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Podcasts
- Scaling AI Infrastructure for the Next 1000x - Gradient, with Dwarkesh Patel (July 2025)
- Latent Space Podcast - "Open Source AI is AI we can Trust" - Tinygrad, Mojo, MLX, PyTorch Mafia, Llama 3, AI robotics (March 2024)
- Generative Now Podcast - Meta's AI Strategy, PyTorch and Llama (June 2024)
- Gradient Dissent (Weights & Biases) - Exploring PyTorch and Open-Source Communities (July 2023)
- The Gradient Podcast - Episode 66: PyTorch's history, design philosophy, and the open-source ML ecosystem (March 2023)
- Untold Stories of Open Source - Personal journey: Hyderabad, Vellore, New York, and getting into AI (September 2022)
- Talking PyTorch and Careers in AI - Udacity, with Mat Leonard (2018)
- TWIML AI Podcast - Talk #70: "PyTorch: Fast Differentiable Dynamic Graphs in Python" - recorded at Strange Loop (November 2017)
Talks & Presentations
PyTorch: Design, Ecosystem & Future
- Fireside Chat - Lightspeed Generative NYC (2024)
- Ray Summit 2022 Day 1 Keynote - Anyscale Ray Summit (2022)
- PyTorch and the Journey in Open Source - JuliaCon 2021 Keynote (2021)
- Growing Open Source: from Torch to PyTorch - Scale TransformX (2021)
- A Vision for the Future of ML Frameworks - Data + AI Summit, GPU Technology Conference (2021)
- PyTorch: an ecosystem for deep learning - Spark AI Summit, London (2018)
- PyTorch 1.0 Deep Dive - PyTorch Developer Conference (2018)
- Fast Differentiable Dynamic Graphs in Python - Strange Loop Conference, St. Louis (2017)
- PyTorch: a framework for fast, dynamic deep learning - EuroSciPy Keynote, Erlangen (2017)
- Dynamic Deep Learning: a paradigm shift in AI research and tools - O'Reilly AI Conference, New York (2017)
- Dynamic Deep Learning - Machines Can See, Moscow (2017)
- Dynamic Deep Learning - MLConf, New York (2017)
- A Dynamic View of the Deep Learning World - AI Frontiers Conference, San Jose (2017)
- Dynamic Deep Learning: a paradigm shift in AI Research and Tools - Applied ML Days, Lausanne (2018)
- The deep learning revolution: rethinking machine learning pipelines - Philly ETE (YouTube, InfoQ) (2015)
Additional appearances
- PyTorch: the strategic and psychological aspects of our growth - Runway ML, New York (2023)
- GPT Cope - AI For Good Hackathon, New York (2023)
- Compile and Train with 43% Speedup using PyTorch 2.0 - NVIDIA GTC, San Jose (2023)
- Deep Learning Systems: the platforms powering research and innovation - Foundation for Armenian Science and Technology, Yerevan (2019)
- Training AI Models Faster With Distributed Training in PyTorch - GPU Technology Conference, San Jose (2019)
- Building Machine Learning Tools - ACM KDD: Data Science in India, London (2018)
- Software for Deep Learning: PyTorch and Others - ACM KDD: Workshop on Deep Learning, London (2018)
- Deep Learning Systems at Scale - GPU Technology Conference Washington DC, ACM ICMR New York, IBM T.J. Watson Research Center (2016)
- Embedded Deep Learning - IEEE ESTIMedia, Pittsburgh (2016)
- Distributed Deep Learning at Scale - GPU Technology Conference, San Jose (2016)
- PyTorch: the past, the present, the future - AICON 2022 Keynote, Hangzhou, China (2022)
- PyTorch: a fast and flexible deep learning framework - GPU Technology Conference, San Jose (2018)
- Usable while performant: the challenges of building PyTorch - IBM AI Systems Day, Boston (2018)
- PyTorch - Dynamic Graph Frameworks - GPU Technology Conference, San Jose (2017)
- Deep Learning using PyTorch - Open Data Science Conference, Boston (2017)
- A deep dive on PyTorch - University of Washington Deep Learning Systems Course (2017)
- An overview of Deep Learning Frameworks and an introduction to PyTorch - a2-dlearn, Ann Arbor (2017)
- Coding papers in PyTorch (or any other framework) - NeurIPS Workshop, Montreal (2017)
- An update on PyTorch - NeurIPS Workshop, Montreal (2017)
Generative Adversarial Networks (GANs)
- How to Train a GAN - ICCV Tutorial Venice (2017), NeurIPS Workshop on Adversarial Training Montreal (2016)
- Generative Models for Images and Videos, a Focus on Adversarial Networks - National Tsing Hua University, Taiwan (Part 1, Part 2) (2017)
- Predicting the future using Deep Adversarial Networks - MLConf, New York (2016)
- Unsupervised Learning using Adversarial Networks - Rework Machine Learning Summit (2016)
- A path to unsupervised learning through adversarial networks - New York AI Meetup, London Machine Learning Meetup (2016)
- Adversarial Networks using Laplacian Pyramids - NeurIPS, Montreal (2015)
Additional appearances
- The Adversarial Networks Nonsense - Stat212b at UC Berkeley (2016)
