Modern Deep Learning Techniques Applied to Natural Language Processing
https://nlpoverview.com/index.html @ArtificialIntelligenceArticles
https://nlpoverview.com/index.html @ArtificialIntelligenceArticles
Mark Zuckerberg & Yuval Noah Harari in Conversation
https://www.youtube.com/watch?v=Boj9eD0Wug8&feature=youtu.be&fbclid=IwAR1YBK-WRhSDmdiY5HRpkGDPI4ytBaIn6mSPRn1RGslEJ9eXxWF9avxVFeg
https://www.youtube.com/watch?v=Boj9eD0Wug8&feature=youtu.be&fbclid=IwAR1YBK-WRhSDmdiY5HRpkGDPI4ytBaIn6mSPRn1RGslEJ9eXxWF9avxVFeg
YouTube
Mark Zuckerberg & Yuval Noah Harari in Conversation
Mark Zuckerberg hosts Yuval Noah Harari for a frank conversation about some big challenges -- as part of the Facebook CEO's 2019 series of public discussions...
UN Handbook on Privacy-Preserving Computation Techniques"
By the Privacy Preserving Techniques Task Team (PPTTT): https://docs.google.com/document/d/1GYu6UJI81jR8LgooXVDsYk1s6FlM-SbOvo3oLHglFhY/edit#
#computation #machinelearning #technology @ArtificialIntelligenceArticles
By the Privacy Preserving Techniques Task Team (PPTTT): https://docs.google.com/document/d/1GYu6UJI81jR8LgooXVDsYk1s6FlM-SbOvo3oLHglFhY/edit#
#computation #machinelearning #technology @ArtificialIntelligenceArticles
FOR.ai Reinforcement Learning Codebase
Generic reinforcement learning codebase in TensorFlow: https://github.com/for-ai/rl @ArtificialIntelligenceArticles
#reinforcementlearning #tensorflow #technology
Generic reinforcement learning codebase in TensorFlow: https://github.com/for-ai/rl @ArtificialIntelligenceArticles
#reinforcementlearning #tensorflow #technology
GANs and Divergence Minimization
By Colin Raffel:
https://colinraffel.com/blog/gans-and-divergence-minimization.html
@ArtificialIntelligenceArticles
#ArtificialIntelligence #DeepLearning #GenerativeAdversarialNetworks
By Colin Raffel:
https://colinraffel.com/blog/gans-and-divergence-minimization.html
@ArtificialIntelligenceArticles
#ArtificialIntelligence #DeepLearning #GenerativeAdversarialNetworks
A Selective Overview of Deep Learning https://www.princeton.edu/~congm/Publication/DL_survey/DL_survey.pdf
#weekend_read
Paper-Title: Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments
Link to the paper: https://arxiv.org/pdf/1904.11483.pdf
#Stanford #HRI
TL;DR: [1] They presented a decision-making framework for autonomously navigating urban intersections.
[2] Secondly, they introduced a learned belief updater that uses an ensemble of RNNs to estimate the location of vehicles behind obstacles and is robust to perception errors.
[3] Further they improved upon pure reinforcement learning methods by using a model checker to enforce safety guarantees.
[4] Finally, through a scene decomposition method they demonstrated how to efficiently scale the algorithm to scenarios with multiple cars and pedestrians.
Paper-Title: Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments
Link to the paper: https://arxiv.org/pdf/1904.11483.pdf
#Stanford #HRI
TL;DR: [1] They presented a decision-making framework for autonomously navigating urban intersections.
[2] Secondly, they introduced a learned belief updater that uses an ensemble of RNNs to estimate the location of vehicles behind obstacles and is robust to perception errors.
[3] Further they improved upon pure reinforcement learning methods by using a model checker to enforce safety guarantees.
[4] Finally, through a scene decomposition method they demonstrated how to efficiently scale the algorithm to scenarios with multiple cars and pedestrians.
Machine Learning From Scratch
Bare bones #Python implementations of #MachineLearning models and algorithms with a focus on accessibility.
By Erik Linder-Noren: https://github.com/eriklindernoren/ML-From-Scratch...
See More
Bare bones #Python implementations of #MachineLearning models and algorithms with a focus on accessibility.
By Erik Linder-Noren: https://github.com/eriklindernoren/ML-From-Scratch...
See More
GitHub
GitHub - eriklindernoren/ML-From-Scratch: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models…
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear...
