NVIDIA Clocks World’s Fastest BERT Training Time and Largest Transformer Based Model, Paving Path For Advanced Conversational AI
https://devblogs.nvidia.com/training-bert-with-gpus/
https://devblogs.nvidia.com/training-bert-with-gpus/
NVIDIA Technical Blog
NVIDIA Clocks World’s Fastest BERT Training Time and Largest Transformer Based Model, Paving Path For Advanced Conversational AI
NVIDIA DGX SuperPOD trains BERT-Large in just 47 minutes, and trains GPT-2 8B, the largest Transformer Network Ever with 8.3Bn parameters Conversational AI is an essential building block of human…
The Illustrated GPT-2 (Visualizing Transformer Language Models)
https://jalammar.github.io/illustrated-gpt2/
https://jalammar.github.io/illustrated-gpt2/
jalammar.github.io
The Illustrated GPT-2 (Visualizing Transformer Language Models)
Discussions:
Hacker News (64 points, 3 comments), Reddit r/MachineLearning (219 points, 18 comments)
Translations: Simplified Chinese, French, Korean, Russian, Turkish
This year, we saw a dazzling application of machine learning. The OpenAI GPT…
Hacker News (64 points, 3 comments), Reddit r/MachineLearning (219 points, 18 comments)
Translations: Simplified Chinese, French, Korean, Russian, Turkish
This year, we saw a dazzling application of machine learning. The OpenAI GPT…
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Continuous Control for High-Dimensional State Spaces: An Interactive Learning Approach
https://arxiv.org/abs/1908.05256
Continuous Control for High-Dimensional State Spaces: An Interactive Learning Approach
https://arxiv.org/abs/1908.05256
arXiv.org
Continuous Control for High-Dimensional State Spaces: An...
Deep Reinforcement Learning (DRL) has become a powerful methodology to solve
complex decision-making problems. However, DRL has several limitations when
used in real-world problems (e.g., robotics...
complex decision-making problems. However, DRL has several limitations when
used in real-world problems (e.g., robotics...
Efficient Segmentation: Learning Downsampling Near Semantic Boundaries
abstract: https://research.fb.com/publications/efficient-segmentation-learning-downsampling-near-semantic-boundaries
paper: https://research.fb.com/wp-content/uploads/2019/08/Efficient-Segmentation-Learning-Downsampling-Near-Semantic-Boundaries.pdf?
abstract: https://research.fb.com/publications/efficient-segmentation-learning-downsampling-near-semantic-boundaries
paper: https://research.fb.com/wp-content/uploads/2019/08/Efficient-Segmentation-Learning-Downsampling-Near-Semantic-Boundaries.pdf?
Facebook Research
Efficient Segmentation: Learning Downsampling Near Semantic Boundaries - Facebook Research
Many automated processes such as auto-piloting rely on a good semantic segmentation as a critical component. To speed up performance, it is common to downsample the input frame. However, this comes at the cost of missed small objects and reduced accuracy…
New State of the Art AI Optimizer: Rectified Adam (RAdam). Improve your AI accuracy instantly versus Adam, and why it works.
https://medium.com/@lessw/new-state-of-the-art-ai-optimizer-rectified-adam-radam-5d854730807b
https://medium.com/@lessw/new-state-of-the-art-ai-optimizer-rectified-adam-radam-5d854730807b
Medium
New State of the Art AI Optimizer: Rectified Adam (RAdam). Improve your AI accuracy instantly versus Adam, and why it works.
A new paper by Liu, Jian, He et al introduces RAdam, or “Rectified Adam”. It’s a new variation of the classic Adam optimizer that provides…
Evaluating and Testing Unintended Memorization in Neural Networks
https://bair.berkeley.edu/blog/2019/08/13/memorization/
https://bair.berkeley.edu/blog/2019/08/13/memorization/
The Berkeley Artificial Intelligence Research Blog
Evaluating and Testing Unintended Memorization in Neural Networks
The BAIR Blog
ai ,machine learning
• 1146 leaderboards
• 1223 tasks
• 1105 datasets
• 14779 papers with code
https://paperswithcode.com/sota
• 1146 leaderboards
• 1223 tasks
• 1105 datasets
• 14779 papers with code
https://paperswithcode.com/sota
huggingface.co
Trending Papers - Hugging Face
Your daily dose of AI research from AK
Transfer learning in natural language processing tutorial
https://docs.google.com/presentation/d/1fIhGikFPnb7G5kr58OvYC3GN4io7MznnM0aAgadvJfc/mobilepresent?slide=id.g58bdd596a1_0_0
https://docs.google.com/presentation/d/1fIhGikFPnb7G5kr58OvYC3GN4io7MznnM0aAgadvJfc/mobilepresent?slide=id.g58bdd596a1_0_0
LVIS: A Dataset for Large Vocabulary Instance Segmentation
Code: https://github.com/lvis-dataset/lvis-api
Article: https://arxiv.org/abs/1908.03195
Progect: https://www.lvisdataset.org/explore
Code: https://github.com/lvis-dataset/lvis-api
Article: https://arxiv.org/abs/1908.03195
Progect: https://www.lvisdataset.org/explore
GitHub
GitHub - lvis-dataset/lvis-api: Python API for LVIS Dataset
Python API for LVIS Dataset. Contribute to lvis-dataset/lvis-api development by creating an account on GitHub.