- Generative adversarial networks for unsupervised learning - IIT Kanpur, India (2016)
AI Industry, Future & Leadership
- Unapologetically Open Science -- the complexity and challenges of making openness win! - ICML 2024 Keynote, Vienna (July 2024)
- Personal, Local, Private AI Agents - AI Engineer World's Fair, San Francisco (June 2024)
- Fireside Chat with Merve Noyan - AI_dev Open Source GenAI & ML Summit (2024)
- AI is making us rethink everything (including software development) - ICSE 2024 Keynote, Lisbon (photos, highlight video) (2024)
- AI and the stuff built for AI -- are they actually useful for data science? - PyData NYC Keynote (2023)
- Increasing the impact of AI through better software - MLConf, New York (2019)
Additional appearances
- From Lab to Launch - Agentic Frontiers Panel - South Park Commons NYC (2025)
- Where is AI Hardware going? - AI Basecamp Panel, Healdsburg (2024)
- AMD Q&A with Lisa Su (CEO) and Peter Lim (President) - AMD Data Center and AI Event, San Francisco (2023)
- The future of AI - Amazon AI Leadership Meetup Panel, New York (2023)
- Retraining yourself for a rapidly changing AI landscape - SnowFlake BUILD Keynote (2023)
- The impact of Large Language Models - Lightning DevCon Panel, New York (2022)
- Open Source AI - Linux Foundation Open Source Summit Panel, Dublin (2022)
- 2022 Predictions: What's next in data science, AI and ML? - Anaconda Webinar Panel (2021)
- Keynote on the future of AI - Taiwan Ministry of Science and Technology, Taipei (2017)
Torch7 & Early Deep Learning
- Applied Deep Learning for Vision, Natural Language and Audio with Torch7 - GPU Technology Conference Tutorial, San Jose (2015)
- The current landscape of Deep Learning: trends and challenges - IIIT Hyderabad, India (2015)
Additional appearances
- Torch: updates on the deep learning framework - NeurIPS, Montreal (2016)
- Torch: growing an open-source ecosystem - ICML, New York (2016)
- Torch: A Flexible Platform for Deep Learning Research - GPU Technology Conference, San Jose (2016)
- Torch: growing a research platform for cutting edge AI - DALI Workshop, Sestri Levante (2016)
- Object Detection Methods for Common objects in context - IIIT Hyderabad, India (2016)
- Deep Learning, Tools and Methods Workshop - IDIAP Research Institute, Martigny (2016)
- Introduction to Torch - NYU Machine Learning Course (2015)
- Torch tutorial on video-classification - The next.ml Conference, San Francisco (2015)
- Applied Deep Learning for Computer Vision with Torch - CVPR Workshop, Boston (2015)
- Deep Networks and tackling Kaggle - Cooper Union, New York (2015)
Tutorials & Summer Schools
- An Introduction to PyTorch - EPFL Lausanne (2018), Johns Hopkins University Baltimore, GeorgiaTech Atlanta, CIFAR/CRM Deep Learning Summer School Montreal (2017)
Additional appearances
- Graph Neural Networks - Deep Learning Summer School, Hyderabad (2019)
- Automatic Differentiation, PyTorch and Graph Neural Networks - IPAM Workshop, Los Angeles (2019)
- Generative Models - CUSO Winter School Lenk Switzerland (2019), Deep Learning Summer School Hyderabad (2018)
- Automatic Differentiation and Deep Learning - International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Saas-Fee (2019)
- Introduction to Deep Learning using PyTorch - ACM Seminar at NYU (2017)
- PyTorch: a framework for fast, dynamic deep learning - GPU Technology Conference, Munich (2017)
Robotics & Embodied AI
- CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory - LangRob Workshop at CoRL, Auckland (2022)
Press Coverage
Leaving Meta & Joining Thinking Machines Lab (2025)
- The Information - "PyTorch Co-Founder is Leaving Meta"
- Yahoo Finance / Business Insider - "A top Meta AI researcher has joined Mira Murati's Thinking Machines Lab"
- Hacker News - "Leaving Meta and PyTorch" - front page
- Built In - "Inside Thinking Machines Lab, Mira Murati's New AI Startup"
More coverage
- GuruFocus - "Meta's AI Leader Joins Thinking Machines Amid AI Industry Shakeup"
- IndexBox - "PyTorch Creator Soumith Chintala Joins Mira Murati's Thinking Machines Lab"
- SiliconANGLE - "Thinking Machines makes its Tinker AI fine-tuning service generally available"
- CXO Digitalpulse - "Soumith Chintala Joins Thinking Machines Lab After Leaving Meta"
- GIGAZINE - "Inventor of PyTorch, a key platform for AI development, leaves Meta"
- American Bazaar - "Indian American AI pioneer Soumith Chintala to leave Meta"
- New India Abroad - "Indian American AI pioneer Soumith Chintala to leave Meta"
- India News Network - "Soumith Chintala: From Tier 2 College to AI Leader at Meta"
- Inshorts - "Who is Indian-origin techie Soumith Chintala, who quit Meta after 11 years?"
