[ML NEWS] Apple scans your phone | Master Faces beat face recognition | WALL-E is real

Yannic Kilcher · Beginner ·📰 AI News & Updates ·4y ago
#mlnews #apple #nolamarck Your update on the latest news in the AI and Machine Learning world. OUTLINE: 0:00 - Intro 0:15 - Sponsor: Weights & Biases 3:30 - Apple to scan iDevices for illegal content 14:10 - EU approves chatcontrol 15:20 - Machine Learning FAQ book 17:40 - TimeDial & Disfl-QA Conversation Datasets 20:30 - VoxPopuli Speech Dataset 21:00 - Google Tensor chip coming to Pixel 6 21:30 - Pentagon uses AI to predict events 23:10 - Sketch your own GAN 24:45 - Can a Fruit Fly learn Word Embeddings? 26:00 - Master Faces beat facial recognition system 27:25 - PyTorch profiler 1.9 27:55 - 0 A.D. gets reinforcement learning interface 28:40 - BeatBot cleans up cigarette butts on the beach Sponsor: Weights & Biases https://wandb.ai References: Apple to scan iDevices for illegal content https://techcrunch.com/2021/08/05/apple-icloud-photos-scanning/ http://tylerneylon.com/a/lsh1/ EU approves chatcontrol https://european-pirateparty.eu/parliament-approves-chatcontrol/ Machine Learning FAQ book https://rentruewang.github.io/learning-machine/layers/emb/emb.html TimeDial & Disfl-QA: New datasets for conversational NLP https://ai.googleblog.com/2021/08/two-new-datasets-for-conversational-nlp.html VoxPopuli: Giant partially labeled speech dataset https://github.com/facebookresearch/voxpopuli Google's Tensor chip coming to Pixel 6 https://blog.google/products/pixel/google-tensor-debuts-new-pixel-6-fall/ Pentagon uses AI for predicting relevant events in advance https://www.engadget.com/pentagon-ai-predicts-days-in-advance-135509604.html?utm_source=pocket_mylist Sketch Your Own GAN https://peterwang512.github.io/GANSketching/ Can a fruit fly learn word embeddings? https://arxiv.org/pdf/2101.06887.pdf Master Faces for attacking facial recognition systems https://arxiv.org/pdf/2108.01077.pdf PyTorch Profiler v1.9 https://www.marktechpost.com/2021/08/06/pytorch-releases-pytorch-profiler-v1-9-with-new-features-to-help-diagnose-and-fix-machine-learning-performance
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1 Imagination-Augmented Agents for Deep Reinforcement Learning
Imagination-Augmented Agents for Deep Reinforcement Learning
Yannic Kilcher
 2 Learning model-based planning from scratch
Learning model-based planning from scratch
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 3 Reinforcement Learning with Unsupervised Auxiliary Tasks
Reinforcement Learning with Unsupervised Auxiliary Tasks
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 4 Attention Is All You Need
Attention Is All You Need
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 5 git for research basics: fundamentals, commits, branches, merging
git for research basics: fundamentals, commits, branches, merging
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 6 Curiosity-driven Exploration by Self-supervised Prediction
Curiosity-driven Exploration by Self-supervised Prediction
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 7 World Models
World Models
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 8 Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
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 9 Stochastic RNNs without Teacher-Forcing
Stochastic RNNs without Teacher-Forcing
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 10 What’s in a name? The need to nip NIPS
What’s in a name? The need to nip NIPS
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 11 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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 12 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Yannic Kilcher
 13 GPT-2: Language Models are Unsupervised Multitask Learners
GPT-2: Language Models are Unsupervised Multitask Learners
Yannic Kilcher
 14 Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
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 15 The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
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 16 Discriminating Systems - Gender, Race, and Power in AI
Discriminating Systems - Gender, Race, and Power in AI
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 17 Blockwise Parallel Decoding for Deep Autoregressive Models
Blockwise Parallel Decoding for Deep Autoregressive Models
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 18 S.H.E. - Search. Human. Equalizer.
S.H.E. - Search. Human. Equalizer.
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 19 Reinforcement Learning, Fast and Slow
Reinforcement Learning, Fast and Slow
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 20 Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
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 21 I'm at ICML19 :)
I'm at ICML19 :)
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 22 Population-Based Search and Open-Ended Algorithms
Population-Based Search and Open-Ended Algorithms
Yannic Kilcher
 23 XLNet: Generalized Autoregressive Pretraining for Language Understanding
XLNet: Generalized Autoregressive Pretraining for Language Understanding
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 24 Conversation about Population-Based Methods (Re-upload)
Conversation about Population-Based Methods (Re-upload)
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 25 Reconciling modern machine learning and the bias-variance trade-off
Reconciling modern machine learning and the bias-variance trade-off
Yannic Kilcher
 26 Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
Yannic Kilcher
 27 Manifold Mixup: Better Representations by Interpolating Hidden States
Manifold Mixup: Better Representations by Interpolating Hidden States
Yannic Kilcher
