Andrew Brock on Generative Models and His Journey to AI Research

HuggingFace · Advanced ·📐 ML Fundamentals ·4y ago
Andrew Brock is a deep learning researcher at DeepMind focusing on fundamental neural network training, efficiency & scalability, generative models, and computer vision. He is widely known as being the first author on the famous BigGAN paper, and was also a contributor to the Perceiver and Perceiver IO papers. In this chat, we talk about his interesting journey to becoming an AI researcher, his work on generative models, and where he sees the field of generative machine learning going. Andrew's Twitter: https://twitter.com/ajmooch Don't have a Hugging Face account? Join, it's free: http://huggingface.co/join Have a question? Checkout the forums: https://discuss.huggingface.co 👾 Join our Discord: https://hf.co/join/discord
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from HuggingFace · HuggingFace · 0 of 60

← Previous Next →
1 The Future of Natural Language Processing
The Future of Natural Language Processing
HuggingFace
 2 Trends in Model Size & Computational Efficiency in NLP
Trends in Model Size & Computational Efficiency in NLP
HuggingFace
 3 Increasing Data Usage in Natural Language Processing
Increasing Data Usage in Natural Language Processing
HuggingFace
 4 In Domain & Out of Domain Generalization in the Future of NLP
In Domain & Out of Domain Generalization in the Future of NLP
HuggingFace
 5 The Limits of NLU & the Rise of NLG in the Future of NLP
The Limits of NLU & the Rise of NLG in the Future of NLP
HuggingFace
 6 The Lack of Robustness in the Future of NLP
The Lack of Robustness in the Future of NLP
HuggingFace
 7 Inductive Bias, Common Sense, Continual Learning in The Future of NLP
Inductive Bias, Common Sense, Continual Learning in The Future of NLP
HuggingFace
 8 Train a Hugging Face Transformers Model with Amazon SageMaker
Train a Hugging Face Transformers Model with Amazon SageMaker
HuggingFace
 9 What is Transfer Learning?
What is Transfer Learning?
HuggingFace
 10 The pipeline function
The pipeline function
HuggingFace
 11 Navigating the Model Hub
Navigating the Model Hub
HuggingFace
 12 Transformer models: Decoders
Transformer models: Decoders
HuggingFace
 13 The Transformer architecture
The Transformer architecture
HuggingFace
 14 Transformer models: Encoder-Decoders
Transformer models: Encoder-Decoders
HuggingFace
 15 Transformer models: Encoders
Transformer models: Encoders
HuggingFace
 16 Keras introduction
Keras introduction
HuggingFace
 17 The push to hub API
The push to hub API
HuggingFace
 18 Fine-tuning with TensorFlow
Fine-tuning with TensorFlow
HuggingFace
 19 Learning rate scheduling with TensorFlow
Learning rate scheduling with TensorFlow
HuggingFace
 20 TensorFlow Predictions and metrics
TensorFlow Predictions and metrics
HuggingFace
 21 Welcome to the Hugging Face course
Welcome to the Hugging Face course
HuggingFace
 22 The tokenization pipeline
The tokenization pipeline
HuggingFace
 23 Supercharge your PyTorch training loop with Accelerate
Supercharge your PyTorch training loop with Accelerate
HuggingFace
 24 The Trainer API
The Trainer API
HuggingFace
 25 Batching inputs together (PyTorch)
Batching inputs together (PyTorch)
HuggingFace
 26 Batching inputs together (TensorFlow)
Batching inputs together (TensorFlow)
HuggingFace
 27 Hugging Face Datasets overview (Pytorch)
Hugging Face Datasets overview (Pytorch)
HuggingFace
 28 Hugging Face Datasets overview (Tensorflow)
Hugging Face Datasets overview (Tensorflow)
HuggingFace
 29 What is dynamic padding?
What is dynamic padding?
HuggingFace
 30 What happens inside the pipeline function? (PyTorch)
What happens inside the pipeline function? (PyTorch)
HuggingFace
 31 What happens inside the pipeline function? (TensorFlow)
What happens inside the pipeline function? (TensorFlow)
HuggingFace
 32 Instantiate a Transformers model (PyTorch)
Instantiate a Transformers model (PyTorch)
HuggingFace