The Problem With Autonomous Cars That No One’s Talking About
Autonomous cars need to learn how to drive like a local
https://medium.com/fast-company/the-problem-with-autonomous-cars-that-no-ones-talking-about-e34d617c338b
Autonomous cars need to learn how to drive like a local
https://medium.com/fast-company/the-problem-with-autonomous-cars-that-no-ones-talking-about-e34d617c338b
Medium
The Problem With Autonomous Cars That No One’s Talking About
Autonomous cars need to learn how to drive like a local
9 Books on Generative Adversarial Networks (GANs)
https://machinelearningmastery.com/books-on-generative-adversarial-networks-gans/
https://machinelearningmastery.com/books-on-generative-adversarial-networks-gans/
MachineLearningMastery.com
9 Books on Generative Adversarial Networks (GANs) - MachineLearningMastery.com
Generative Adversarial Networks, or GANs for short, were first described in the 2014 paper by Ian Goodfellow, et al. titled
Unsupervised Pre-Training of Image Features on Non-Curated Data
https://research.fb.com/publications/unsupervised-pre-training-of-image-features-on-non-curated-data/
https://research.fb.com/publications/unsupervised-pre-training-of-image-features-on-non-curated-data/
Facebook Research
Unsupervised Pre-Training of Image Features on Non-Curated Data
Pre-training general-purpose visual features with convolutional neural networks without relying on annotations is a challenging and important task. Most recent efforts in unsupervised feature learning have focused on either small or highly curated datasets…
OpenGPT-2: We Replicated GPT-2 Because You Can Too
https://medium.com/@vanya_cohen/opengpt-2-we-replicated-gpt-2-because-you-can-too-45e34e6d36dc
https://medium.com/@vanya_cohen/opengpt-2-we-replicated-gpt-2-because-you-can-too-45e34e6d36dc
Medium
OpenGPT-2: We Replicated GPT-2 Because You Can Too
By Aaron Gokaslan* and Vanya Cohen*
AI Learns To Animate Your Face in VR
Paper:https://research.fb.com/publications/vr-facial-animation-via-multiview-image-translation/
video: https://www.youtube.com/watch?v=hkSfHCtpnHU
Paper:https://research.fb.com/publications/vr-facial-animation-via-multiview-image-translation/
video: https://www.youtube.com/watch?v=hkSfHCtpnHU
Meta Research
VR Facial Animation via Multiview Image Translation - Meta Research
In this work, we present a bidirectional system that can animate avatar heads of both users’ full likeness using consumer-friendly headset mounted cameras (HMC). There are two main challenges in doing this: unaccommodating camera views and the image-to-avatar…
A Gentle Introduction to BigGAN the Big Generative Adversarial Network
https://machinelearningmastery.com/a-gentle-introduction-to-the-biggan/
https://machinelearningmastery.com/a-gentle-introduction-to-the-biggan/
MachineLearningMastery.com
A Gentle Introduction to BigGAN the Big Generative Adversarial Network - MachineLearningMastery.com
Generative Adversarial Networks, or GANs, are perhaps the most effective generative model for image synthesis.
Nevertheless, they are typically restricted to generating small images and the training process remains fragile, dependent upon specific augmentations…
Nevertheless, they are typically restricted to generating small images and the training process remains fragile, dependent upon specific augmentations…
How to Evaluate Generative Adversarial Networks
https://machinelearningmastery.com/how-to-evaluate-generative-adversarial-networks/
https://machinelearningmastery.com/how-to-evaluate-generative-adversarial-networks/