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Το περιεχόμενο παρέχεται από το Jay Shah. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Jay Shah ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.player.fm/legal.
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Theory of Machine Learning, Transformer models, ChatGPT & tips for research career | Dr. Surbhi Goel

1:31:25
 
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Manage episode 355564638 series 2859018
Το περιεχόμενο παρέχεται από το Jay Shah. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Jay Shah ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.player.fm/legal.

Surbhi is an Assistant Professor at the University of Pennsylvania. She got her Ph.D. in Computer Science from UT Austin and prior to joining UPenn as an Assistant Professor, she was a postdoctoral researcher at Microsoft Research NYC in the Machine Learning group. She has research expertise in theoretical computer science & machine learning, with a particular focus on developing theoretical foundations for modern deep learning paradigms. She also is a part of building the Learning Theory Alliance community that organizes and conducts several events useful for researchers and students in their careers.
Time stamps of the conversation
00:00:54 Introduction
00:01:54 Background and research interests
00:05:03 Interest in Machine Learning Theory
00:13:02 Understanding how deep learning works
00:16:30 Transformer architecture
00:25:40 Scale of data and big models
00:31:28 Reasoning in deep learning
00:38:52 Theoretical perspective on AGI, consciousness, and sentience in AI
00:46:00 Remaining updated to the latest research
00:53:38 Should one do a Ph.D.?
00:57:45 Is a Ph.D. mandatory for machine learning industry positions?
01:01:38 What makes a good research thesis?
01:05:30 Some best practices in research
01:12:20 Learning Theory Alliance Group
01:14:25 Job interviews in academia for researchers
01:20:00 Advice to young researchers and students
01:25:02 Decision to become a Professor
Find Dr. Goel on social media
Website: https://www.surbhigoel.com/
Linkedin: https://www.linkedin.com/in/surbhi-goel-5455b25a
Twitter: https://twitter.com/surbhigoel_?lang=en
Learning Theory Alliance: https://let-all.com/index.html
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.***

Checkout these Podcasts on YouTube: https://www.youtube.com/c/JayShahml
About the author: https://www.public.asu.edu/~jgshah1/

  continue reading

92 επεισόδια

Artwork
iconΜοίρασέ το
 
Manage episode 355564638 series 2859018
Το περιεχόμενο παρέχεται από το Jay Shah. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Jay Shah ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.player.fm/legal.

Surbhi is an Assistant Professor at the University of Pennsylvania. She got her Ph.D. in Computer Science from UT Austin and prior to joining UPenn as an Assistant Professor, she was a postdoctoral researcher at Microsoft Research NYC in the Machine Learning group. She has research expertise in theoretical computer science & machine learning, with a particular focus on developing theoretical foundations for modern deep learning paradigms. She also is a part of building the Learning Theory Alliance community that organizes and conducts several events useful for researchers and students in their careers.
Time stamps of the conversation
00:00:54 Introduction
00:01:54 Background and research interests
00:05:03 Interest in Machine Learning Theory
00:13:02 Understanding how deep learning works
00:16:30 Transformer architecture
00:25:40 Scale of data and big models
00:31:28 Reasoning in deep learning
00:38:52 Theoretical perspective on AGI, consciousness, and sentience in AI
00:46:00 Remaining updated to the latest research
00:53:38 Should one do a Ph.D.?
00:57:45 Is a Ph.D. mandatory for machine learning industry positions?
01:01:38 What makes a good research thesis?
01:05:30 Some best practices in research
01:12:20 Learning Theory Alliance Group
01:14:25 Job interviews in academia for researchers
01:20:00 Advice to young researchers and students
01:25:02 Decision to become a Professor
Find Dr. Goel on social media
Website: https://www.surbhigoel.com/
Linkedin: https://www.linkedin.com/in/surbhi-goel-5455b25a
Twitter: https://twitter.com/surbhigoel_?lang=en
Learning Theory Alliance: https://let-all.com/index.html
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.***

Checkout these Podcasts on YouTube: https://www.youtube.com/c/JayShahml
About the author: https://www.public.asu.edu/~jgshah1/

  continue reading

92 επεισόδια

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