11 episodes

Deep Neural Notebooks is a podcast where I like to discuss topics ranging from Deep Learning, NLP and Computer Vision to Neuroscience and Open Source Software, through conversations with experts about their thoughts on the state of their specialisations, how things fit into the bigger picture, their journey so far and the road ahead.

I believe that it is through conversations like these that we can boil down the essence of vast resources of knowledge and expertise into more consumable bits that can enrich our understanding of concepts and technologies that are shaping our world.

Deep Neural Notebooks Mukul Khanna

    • Science
    • 5.0 • 4 Ratings

Deep Neural Notebooks is a podcast where I like to discuss topics ranging from Deep Learning, NLP and Computer Vision to Neuroscience and Open Source Software, through conversations with experts about their thoughts on the state of their specialisations, how things fit into the bigger picture, their journey so far and the road ahead.

I believe that it is through conversations like these that we can boil down the essence of vast resources of knowledge and expertise into more consumable bits that can enrich our understanding of concepts and technologies that are shaping our world.

    DNN 10: Practical Natural Language Processing Book [Interview + Giveaway] | NLP, Machine Learning & AI in the Industry | GPT-3 and more

    DNN 10: Practical Natural Language Processing Book [Interview + Giveaway] | NLP, Machine Learning & AI in the Industry | GPT-3 and more

    GIVEAWAY INFORMATION:  

    Thanks to O'Reilly and the authors, we are giving away 5 copies of the Practical Natural Language Processing book.   

    Giveaway tweet: [TBD at 7:30PM IST]  

    To participate in the giveaway, retweet and comment about your favourite part of the conversation with the #practicalnlp hashtag. The winners will be selected and notified on October 1, 2020. To be updated about the results, subscribe to the Youtube channel and follow me on twitter https://twitter.com/mkulkhanna.  

    You can also get a 30-day free trial from the O'Reilly website by using the promo code PNLP20 or the link below. 

    Link: https://learning.oreilly.com/get-learning/?code=PNLP20  


    Episode Introduction:  

    This is the 10th episode of the podcast and a really special one. I've got the authors of the Practical Natural Language Processing book. The book is a comprehensive guide to building, iterating and scaling real world NLP Systems. It is for anyone who is involved in any way in building NLP systems in industry - from software engineers to data scientists to ML engineers to product managers and business leaders. The book is already topping the charts on Amazon and has been endorsed by various experts from academia and industry.  



    Episode Overview:  

    So for this episode, I talk to the authors of the book - Sowmya, Bodhi, Anuj and Harshit.  We talk about the key ideas behind the book - about how it bridges the gap between theory and building practical ML/NLP solutions. We talk about the inspiration behind writing the book, how it stands out, how it has been structured, who can benefit from it and lots more. We also talk about the elephant in the room, GPT-3 and try to make sense of the hype around it and understand it's broader impact and how it positions us, as a community to leverage these systems on a wider scale.  

    We also talk about the state of ML and NLP in general, about the many misconceptions and misinformed expectations that surround these fields in the context of the business of AI, and about how they've tried to incorporate this message in the book.  



    Practical Natural Language Processing Book:  

    Website: http://www.practicalnlp.ai/
    Twitter: https://twitter.com/PracticalNLProc  



    Authors / Guests:  

    Sowmya Vajjala: https://twitter.com/adyantalamadhya
    She is a research officer at National Research Council, Canada’s largest federal research and development organization. Her past work experience spans both academia as a faculty at Iowa State University, USA and industry at Microsoft Research. 



    Bodhisattwa Majumder: https://twitter.com/mbodhisattwa
    He is a Computer Science PhD student working on NLP and ML at UC San Diego. His research interests include Lang Generation and Dialogue & Interactive Systems 



    Anuj Gupta: https://twitter.com/anujgupta82
    He is currently Head of Machine Learning and Data Science at Vahan Inc. He has built NLP and ML systems at Fortune 100 companies as well as startups as a senior leader.   



    Harshit Surana: https://twitter.com/surana_h
    He is a co-founder at DeepFlux Inc. He has built and scaled ML systems and engineering pipelines at several Silicon Valley startups as a founder and an advisor.



