02:12

RevEye Reverse Image Search 2

02:49

ChatGPT 4 system prompt (December 16, 2023)

00:07

ChatGPT 3.5 system prompt (December 16, 2023)

00:42

GitHub Copilot demonstration October 2023 (part 2)

02:14

GitHub Copilot demonstration October 2023 (part 1)

01:06

Demo of ChatGPT's visual capabilities (Oct. 2023)

02:22

Demo of ChatGPT's Advanced Data Analysis (Oct. 2023)

02:31

Geometric reasoning with ChatGPT and GeoGebra, part 2

00:25

ChatGPT 3 minute presentation

03:00

Copilot demonstration April 2023

01:07

Using ChatPDF to chat with an astrophysics paper

11:24

Using D-ID to create a talking avatar video

03:12

Using ChatPDF to automatically generate Python code from pseudocode in an academic article

03:09

Geometric reasoning with ChatGPT and GeoGebra, part 1

01:13

RevEye Reverse Image Search

39:30

Aki Vehtari: Stan and probabilistic programming (MLSP 2020 tutorial)

46:59

Razvan Pascanu: Improving learning efficiency for deep neural networks (MLSP 2020 keynote)

01:00:57

Ole Winther: Latent variable models from independent components to VAEs and flows (MLSP2020 keynote)

52:32

Michael Unser: Splines and Machine Learning: From classical RKHS methods to DNN (MLSP 2020 keynote)

13:39

Truyen Tran - Learning to Remember More with Less Memorization (ICLR 2019 talk)

18:58

Robert Geirhos: ImageNet-trained CNNs are biased towards texture (ICLR 2019 talk)

57:06

John M. Abowd: The U.S. Census Bureau Tries to be a Good Data Steward in the 21st Century

01:03:01

ICLR Debate with Leslie Kaelbling (ICLR 2019)

13:08

Yikang Shen: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks (ICLR2019)

46:39

Pierre-Yves Oudeyer: Developmental Autonomous Learning (ICLR 2019 invited talk)

43:06

Ian Goodfellow: Adversarial Machine Learning (ICLR 2019 invited talk)

15:05

J. Frankle & M. Carbin: The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

02:04:01

Susan Athey: Counterfactual Inference (NeurIPS 2018 Tutorial)

01:59:15

Alex Graves and Marc'Aurelio Ranzato: Unsupervised Deep Learning (NeurIPS 2018 Tutorial)

02:02:26

Frank Hutter and Joaquin Vanschoren: Automatic Machine Learning (NeurIPS 2018 Tutorial)

01:58:09

Shawe-Taylor and Rivasplata: Statistical Learning Theory - a Hitchhiker's Guide (NeurIPS 2018)

01:55:16

Common Pitfalls for Studying the Human Side of Machine Learning (NeurIPS 2018 Tutorial)

02:07:57

David Dunson: Scalable Bayesian Inference (NeurIPS 2018 Tutorial)

02:00:03

J. Z. Kolter and A. Madry: Adversarial Robustness - Theory and Practice (NeurIPS 2018 Tutorial)

02:00:23

Fernanda Viégas and Martin Wattenberg: Visualization for Machine Learning (NeurIPS 2018 Tutorial)

06:09

Evolution of Apache Spark (September 12, 2018)

05:31

Evolution of Apache Hadoop (September 11, 2018)

02:13:57

Sanjeev Arora: Toward Theoretical Understanding of Deep Learning (ICML 2018 tutorial)

01:00:33

Dawn Song: AI and Security: Lessons, Challenges and Future Directions (ICML 2018 invited talk)

01:12:24

Josh Tenenbaum: Building Machines that Learn and Think Like People (ICML 2018 invited talk)

02:05:38

Benjamin Recht: Optimization Perspectives on Learning to Control (ICML 2018 tutorial)

02:07:24

Understanding your Neighbors: Practical Perspectives From Modern Analysis (ICML 2018 tutorial)

02:22:04

Yisong Yue and Hoang M Le: Tutorial on Imitation Learning (ICML 2018 tutorial)

02:17:50

Tamara Broderick: Variational Bayes and Beyond: Bayesian Inference for Big Data (ICML 2018 tutorial)

02:15:29

Machine Learning in Automated Mechanism Design for Pricing and Auctions (ICML 2018 tutorial)

01:01:31

Max Welling: Intelligence per Kilowatthour (ICML 2018 invited talk)

01:40

Evolution of OpenAI Gym (May 15th, 2018)

01:29

Evolution of CleverHans (May 15th, 2018)

47:39

Kristen Grauman: Visual Learning With Unlabeled Video and Look-Around Policies ICLR2018 invited talk

36:10

Fireside Chat with Daphne Koller (ICLR 2018)

46:23

Christopher D Manning: A Neural Network Model That Can Reason (ICLR 2018 invited talk)

49:24

Joelle Pineau: Reproducibility, Reusability, and Robustness in Deep Reinforcement Learning ICLR 2018

50:22

Blake Richards: Deep Learning with Ensembles of Neocortical Microcircuits (ICLR 2018 invited talks)

45:32

Koray Kavukcuoglu: From Generative Models to Generative Agents (ICLR 2018 invited talk)

48:54

Suchi Saria: Augmenting Clinical Intelligence with Machine Intelligence (ICLR 2018 invited talk)

43:12

Bernhard Schölkopf: Learning Causal Mechanisms (ICLR invited talk)

56:52

Erik Brynjolfsson: What Can Machine Learning Do? Workforce Implications (ICLR 2018)

01:01:46

Alex Acero: The Deep Learning Revolution (ICASSP 2018 plenary)

58:38

Luc Vincent: Transportation as a Service using a hybrid network of drivers and self-driving vehicles

58:44

Julia Hirschberg: "Detecting Deceptive Speech: Humans vs. Machines" (ICASSP 2018 plenary)