DeepMind's TacticAI: an AI assistant for football tactics | Petar Veliฤkoviฤ‡

The AI Epiphany ยท Beginner ยท๐Ÿ“ฐ AI News & Updates ยท2y ago
Become a Patreon: https://www.patreon.com/theaiepiphany ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Join our Discord community: https://discord.gg/peBrCpheKE Petar Velickovic joined us to share more on his latest work - TacticAI - an AI assistant for football tactics! โ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌ TacticAI: an AI assistant for football tactics: https://arxiv.org/abs/2310.10553 โ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌ โŒš๏ธ Timetable: 00:00:00 - 00:00:39 Intro 00:00:39 - 00:02:20 Hyperstack GPUs (sponsored) 00:02:20 - 00:10:15 Why AI for football? 00:10:15 - 00:17:50 DeepMind's collaboration with Liverpool FC 00:17:50 - 00:39:00 TacticAI 00:39:00 - 00:53:45 Quantitative & human evaluation 00:53:45 - 00:58:25 Greatest hits from TacticAI 00:58:25 - 01:05:58 Outro / Q&A โ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌ ๐Ÿ’ฐ SPONSOR The AI Epiphany - https://www.patreon.com/theaiepiphany One-time donation - https://www.paypal.com/paypalme/theaiepiphany Huge thank you to these AI Epiphany patreons: Eli Mahler Petar Veliฤkoviฤ‡ โ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌ ๐Ÿ’ผ LinkedIn - https://www.linkedin.com/in/aleksagordic/ ๐Ÿฆ Twitter - https://twitter.com/gordic_aleksa ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Discord - https://discord.gg/peBrCpheKE ๐Ÿ“บ YouTube - https://www.youtube.com/c/TheAIEpiphany/ ๐Ÿ“š Medium - https://gordicaleksa.medium.com/ ๐Ÿ’ป GitHub - https://github.com/gordicaleksa ๐Ÿ“ข AI Newsletter - https://aiepiphany.substack.com/ โ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌโ–ฌ #tacticai #football #deepmind
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1 Intro | Neural Style Transfer #1
Intro | Neural Style Transfer #1
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 2 Basic Theory | Neural Style Transfer #2
Basic Theory | Neural Style Transfer #2
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 3 Optimization method | Neural Style Transfer #3
Optimization method | Neural Style Transfer #3
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 4 Advanced Theory | Neural Style Transfer #4
Advanced Theory | Neural Style Transfer #4
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 6 What is Computer Vision? | The Art of Creating Seeing Machines
What is Computer Vision? | The Art of Creating Seeing Machines
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 7 Feed-forward method | Neural Style Transfer #5
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 8 Alan Turing | Computing Machinery and Intelligence
Alan Turing | Computing Machinery and Intelligence
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 9 Feed-forward method (training) | Neural Style Transfer #6
Feed-forward method (training) | Neural Style Transfer #6
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 10 What is Google Deep Dream? (Basic Theory) | Deep Dream Series #1
What is Google Deep Dream? (Basic Theory) | Deep Dream Series #1
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 11 Semantic Segmentation in PyTorch | Neural Style Transfer #7
Semantic Segmentation in PyTorch | Neural Style Transfer #7
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 12 How to get started with Machine Learning
How to get started with Machine Learning
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How to learn PyTorch? (3 easy steps) | 2021
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PyTorch or TensorFlow?
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3 Machine Learning Projects For Beginners (Highly visual) | 2021
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Machine Learning Projects (Intermediate level) | 2021
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 17 Cheapest (0$) Deep Learning Hardware Options | 2021
Cheapest (0$) Deep Learning Hardware Options | 2021
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 18 How to learn deep learning? (Transformers Example)
How to learn deep learning? (Transformers Example)
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 19 How do transformers work? (Attention is all you need)
How do transformers work? (Attention is all you need)
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 20 Developing a deep learning project (case study on transformer)
Developing a deep learning project (case study on transformer)
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 21 Vision Transformer (ViT) - An image is worth 16x16 words | Paper Explained
Vision Transformer (ViT) - An image is worth 16x16 words | Paper Explained
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 22 GPT-3 - Language Models are Few-Shot Learners | Paper Explained
GPT-3 - Language Models are Few-Shot Learners | Paper Explained
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 23 Google DeepMind's AlphaFold 2 explained! (Protein folding, AlphaFold 1, a glimpse into AlphaFold 2)
Google DeepMind's AlphaFold 2 explained! (Protein folding, AlphaFold 1, a glimpse into AlphaFold 2)
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 24 Attention Is All You Need (Transformer) | Paper Explained
Attention Is All You Need (Transformer) | Paper Explained
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 25 Graph Attention Networks (GAT) | GNN Paper Explained
Graph Attention Networks (GAT) | GNN Paper Explained
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 26 Graph Convolutional Networks (GCN) | GNN Paper Explained
Graph Convolutional Networks (GCN) | GNN Paper Explained
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 27 Graph SAGE - Inductive Representation Learning on Large Graphs | GNN Paper Explained
Graph SAGE - Inductive Representation Learning on Large Graphs | GNN Paper Explained
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 28 PinSage - Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Paper Explained
PinSage - Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Paper Explained
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 29 OpenAI CLIP - Connecting Text and Images | Paper Explained