    Connect with me 🙎🏻‍♂️:   

    Website: https://mukulkhanna.github.io
    Twitter: https://twitter.com/mkulkhanna 



    Deep Neural Notebooks podcast 🎙: 

    Youtube: www.youtube.com/channel/UC66w1T4oMv66Jn1LR5CW2yg

    Anchor: www.anchor.fm/deep-neural-notebooks

    Spotify: www.open.spotify.com/show/2eq1jD7V5K19aZUUJnIz5z

    Apple Podcasts: www.podcasts.apple.com/in/podcast/deep-neural-notebooks/id1488705711

    • 1 hr 41 min
    DNN 9: NVIDIA's AI Co-Pilot: Computer Vision & Machine Learning Inside The Car | Shalini De Mello, Research Lead, NVIDIA

    DNN 9: NVIDIA's AI Co-Pilot: Computer Vision & Machine Learning Inside The Car | Shalini De Mello, Research Lead, NVIDIA

    In this episode, I talk with Shalini De Mello, who is a Principal Research Scientist and Research Lead at NVIDIA. Her research interests are in computer vision and machine learning for human-computer interaction and smart interfaces.

    At NVIDIA, she has developed technologies for gaze estimation, 2D and 3D head pose estimation, hand gesture recognition, face detection, video stabilization and GPU-optimized libraries for mobile computer vision. Her research has been focused on human-computer interaction in cars and has led to the development of NVIDIA’s innovative DriveIX product for smart AI-based automotive interfaces for future generations of cars.

    Shalini received her Masters and PhD in Electrical and Computer Engineering from the University of Texas at Austin. She received a Bachelor of Engineering degree in Electronics and Electrical Communication Engineering from Punjab Engineering College.

    In this episode, we talk about her journey - about how she got started with Computer Vision and Machine Learning, from her Bahelor's to her Master's in Biomedical Imaging to her PhD work on Human Face Recognition - about how her research interests shaped over the years. We also talk about Machine Learning inside the car, about her vision of using Machine Learning & Deep Learning for building smart assistive interfaces for inside the car, and about how that manifested into the DriveIX product that NVIDIA recently launched. Among other things, we talk about the importance of open-sourcing technology, about the future of autonomous and semi-autonomous vehicles, about the joys of learning something new everyday, about how to keep track of the every growing amount of research and much more. It was an absolute pleasure to talk with Shalini and learn from her research insights. I hope you like the conversation.



    Shalini De Mello:

    Twitter: https://twitter.com/shalinidemello

    Website: https://research.nvidia.com/person/shalini-gupta



    Links:

    NVIDIA Drive IX: https://www.nvidia.com/en-us/self-driving-cars/drive-ix/, https://developer.nvidia.com/drive/drive-ix

    Self-Supervised Viewpoint Learning From Image Collections: https://research.nvidia.com/publication/2020-03_Self-Supervised-Viewpoint-Learning

    Multi-sensor System for Driver’s Hand-Gesture Recognition: https://research.nvidia.com/publication/hand-gesture-recognition-3d-convolutional-neural-networks

    AI Co-Pilot: RNNs for Dynamic Facial Analysis: https://developer.nvidia.com/blog/ai-co-pilot-rnn-dynamic-facial-analysis/



    Podcast links:

    Spotify: https://tinyurl.com/yb6sn2rv

    Apple Podcasts: https://tinyurl.com/y9hu7lzq

    Google Podcasts: https://tinyurl.com/ybb8gxd5

    Anchor.fm: https://tinyurl.com/ya98vk7b

    Youtube: https://youtu.be/Hfz965mLuvM



    Connect with me 🙎🏻‍♂️: 

    Twitter: twitter.com/mkulkhanna

    Instagram: instagram.com/mkulkhanna/



    Deep Neural Notebooks podcast 🎙:

    Youtube: www.youtube.com/channel/UC66w1T4oMv66Jn1LR5CW2yg

    Anchor: www.anchor.fm/deep-neural-notebooks

    Spotify: www.open.spotify.com/show/2eq1jD7V5K19aZUUJnIz5z

    Apple Podcasts: www.podcasts.apple.com/in/podcast/deep-neural-notebooks/id1488705711

    • 1 hr 15 min
    DNN 8: Super SloMo, Computer Vision and Machine Learning Research | Varun Jampani, Google Research

    DNN 8: Super SloMo, Computer Vision and Machine Learning Research | Varun Jampani, Google Research

    In this episode, I interview Varun Jampani, who is a Research Scientist at Google Research. You might recognise him from the renowned Super SloMo paper. His work lies at the intersection of Computer Vision and Machine Learning. His main focus is to leverage machine learning techniques for better inference in computer vision models.