 33 Instantiate a Transformers model (TensorFlow)
Instantiate a Transformers model (TensorFlow)
HuggingFace
 34 Preprocessing sentence pairs (PyTorch)
Preprocessing sentence pairs (PyTorch)
HuggingFace
 35 Preprocessing sentence pairs (TensorFlow)
Preprocessing sentence pairs (TensorFlow)
HuggingFace
 36 Write your training loop in PyTorch
Write your training loop in PyTorch
HuggingFace
 37 Managing a repo on the Model Hub
Managing a repo on the Model Hub
HuggingFace
 38 Chapter 1 Live Session with Sylvain
Chapter 1 Live Session with Sylvain
HuggingFace
 39 Chapter 2 Live Session with Lewis
Chapter 2 Live Session with Lewis
HuggingFace
 40 The push to hub API
The push to hub API
HuggingFace
 41 Chapter 2 Live Session with Sylvain
Chapter 2 Live Session with Sylvain
HuggingFace
 42 Chapter 3 live sessions with Lewis (PyTorch)
Chapter 3 live sessions with Lewis (PyTorch)
HuggingFace
 43 Day 1 Talks: JAX, Flax & Transformers 🤗
Day 1 Talks: JAX, Flax & Transformers 🤗
HuggingFace
 44 Day 2 Talks: JAX, Flax & Transformers 🤗
Day 2 Talks: JAX, Flax & Transformers 🤗
HuggingFace
 45 Day 3 Talks JAX, Flax, Transformers 🤗
Day 3 Talks JAX, Flax, Transformers 🤗
HuggingFace
 46 Chapter 4 live sessions with Omar
Chapter 4 live sessions with Omar
HuggingFace
 47 Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker
Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker
HuggingFace
 48 Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker
Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker
HuggingFace
 49 Run a Batch Transform Job using Hugging Face Transformers and Amazon SageMaker
Run a Batch Transform Job using Hugging Face Transformers and Amazon SageMaker
HuggingFace
 50 [Webinar] How to add machine learning capabilities with just a few lines of code
[Webinar] How to add machine learning capabilities with just a few lines of code
HuggingFace
 51 Hugging Face + Zapier Demo Video
Hugging Face + Zapier Demo Video
HuggingFace
 52 Hugging Face + Google Sheets Demo
Hugging Face + Google Sheets Demo
HuggingFace
 53 Hugging Face Infinity Launch - 09/28
Hugging Face Infinity Launch - 09/28
HuggingFace
 54 Build and Deploy a Machine Learning App in 2 Minutes
Build and Deploy a Machine Learning App in 2 Minutes
HuggingFace
 55 Hugging Face Infinity - GPU Walkthrough
Hugging Face Infinity - GPU Walkthrough
HuggingFace
 56 Otto - 🤗 Infinity Case Study
Otto - 🤗 Infinity Case Study
HuggingFace
 57 Workshop: Getting started with Amazon Sagemaker Train a Hugging Face Transformers and deploy it
Workshop: Getting started with Amazon Sagemaker Train a Hugging Face Transformers and deploy it
HuggingFace
 58 Workshop: Going Production: Deploying, Scaling & Monitoring Hugging Face Transformer models
Workshop: Going Production: Deploying, Scaling & Monitoring Hugging Face Transformer models
HuggingFace
 59 🤗 Tasks: Causal Language Modeling
🤗 Tasks: Causal Language Modeling
HuggingFace
 60 🤗 Tasks: Masked Language Modeling
🤗 Tasks: Masked Language Modeling
HuggingFace

Related AI Lessons

⚡
AI is heading toward a wall, and most people still don’t see it...
AI development is facing a significant obstacle due to increasing inference costs and memory requirements, which will impact its scalability and efficiency
Dev.to · Gary Doman/TizWildin
 ⚡
gradient improvement tree GBT, ridge regression, Lasso regression, support vector machine SVM to…
Learn to improve gradient boosting trees with ridge and lasso regression, and compare with support vector machines for better predictive models
Medium · Machine Learning
 ⚡
Struktur Data: Hashing
Learn the fundamentals of hashing in data structures and its importance in programming
Medium · Programming
 ⚡
vite HMR is silently the reason ur laptop fan wont stop
Vite's HMR feature can cause high CPU usage and laptop fan noise, learn how to identify and fix the issue
Dev.to · BaoDev Studio
Up next
Tapping Into the Zen of Python: Reading the Poem & Understanding the History
Real Python
Watch →