 28 Processing Megapixel Images with Deep Attention-Sampling Models
Processing Megapixel Images with Deep Attention-Sampling Models
Yannic Kilcher
 29 Gauge Equivariant Convolutional Networks and the Icosahedral CNN
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
Yannic Kilcher
 30 Auditing Radicalization Pathways on YouTube
Auditing Radicalization Pathways on YouTube
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 31 RoBERTa: A Robustly Optimized BERT Pretraining Approach
RoBERTa: A Robustly Optimized BERT Pretraining Approach
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 32 Dynamic Routing Between Capsules
Dynamic Routing Between Capsules
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 33 DEEP LEARNING MEME REVIEW - Episode 1
DEEP LEARNING MEME REVIEW - Episode 1
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 34 Accelerating Deep Learning by Focusing on the Biggest Losers
Accelerating Deep Learning by Focusing on the Biggest Losers
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 35 [News] The Siraj Raval Controversy
[News] The Siraj Raval Controversy
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 36 LeDeepChef 👨‍🍳 Deep Reinforcement Learning Agent for Families of Text-Based Games
LeDeepChef 👨‍🍳 Deep Reinforcement Learning Agent for Families of Text-Based Games
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 37 The Visual Task Adaptation Benchmark
The Visual Task Adaptation Benchmark
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 38 IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
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 39 AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning
AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning
Yannic Kilcher
 40 SinGAN: Learning a Generative Model from a Single Natural Image
SinGAN: Learning a Generative Model from a Single Natural Image
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 41 A neurally plausible model learns successor representations in partially observable environments
A neurally plausible model learns successor representations in partially observable environments
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 42 MuZero: Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
MuZero: Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
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 43 Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions
Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions
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 44 NeurIPS 19 Poster Session
NeurIPS 19 Poster Session
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 45 Go-Explore: a New Approach for Hard-Exploration Problems
Go-Explore: a New Approach for Hard-Exploration Problems
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 46 Reformer: The Efficient Transformer
Reformer: The Efficient Transformer
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 47 [Interview] Mark Ledwich - Algorithmic Extremism: Examining YouTube's Rabbit Hole of Radicalization
[Interview] Mark Ledwich - Algorithmic Extremism: Examining YouTube's Rabbit Hole of Radicalization
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 48 Turing-NLG, DeepSpeed and the ZeRO optimizer
Turing-NLG, DeepSpeed and the ZeRO optimizer
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 49 Growing Neural Cellular Automata
Growing Neural Cellular Automata
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 50 NeurIPS 2020 Changes to Paper Submission Process
NeurIPS 2020 Changes to Paper Submission Process
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 51 Deep Learning for Symbolic Mathematics
Deep Learning for Symbolic Mathematics
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 52 Online Education - How I Make My Videos
Online Education - How I Make My Videos
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 53 [Rant] coronavirus
[Rant] coronavirus
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 54 Axial Attention & MetNet: A Neural Weather Model for Precipitation Forecasting
Axial Attention & MetNet: A Neural Weather Model for Precipitation Forecasting
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 55 Agent57: Outperforming the Atari Human Benchmark
Agent57: Outperforming the Atari Human Benchmark
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 56 State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication
State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication
Yannic Kilcher
 57 Dream to Control: Learning Behaviors by Latent Imagination
Dream to Control: Learning Behaviors by Latent Imagination
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 58 POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and Solutions
POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and Solutions
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 59 Evaluating NLP Models via Contrast Sets
Evaluating NLP Models via Contrast Sets
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 60 [Drama] Who invented Contrast Sets?
[Drama] Who invented Contrast Sets?
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Related AI Lessons

Chapters (15)

Intro
0:15 Sponsor: Weights & Biases
3:30 Apple to scan iDevices for illegal content
14:10 EU approves chatcontrol
15:20 Machine Learning FAQ book
17:40 TimeDial & Disfl-QA Conversation Datasets
20:30 VoxPopuli Speech Dataset
21:00 Google Tensor chip coming to Pixel 6
21:30 Pentagon uses AI to predict events
23:10 Sketch your own GAN
24:45 Can a Fruit Fly learn Word Embeddings?
26:00 Master Faces beat facial recognition system
27:25 PyTorch profiler 1.9
27:55 0 A.D. gets reinforcement learning interface
28:40 BeatBot cleans up cigarette butts on the beach
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