    Prior to joining Google, he was a research scientist at NVIDIA. He completed his PhD at the Max-Planck Institute (MPI) for Intelligent Systems. He is also a IIIT Hyderabad alum, where he did his Bachelor's and Master's.  

    In this episode, we talk about his journey — from his Bachelor's and Masters at IIIT Hyderabad to his PhD at MPI, about how his research has shaped over the years, about his focus on always asking good research questions and tackling fundamental problems in Computer Vision as a whole.  We also talk about the SuperSloMo paper, about how it started, the key design decisions that were taken and the challenges faced in the process. If there's one thing that you are likely to take away from this conversation, it is the importance of asking good research questions and letting that drive your learning and research.  

    Guest:  

    Varun Jampani: https://varunjampani.github.io/  

    Links:  

    CVPR 2020 Novel View Synthesis Tutorial: https://www.youtube.com/watch?v=OEUHalxanuc

    Episode links:

    Spotify: https://tinyurl.com/y7u98d7m
    Apple Podcasts: https://tinyurl.com/y8w7tkhf
    Google Podcasts: https://tinyurl.com/y8aas5le
    Anchor.fm: https://tinyurl.com/ycudgfse

    Connect with me 🙎🏻‍♂️:   

    Twitter: twitter.com/mkulkhanna
    Instagram: instagram.com/mkulkhanna/  

    Deep Neural Notebooks podcast 🎙:

    Youtube: www.youtube.com/channel/UC66w1T4oMv66Jn1LR5CW2yg
    Anchor: www.anchor.fm/deep-neural-notebooks
    Spotify: www.open.spotify.com/show/2eq1jD7V5K19aZUUJnIz5z
    Apple Podcasts: www.podcasts.apple.com/in/podcast/deep-neural-notebooks/id1488705711

    • 52 min
    DNN 7: Reinforcement Learning | Research at Waymo, University of Oxford | Shimon Whiteson

    DNN 7: Reinforcement Learning | Research at Waymo, University of Oxford | Shimon Whiteson

    In the seventh episode of Deep Neural Notebooks, I interview Shimon Whiteson.  

    Shimon sir is a Computer Science Professor at the University of Oxford, where he leads the Whiteson Research Lab. He is also a Data Scientist at Waymo (formerly the Google Self Driving Car Project). His research specialises in Reinforcement Learning (RL), Cooperative Multi-Agent RL, to be precise.   

    So this interview is all in the context of Reinforcement Learning. We talk about his journey  - how he started with Machine Learning & RL. I ask him about his thoughts on the state of RL - about how the field has progressed and changed since he started, about how it has become so popular in the last few years, and about the challenges being faced.  

    We also talk about his research at Waymo, about recent projects from his lab, and about the scope and future of telepresence robots, one of which was developed under his guidance. We also talk about the infamous Reward Hypothesis in the context of RL and Philosophy. In the end, he also shares some advice for people starting out with RL.  

    Links:  

    - Shimon Whiteson: https://twitter.com/shimon8282 

    - Whiteson Research Lab (WhiRL): http://whirl.cs.ox.ac.uk/ 

    - Teresa Robot: https://whirl.cs.ox.ac.uk/teresa/ 

    - RL workshop at Machine Learning Summer School, Moscow: https://www.youtube.com/watch?v=RAw0Chs7QKA 

    - The Reward Hypothesis: http://incompleteideas.net/rlai.cs.ualberta.ca/RLAI/rewardhypothesis.html



    Timestamps:

    03:42 Beginnings in Computer Science06:13 Beginnings in ML

    07:15 PhD at UT Austin

    10:40 Intersection of Neuroevolution and RL

    14:10 Research directions since PhD

    16:35 State of RL

    20:33 Simulation for RL

    22:07 Research at Waymo

    25:30 Multi-agent RL

    33:25 Recent projects at WhiRL

    41:30 Teresa project and Telepresence Robots

    48:08 Bottlenecks for RL and Robotics

    49:45 End-goal for RL, Human-level Intelligence

    53:45 What do you find most fascinating about your research?

