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P2 Working at DeepMind, Interview Tips & doing a PhD for a career in AI | Dr. David Stutz

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Contenuto fornito da Jay Shah. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Jay Shah o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

Part-2 of my podcast with David Stutz. (Part-1: https://youtu.be/J7hzMYUcfto) David is a research scientist at DeepMind working on building robust and safe deep learning models. Prior to joining DeepMind, he was a PhD student at the Max Plank Institute of Informatics. He also maintains a fantastic blog on various topics related to machine learning and graduate life which is insightful to young researchers out there. 00:00:00 Working at DeepMind 00:08:20 Importance of Abstraction and Collaboration in Research 00:13:08 DeepMind internship project 00:19:39 What drives research projects at DeepMind 00:27:45 Research in Industry vs Academia 00:30:45 Interview tips for research roles, at DeepMind or other companies 00:44:38 Finding the right Advisor & Institute for PhD 01:02:12 Do you really need a Ph.D. to do AI/ML research? 01:08:28 Academia vs Industry: Making the choice 01:10:49 Pressure to publish more papers 01:21:35 Artificial General Intelligence (AGI) 01:33:24 Advice to young enthusiasts on getting started David's Homepage: https://davidstutz.de/ And his blog: https://davidstutz.de/category/blog/ Research work: https://scholar.google.com/citations?user=TxEy3cwAAAAJ&hl=en About the Host: Jay is a Ph.D. student at Arizona State University. Linkedin: https://www.linkedin.com/in/shahjay22/ Twitter: https://twitter.com/jaygshah22 Homepage: https://www.public.asu.edu/~jgshah1/ for any queries. Stay tuned for upcoming webinars! ***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***

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92 episodi

Artwork
iconCondividi
 
Manage episode 370885634 series 2859018
Contenuto fornito da Jay Shah. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Jay Shah o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

Part-2 of my podcast with David Stutz. (Part-1: https://youtu.be/J7hzMYUcfto) David is a research scientist at DeepMind working on building robust and safe deep learning models. Prior to joining DeepMind, he was a PhD student at the Max Plank Institute of Informatics. He also maintains a fantastic blog on various topics related to machine learning and graduate life which is insightful to young researchers out there. 00:00:00 Working at DeepMind 00:08:20 Importance of Abstraction and Collaboration in Research 00:13:08 DeepMind internship project 00:19:39 What drives research projects at DeepMind 00:27:45 Research in Industry vs Academia 00:30:45 Interview tips for research roles, at DeepMind or other companies 00:44:38 Finding the right Advisor & Institute for PhD 01:02:12 Do you really need a Ph.D. to do AI/ML research? 01:08:28 Academia vs Industry: Making the choice 01:10:49 Pressure to publish more papers 01:21:35 Artificial General Intelligence (AGI) 01:33:24 Advice to young enthusiasts on getting started David's Homepage: https://davidstutz.de/ And his blog: https://davidstutz.de/category/blog/ Research work: https://scholar.google.com/citations?user=TxEy3cwAAAAJ&hl=en About the Host: Jay is a Ph.D. student at Arizona State University. Linkedin: https://www.linkedin.com/in/shahjay22/ Twitter: https://twitter.com/jaygshah22 Homepage: https://www.public.asu.edu/~jgshah1/ for any queries. Stay tuned for upcoming webinars! ***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***

  continue reading

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