- WebProNews - "PyTorch Creator's Bold Leap to Murati's AI Startup Shakes Up Tech Landscape"
- Byteiota - "PyTorch Creator Soumith Chintala Leaves Meta for 'Small'"
- 36Kr - "PyTorch Father Posts Long Resignation Letter to Bid Farewell to Meta"
PyTorch: Growth, Releases & Adoption
- VentureBeat - "PyTorch 2.0 release accelerates open-source machine learning" (March 2023)
- InfoQ - "PyTorch Becomes Linux Foundation Top-Level Project" (October 2022)
- Linux Foundation - "Meta Transitions PyTorch to the Linux Foundation" (September 2022)
- VentureBeat - "OpenAI goes all-in on Facebook's PyTorch machine learning framework" (2019)
- Business Insider - "Everything you need to know about PyTorch, the world's fastest-growing AI project" (2019)
- TechCrunch - "Facebook announces PyTorch 1.0, a more unified AI framework" (May 2018)
- Meta Engineering Blog - "PyTorch developer ecosystem expands, 1.0 stable release now available" (December 2018)
More coverage
- InfoQ - "PyTorch 2.0 Compiler Improves Model Training Speed" (March 2023)
- Analytics India Magazine - "PyTorch 2.0 Promises 100% Backward Compatibility" (2023)
- VentureBeat - "Facebook launches PyTorch 1.1 with TensorBoard support" (2019)
- InfoWorld - "Microsoft speeds up PyTorch with DeepSpeed" (2020)
- The Register - "Something to fire up PyTorch fans, Facebook emits code for analyzing human poses" (2019)
- Analytics India - "How PyTorch is increasingly being adopted by organizations" (2019)
- TechRepublic - "Data science: Which technologies are hot (and which are not)?" (2019)
- Analytics India - "CalTech uses PyTorch to build smooth landing drones" (2019)
- Synced - "Japanese Unicorn Preferred Networks Migrates Its DL Platform to PyTorch" (2019)
- GitHub Annual Report - 2nd fastest growing technology overall (2018)
- StackOverflow Developer Survey - Top-10 used frameworks in all of programming (2018/2019)
Torch7 & Facebook AI Open Source (2015)
- TechCrunch - "Facebook Open-Sources Some Of Its Deep-Learning Tools"
- VentureBeat - "Facebook open sources its cutting-edge deep learning tools"
More coverage
- New York Times - Quentin Hardy - "Facebook Offers Artificial Intelligence Tech to Open Source Group"
- Wired Magazine - Klint Finley - "Facebook Open-Sources a Trove of AI Tools"
- GigaOm - Derrick Harris - "Facebook open sources tools for bigger, faster deep learning models"
- PCWorld - "Facebook open-sources new AI smarts"
- FastCompany - "How Facebook's Massive Open-source push delivers better code"
- The Verge - "Facebook is opening up some of its AI research for public use"
- ZDNet - "Facebook open sources AI tools, possibly turbo charges deep learning"
- LeMonde Informatique - "Le Lab de Facebook offre ses technologies d'intelligence artificielle"
Generative Adversarial Networks (GANs) Research
- Bloomberg - Jack Clark - "Computers Learn How to Paint Whatever You Tell Them To" (December 2015)
- Scientific American - "When Will Computers Have Common Sense? Ask Facebook" (2016)
- VICE Magazine - "The Story Behind the Cover" - DCGAN-generated magazine cover (February 2016)
- Future of Life Institute - "Top A.I. Breakthroughs of 2015"
- KDnuggets - "The Rise of Generative Adversarial Networks" - features DCGAN paper (2019)
More coverage
- Wired Magazine - Cade Metz - "Facebook's New AI can paint, but Google's knows how to party" (2015)
- New Scientist - "Computers learn to create photos of bedrooms and faces on demand" (2015)
Facebook/Meta AI Research (FAIR)
- Meta Engineering Blog - "FAIR at 5: Facebook Artificial Intelligence Research accomplishments" (December 2018)
- The Next Web - "How Facebook's Yann LeCun is charting a path to human-level artificial intelligence" (2018)
Profiles & Features
- Lightspeed Venture Partners - "Highlights from #GenNYC: PyTorch Co-Founder on The Evolution of PyTorch" (2024)
- VentureBeat - "Top minds in machine learning predict where AI is going in 2020" (2020)
- Dataconomy - "15 Global Influencers in Artificial Intelligence and Machine Learning" (2018)
More profiles
- Web SoftTech - "Who Is Soumith Chintala? All About the Man Powering Meta's AI and PyTorch"
- Leviathan Encyclopedia - Comprehensive profile
- DeepAI - Profile
- AI Blog - People in AI - Profile
- IQ.wiki - Encyclopedia entry