OpenAI CLIP - Connecting Text and Images | Paper Explained
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 30 Temporal Graph Networks (TGN) | GNN Paper Explained
Temporal Graph Networks (TGN) | GNN Paper Explained
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 31 Graph Neural Network Project Update! (I'm coding GAT from scratch)
Graph Neural Network Project Update! (I'm coding GAT from scratch)
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 32 Graph Attention Network Project Walkthrough
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How to get started with Graph ML? (Blog walkthrough)
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 34 DQN - Playing Atari with Deep Reinforcement Learning | RL Paper Explained
DQN - Playing Atari with Deep Reinforcement Learning | RL Paper Explained
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 35 AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained
AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained
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 36 DeepMind's AlphaGo Zero and AlphaZero | RL paper explained
DeepMind's AlphaGo Zero and AlphaZero | RL paper explained
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 37 OpenAI - Solving Rubik's Cube with a Robot Hand | RL paper explained
OpenAI - Solving Rubik's Cube with a Robot Hand | RL paper explained
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MuZero - Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model | RL Paper explained
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 39 EfficientNetV2 - Smaller Models and Faster Training | Paper explained
EfficientNetV2 - Smaller Models and Faster Training | Paper explained
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 40 Implementing DeepMind's DQN from scratch! | Project Update
Implementing DeepMind's DQN from scratch! | Project Update
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 41 MLP-Mixer: An all-MLP Architecture for Vision | Paper explained
MLP-Mixer: An all-MLP Architecture for Vision | Paper explained
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 42 DeepMind's Android RL Environment - AndroidEnv
DeepMind's Android RL Environment - AndroidEnv
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 43 When Vision Transformers Outperform ResNets without Pretraining | Paper Explained
When Vision Transformers Outperform ResNets without Pretraining | Paper Explained
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 44 Non-Parametric Transformers | Paper explained
Non-Parametric Transformers | Paper explained
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 45 Chip Placement with Deep Reinforcement Learning | Paper Explained
Chip Placement with Deep Reinforcement Learning | Paper Explained
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Text Style Brush - Transfer of text aesthetics from a single example | Paper Explained
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 47 Graphormer - Do Transformers Really Perform Bad for Graph Representation? | Paper Explained
Graphormer - Do Transformers Really Perform Bad for Graph Representation? | Paper Explained
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 48 GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation | Paper Explained
GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation | Paper Explained
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 49 VQ-VAEs: Neural Discrete Representation Learning | Paper + PyTorch Code Explained
VQ-VAEs: Neural Discrete Representation Learning | Paper + PyTorch Code Explained
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 50 VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained
VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained
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 51 Multimodal Few-Shot Learning with Frozen Language Models | Paper Explained
Multimodal Few-Shot Learning with Frozen Language Models | Paper Explained
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 52 Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers
Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers
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 53 AudioCLIP: Extending CLIP to Image, Text and Audio | Paper Explained
AudioCLIP: Extending CLIP to Image, Text and Audio | Paper Explained
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 54 RMA: Rapid Motor Adaptation for Legged Robots | Paper Explained
RMA: Rapid Motor Adaptation for Legged Robots | Paper Explained
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 55 DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained
DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained
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 56 DETR: End-to-End Object Detection with Transformers | Paper Explained
DETR: End-to-End Object Detection with Transformers | Paper Explained
Aleksa Gordiฤ‡ - The AI Epiphany
 57 DINO: Emerging Properties in Self-Supervised Vision Transformers | Paper Explained!
DINO: Emerging Properties in Self-Supervised Vision Transformers | Paper Explained!
Aleksa Gordiฤ‡ - The AI Epiphany
 58 DeepMind DetCon: Efficient Visual Pretraining with Contrastive Detection | Paper Explained
DeepMind DetCon: Efficient Visual Pretraining with Contrastive Detection | Paper Explained
Aleksa Gordiฤ‡ - The AI Epiphany
 59 Do Vision Transformers See Like Convolutional Neural Networks? | Paper Explained
Do Vision Transformers See Like Convolutional Neural Networks? | Paper Explained
Aleksa Gordiฤ‡ - The AI Epiphany
 60 Fastformer: Additive Attention Can Be All You Need | Paper Explained
Fastformer: Additive Attention Can Be All You Need | Paper Explained
Aleksa Gordiฤ‡ - The AI Epiphany

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Chapters (8)

00:00:39 Intro
0:39 00:02:20 Hyperstack GPUs (sponsored)
2:20 00:10:15 Why AI for football?
10:15 00:17:50 DeepMind's collaboration with Liverpool FC
17:50 00:39:00 TacticAI
39:00 00:53:45 Quantitative & human evaluation
53:45 00:58:25 Greatest hits from TacticAI
58:25 01:05:58 Outro / Q&A
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