is Dhruv Batra, an Associate Professor in the School of Interactive Computing at Georgia Tech and a Research Scientist at Facebook AI Research (FAIR). Find out more about him at <a href="https://www.cc.gatech.edu/~dbatra/" rel="nofollow" target="_blank">his homepage</a> or follow him on <a href="https://twitter.com/DhruvBatraDB" rel="nofollow" target="_blank">Twitter</a>. This interview was recorded on 26th April 2021.--- Send in a voice message: <a href="https://podcasters.spotify.com/pod/show/humanstoriesai/message" rel="nofollow" target="_blank">https://podcasters.spotify.com/pod/show/humanstoriesai/message</a>

S2E16: Felix Hill with Dhruv Batra

This week, we are joined by a young singer-songwriter from Manchester, Felix Hill. We discuss his latest single 'Down by the Races', radio and social media praise, juggling music and A levels and plenty more!

Episode 8 - Felix Hill 

PT Proud's Felix Hill: The LGBTQ+ Competency Handbook