    55:38 RL & Philosophy

    1:01:20 Keeping up with latest research

    1:03:28 Advice for beginners



    Podcast links :

    Youtube: https://youtu.be/bbrYZDgPI9M

    Apple Podcasts:  https://apple.co/2TLUZ0y

    Google Podcasts: https://bit.ly/2TIyvh6

    Spotify:  https://open.spotify.com/episode/3936aEvSwsIhfwQfURmDb9

    Anchor: https://bit.ly/3gpMi65



    Connect:  

    Twitter: https://twitter.com/mkulkhanna 

    Website: https://mukulkhanna.co 

    LinkedIn: https://linkedin.com/in/mukulkhanna/

    • 1 hr 5 min
    DNN 6: Spirituality, Music & The Bhagavad Gita | Srinivas Reddy

    DNN 6: Spirituality, Music & The Bhagavad Gita | Srinivas Reddy

    In the fifth episode of the Deep Neural Notebooks podcast, I interview Professor, Author, Sitarist and Composer, Srinivas Reddy.  

    He is a Guest Professor of South and Southeast Asian Studies at IIT Gandhinagar and Visiting Assistant Professor of Religious Studies and Contemplative Studies at Brown University. He lives in Rhode Island and spends his time performing, teaching and conducting research around the world.  He is an author of 4 books, 3 of which are translations of Telugu and Sanskrit texts; and the latest book that came out this March is a critical biography of Krishnadevaraya of Vijayanagara, called RAYA.  
    Srinivas is a professional concert sitarist and has given numerous recitals in the US, India and Europe. He has three albums to his credit: GITA (1999), Sitar & Tabla (2001) and Hemant & Jog (2008).  

    This episode is more in the realms of spirituality, in the context of South Asian philosophy and the Bhagwad Gita. We discuss some of his favourite verses and chapters from the Gita, about the deep underlying wisdom, and how we can make sense of them in today's day and age.  I ask him about his thoughts on religion, consciousness, meditation, his passion for music and much more.  He also talks about how India never really recovered from colonialisation and how the quest for adoption of Western ideologies has left us devoid of any appreciation for our cultural heritage, and how unconditioning ourselves is the first step in moving forward on our spiritual path.   

    Keep in mind that this episode was recorded in the first week of January, wayyy before the pandemic outbreak; so some of his advice like going out for a walk on a beautiful sunny day was shared in a pre-COVID-19 context.  I hope you enjoy the episode, and learn something valuable from it. If you do, please leave a thumb's up or a 5-star rating depending on the streaming platform.  

    Links: 

    Srinivas Reddy: https://www.srinivasreddy.org/ 

    Books: 

    - Giver of the Worn Garland (Amuktamalyada) - http://www.tinyurl.com/amukta
    - The Dancer and the King (Malavikagnimitram) - https://www.amazon.com/Malavikagnimitram-Dancer-King-Kalidasa/dp/0670086878/ref=sr_1_2?ie=UTF8&qid=1495455130&sr=8-2&keywords=dancer+and+the+king - The Cloud Message (Meghadutam) - https://www.amazon.com/Meghadutam-Kalidasa-ebook/dp/B01N7PFSGG/ref=sr_1_1?ie=UTF8&qid=1495454149&sr=8-1&keywords=kalidasa+meghadutam
    - RAYA: Krishnadevaraya of Vijayanagara -https://www.amazon.com/gp/product/9353450977/ref=dbs_a_def_rwt_bibl_vppi_i3  

    Concerts:
    - Classical Sitar Concert by Srinivas Reddy: https://www.youtube.com/watch?v=DwjcOHgyyiw
    - Srinivas Reddy Concert - https://www.youtube.com/watch?v=GRWLXjtoIPc  

    Albums:
    - Hemant and Jog (2008): https://play.google.com/store/music/album/?id=B3jmymz4awn3ws5343nvncrib3e  

