Podcast

Description

Ishan Misra is a research scientist at FAIR working on self-supervised visual learning. Please support this podcast by checking out our sponsors:

• Onnit: https://lexfridman.com/onnit to get up to 10% off
  
• The Information: https://theinformation.com/lex to get 75% off first month
  
• Grammarly: https://grammarly.com/lex to get 20% off premium
  
• Athletic Greens: https://athleticgreens.com/lex and use code LEX to get 1 month of fish oil
  
  EPISODE LINKS:
  Ishan’s twitter: https://twitter.com/imisra_
  Ishan’s website: https://imisra.github.io
  Ishan’s FAIR page: https://ai.facebook.com/people/ishan-misra/
  
  PODCAST INFO:
  Podcast website: https://lexfridman.com/podcast
  Apple Podcasts: https://apple.co/2lwqZIr
  Spotify: https://spoti.fi/2nEwCF8
  RSS: https://lexfridman.com/feed/podcast/
  YouTube Full Episodes: https://youtube.com/lexfridman
  YouTube Clips: https://youtube.com/lexclips
  
  SUPPORT & CONNECT:
  
• Check out the sponsors above, it’s the best way to support this podcast
  
• Support on Patreon: https://www.patreon.com/lexfridman
  
• Twitter: https://twitter.com/lexfridman
  
• Instagram: https://www.instagram.com/lexfridman
  
• LinkedIn: https://www.linkedin.com/in/lexfridman
  
• Facebook: https://www.facebook.com/lexfridman
  
• Medium: https://medium.com/@lexfridman
  
  OUTLINE:
  Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
  (00:00) - Introduction
  (07:49) - Self-supervised learning
  (16:24) - Self-supervised learning is the dark matter of intelligence
  (20:17) - Categorization
  (28:50) - Is computer vision still really hard?
  (32:35) - Understanding Language
  (42:14) - Harder to solve: vision or language
  (48:59) - Contrastive learning & energy-based models
  (52:59) - Data augmentation
  (57:19) - Fixed audio spike by lowering sound with pen tool
  (1:05:33) - Real data vs. augmented data
  (1:09:16) - Non-contrastive learning energy based self supervised learning methods
  (1:12:54) - Unsupervised learning (SwAV)
  (1:15:37) - Self-supervised Pretraining (SEER)
  (1:20:44) - Self-supervised learning (SSL) architectures
  (1:26:43) - VISSL pytorch-based SSL library
  (1:29:38) - Multi-modal
  (1:37:06) - Active learning
  (1:42:45) - Autonomous driving
  (1:54:12) - Limits of deep learning
  (1:58:19) - Difference between learning and reasoning
  (2:03:26) - Building super-human AI
  (2:11:14) - Most beautiful idea in self-supervised learning
  (2:15:02) - Simulation for training AI
  (2:18:27) - Video games replacing reality
  (2:19:40) - How to write a good research paper
  (2:24:08) - Best programming language for beginners
  (2:25:01) - PyTorch vs TensorFlow
  (2:28:26) - Advice for getting into machine learning
  (2:30:31) - Advice for young people
  (2:32:58) - Meaning of life

Transcript