Henry AI Labs

This video explores Teacher-Student Curriculum Learning! Interestingly, the Teacher is rewarded for the Student's progress on Sub-Tasks rather than solely optimizing for progress on the hardest task, Intrinsic Motivation! https://youtu.be/GFCujBpTf3k  #100DaysOfMLCode

This video explores "Learning to Execute" using Sequence-to-Sequence LSTMs to predict the output of a Python program without running the code! I was really interested in this paper because of their exploration into Curriculum Learning! https://youtu.be/5rrldwJdDRE  #100DaysOfMLCode

AI Weekly update for February 3rd, 2020! This update covers Google AI's Meena Chatbot, Microsoft's ImageBERT, blog posts on Curriculum Learning in RL and Contrastive Self-Supervised Learning, and more! https://youtu.be/N9jsScucOXs  #100DaysOfMLCode

This video explains @GoogleAI 's amazing new Meena chatbot! An Evolved Transformer with 2.6B parameters on 341 GB / 40B words of conversation data to achieves remarkable chatbot performance! "Horses go to Hayvard!" https://youtu.be/STrrlLG15OY  #100DaysOfMLCode

This video covers the Evolved Transformer used in the mind-blowing Meena chatbot from @GoogleAI! This video explains the details of how they encode Transformers for automated architecture search! https://youtu.be/khA-fiC1Wa0  #100DaysOfMLCode

14th Edition of AI Weekly Update! Happy to get back to this after a 2 month break! Covering Point-Goal navigation in AI-Habitat from FAIR, FixMatch for Semi-Supervised Learning, OpenAI's study on scaling language models and more! https://youtu.be/s5wILiRE-6Q  #100DaysOfMLCode

This video explains FixMatch, a new Semi-Supervised Learning algorithm from @GoogleAI!! FixMatch enforces consistent predictions through Data Augmentation and Pseudo-Labeling to achieve remarkable success with limited labeled data! https://youtu.be/nkewn6XGyt8  #100DaysOfMLCode

This video explores the Reformer Efficient Transformer model! Locality-Sensitive Hashing matches inherent sparsity in attention to attend only to similar keys. Reversible layers reduce memory costs from storing intermediate activations! https://youtu.be/Kf3x3lqf9cQ  #100DaysOfMLCode

Grateful to have my article on "The Evolution of AlphaGo to MuZero" accepted by the Medium curators for Machine Learning articles! https://medium.com/p/the-evolution-of-alphago-to-muzero-c2c37306bf9?source=email-59216259c525--writer.postDistributed&sk=a8a9cee5706b36b07a08940b805f3410 … #100DaysOfMLCode

This video explains the evolution of AlphaGo to MuZero from @DeepMindAI! Going from policy nets trained with supervised learning on expert moves in Go, to an algorithm that does model-based planning in abstract space on 57 Atari games! https://youtu.be/A0HX8BgckFI  #100DaysOfMLCode

This video explains MuZero! MuZero uses hidden states to facilitate Model-Based RL through the self-play MCTS from the AlphaGo series. I also tried to provide an explanation of how Backprop through Time (BPTT) is used to train this! https://youtu.be/szbvm8aNDxw  #100DaysOfMLCode

This video explains AlphaZero from DeepMind in the series: AlphaGo to MuZero! AlphaZero doesn't dramatically change the previous AlphaGo Zero algorithm, but it does show how the algorithm can generalize to Chess and Shogi! https://youtu.be/4FdiTTZPkos  #100DaysOfMLCode

Extremely grateful for the promotion and endorsement of my YouTube channel in this Reddit Thread! The Machine Learning community is amazingly encouraging, hoping to improve these videos!https://www.reddit.com/r/MachineLearning/comments/elt7p6/n_henry_ai_labs_on_youtube/ …

This video explores AlphaGo Zero! AGZero avoids human encoded knowledge: no handcrafted features for state rep. and no supervised learning on expert moves. AGZero uses a really interesting extension to the MCTS self-play for training! https://youtu.be/B1MUfP1qqLs  #100DaysOfMLCode

This video explains how AlphaGo works! This is the first in a series explaining the evolution of AlphaGo to MuZero! AlphaGo uses convolutional policy and value networks to enhance their tree search! https://youtu.be/jgAj8CqcBBs  #100DaysOfMLCode

This is my recap of Artificial Intelligence in 2019! This video covers new developments in understanding Neural Networks, self-supervised learning, language models, Generative Models, Game-playing RL, and many more! https://youtu.be/6SWpN64Ivb4  #100DaysOfMLCode

Check out this repository organizing videos on Henry AI Labs! I've categorized videos based on general topics like "Generative Modeling" or "Neural Architecture Search", and I will continue to update this list with new videos! https://github.com/CShorten/HenryAILabs-VideoList … #100DaysOfMLCode