    Podcast links -  

    - Youtube: https://youtu.be/JK2X_ZM4vHM
    - Apple Podcasts: https://apple.co/3a6HY7p
    - Google Podcasts: https://bit.ly/3caOFqr
    - Spotify: https://open.spotify.com/episode/6SJ7z5gavxGR9zaPFJkwCs
    - Anchor: https://anchor.fm/deep-neural-notebooks/episodes/DNN-6-Spirituality--Music--The-Bhagavad-Gita--Srinivas-Reddy-ecnl7p

    Connect with me:  

    Twitter: https://twitter.com/mkulkhanna
    Website: https://mukulkhanna.co
    LinkedIn: https://linkedin.com/in/mukulkhanna/

    • 53 min
    DNN 5: Neuroscience, Art & Creativity | Leslee Lazar

    DNN 5: Neuroscience, Art & Creativity | Leslee Lazar

    In this episode, I interview Leslee Lazar, a cognitive neuroscientist and visual artist. He is a professor at IIT Gandhinagar, at the Centre for Cognitive and Brain Science, working on processing of tactile perception in the somatosensory cortex of the brain. He is passionate about art and design, and uses illustrations, graphic design, infographics, collages and photography to convey complex stories. Neuroscientist by day, visual artist by evening, his research interests include understanding creativity and perception of art from a Neuroscience point of view. He has some amazing artworks, illustrations and posters that I'd recommend you to check out on his Instagram and Tumblr accounts, links to which can be found below.  

    In this episode, we talk about his journey - from Zoology to Neuroscience, his work on touch perception, about creativity, and about how we as humans share an innate appreciation for art and beauty. On the intersection of Computer Science and Neuroscience, I asked him about brain computer interfaces, like the ones being developed at Neuralink, and his thoughts on possibility of being able to model a digital brain one day.   In the end, he shares some advice for people taking interest in Neuroscience and a list of books people can refer to, to get started.  

    This video was recorded before the lockdown in India.  

    If you enjoyed the conversation or learned something valuable from it, please give it a thumb's up or a 5-star rating depending on the streaming platform - it really helps the channel and allows more people to discover it.  

    List of Top Neuroscience books for people starting out: 


    Mind: Introduction to Cognitive Science by Paul Thagard 
    The Brain That Changes Itself by Norman Doidge 
    Descartes' ErrorBook by Antonio Damasio - The Man Who Mistook His Wife for a Hat by Oliver Sacks 
    Phantoms in the Brain: Probing the Mysteries of the Human Mind by Sandra Blakeslee and V. S. Ramachandran 
    Neuroscience: Exploring the Brain by Mark F. Bear, Barry W. Connors & Michael A. Paradiso  

    Links:  

    Leslee Lazar -  

    Website: https://lesleelazar.com 

    Twitter: https://twitter.com/leslee_lazar 

    Instagram: https://instagram.com/dull_eye_llama 

    Tumblr: https://lesleelazar.tumblr.com  

    Centre for Cognitive and Brain Science: https://cogs.iitgn.ac.in  

    Nature article on COVID-19: https://nature.com/articles/s41591-020-0820-9?fbclid=IwAR2xZouI4JVsZdFbIqLixXC-XC8mxMCQ_Inw2znKGcgrdeUW6kVzZQB_VVs  


    Podcast links -  

    Youtube: https://youtu.be/X2V5z6J6J1o 

    Apple Podcasts: https://apple.co/2V22kZO

    Google Podcasts: https://bit.ly/3aItP1o

    Spotify: https://open.spotify.com/episode/4TuU8kZBCM2KWevHBAbpNj 

    Anchor: https://anchor.fm/deep-neural-notebooks/episodes/DNN-5-Neuroscience--Art-and-Creativity--Leslee-Lazar-ecaqoc



    Connect:  

    Twitter: https://twitter.com/mkulkhanna 

    Website: https://mukulkhanna.co 

    LinkedIn: https://linkedin.com/in/mukulkhanna/

    • 55 min

Customer Reviews

5.0 out of 5
4 Ratings

4 Ratings

sriya97 ,

Really Good Content

This series of podcasts is perfect for data science and machine learning enthusiasts. I got to learn about research being done in eminent institutions , and big companies like mozilla. All the topics are discussed in a comprehensive manner helping me strengthen my understanding. Kudos to the creator!

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