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
Contenido proporcionado por NLP Highlights and Allen Institute for Artificial Intelligence. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente NLP Highlights and Allen Institute for Artificial Intelligence o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
Player FM : aplicación de podcast
¡Desconecta con la aplicación Player FM !
¡Desconecta con la aplicación Player FM !
125 - VQA for Real Users, with Danna Gurari
MP3•Episodio en casa
Manage episode 291687356 series 1452120
Contenido proporcionado por NLP Highlights and Allen Institute for Artificial Intelligence. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente NLP Highlights and Allen Institute for Artificial Intelligence o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
How can we build Visual Question Answering systems for real users? For this episode, we chatted with Danna Gurari, about her work in building datasets and models towards VQA for people who are blind. We talked about the differences between the existing datasets, and Vizwiz, a dataset built by Gurari et al., and the resulting algorithmic changes. We also discussed the unsolved challenges in this field, and the new tasks they result in. Danna Gurari is an Assistant Professor as well as Founding Director of the Image and Video Computing group in the School of Information at University of Texas at Austin (UT-Austin). Vizwiz project page: https://vizwiz.org/ The hosts for this episode are Ana Marasović and Pradeep Dasigi.
…
continue reading
145 episodios
MP3•Episodio en casa
Manage episode 291687356 series 1452120
Contenido proporcionado por NLP Highlights and Allen Institute for Artificial Intelligence. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente NLP Highlights and Allen Institute for Artificial Intelligence o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
How can we build Visual Question Answering systems for real users? For this episode, we chatted with Danna Gurari, about her work in building datasets and models towards VQA for people who are blind. We talked about the differences between the existing datasets, and Vizwiz, a dataset built by Gurari et al., and the resulting algorithmic changes. We also discussed the unsolved challenges in this field, and the new tasks they result in. Danna Gurari is an Assistant Professor as well as Founding Director of the Image and Video Computing group in the School of Information at University of Texas at Austin (UT-Austin). Vizwiz project page: https://vizwiz.org/ The hosts for this episode are Ana Marasović and Pradeep Dasigi.
…
continue reading
145 episodios
Todos los episodios
×Bienvenido a Player FM!
Player FM está escaneando la web en busca de podcasts de alta calidad para que los disfrutes en este momento. Es la mejor aplicación de podcast y funciona en Android, iPhone y la web. Regístrate para sincronizar suscripciones a través de dispositivos.