Deep Learning: AlphaGo Zero Explained In One Picture
By L.V.: https://api.ning.com/files/G3detyndwpXvT8Py3CFA1rtuPS549-KcvNCPjfyaORlWtrBVjnT7MSsnV5zQmlOYZg8n9cIqQqf2u4GMq0VHnN1AE-nlYFnx/porc.png
By L.V.: https://api.ning.com/files/G3detyndwpXvT8Py3CFA1rtuPS549-KcvNCPjfyaORlWtrBVjnT7MSsnV5zQmlOYZg8n9cIqQqf2u4GMq0VHnN1AE-nlYFnx/porc.png
A Gentle Introduction to 1×1 Convolutions to Reduce the Complexity of Convolutional Neural Networks
https://machinelearningmastery.com/introduction-to-1x1-convolutions-to-reduce-the-complexity-of-convolutional-neural-networks/
https://machinelearningmastery.com/introduction-to-1x1-convolutions-to-reduce-the-complexity-of-convolutional-neural-networks/
MachineLearningMastery.com
A Gentle Introduction to 1×1 Convolutions to Manage Model Complexity - MachineLearningMastery.com
Pooling can be used to down sample the content of feature maps, reducing their width and height whilst maintaining their salient features. A problem with deep convolutional neural networks is that the number of feature maps often increases with the depth…
Ironically, Yuval Noah Harari's equation of B X C X D= HH, where B=biological knowledge, C=computer power, D=data, HH=human hacking in days after the 1st report of direct #brain activity to speech.
Fei Fei Li to YNH : "Okay, can I be specific? First of all the birth of AI is AI scientists talking to biologists, specifically neuroscientists, right. The birth of AI is very much inspired by what the brain does. Fast forward to 60 years later, today's AI is making great improvements in healthcare. There's a lot of data from our physiology and pathology being collected and using machine learning to help us. But I feel like you're talking about something else."
https://www.wired.com/story/will-artificial-intelligence-enhance-hack-humanity/
Fei Fei Li to YNH : "Okay, can I be specific? First of all the birth of AI is AI scientists talking to biologists, specifically neuroscientists, right. The birth of AI is very much inspired by what the brain does. Fast forward to 60 years later, today's AI is making great improvements in healthcare. There's a lot of data from our physiology and pathology being collected and using machine learning to help us. But I feel like you're talking about something else."
https://www.wired.com/story/will-artificial-intelligence-enhance-hack-humanity/
WIRED
Will Artificial Intelligence Enhance or Hack Humanity?
Historian Yuval Noah Harari and computer scientist Fei-Fei Li discuss the promise and perils of the transformative technology with WIRED editor in chief Nicholas Thompson.
Mathematics for Artificial Intelligence
https://rubikscode.net/2019/04/29/mathematics-for-artificial-intelligence-linear-algebra/
https://rubikscode.net/2019/04/29/mathematics-for-artificial-intelligence-linear-algebra/
Meta-Sim: Learning to Generate Synthetic Datasets
Kar et al.: https://arxiv.org/abs/1904.11621 @ArtificialIntelligenceArticles
#ComputerVision #PatternRecognition #ArtificialIntelligence
Kar et al.: https://arxiv.org/abs/1904.11621 @ArtificialIntelligenceArticles
#ComputerVision #PatternRecognition #ArtificialIntelligence
Conversation between Lex Fridman and Oriol Vinyals about DeepMind AlphaStar, StarCraft, and Language
Artificial Intelligence podcast: https://youtu.be/Kedt2or9xlo
#AlphaStar #ArtificialIntelligence #DeepLearning #ReinforcementLearning
Artificial Intelligence podcast: https://youtu.be/Kedt2or9xlo
#AlphaStar #ArtificialIntelligence #DeepLearning #ReinforcementLearning
YouTube
Oriol Vinyals: DeepMind AlphaStar, StarCraft, and Language | Lex Fridman Podcast #20
Invertible Residual Networks
Behrmann et al.: https://arxiv.org/abs/1811.00995
#MachineLearning #ArtificialIntelligence #ComputerVision
Behrmann et al.: https://arxiv.org/abs/1811.00995
#MachineLearning #ArtificialIntelligence #ComputerVision
A first in medical robotics: Autonomous navigation inside the body
https://techxplore.com/news/2019-04-medical-robotics-autonomous-body.html?fbclid=IwAR3ragCWgmUkIpQffYdtebY6mnRO7U6d__4uK_nsZKuaoTtv7JHBY0ZNUNo
https://techxplore.com/news/2019-04-medical-robotics-autonomous-body.html?fbclid=IwAR3ragCWgmUkIpQffYdtebY6mnRO7U6d__4uK_nsZKuaoTtv7JHBY0ZNUNo
Techxplore
A first in medical robotics: Autonomous navigation inside the body
Bioengineers at Boston Children's Hospital report the first demonstration of a robot able to navigate autonomously inside the body. In an animal model of cardiac valve repair, the team programmed a robotic ...
Taming Recurrent Neural Networks for Better Summarization
https://www.abigailsee.com/2017/04/16/taming-rnns-for-better-summarization.html
https://www.abigailsee.com/2017/04/16/taming-rnns-for-better-summarization.html
Abigailsee
Taming Recurrent Neural Networks for Better Summarization
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Unsupervised Data Augmentation
Xie et al.: https://arxiv.org/abs/1904.12848
#DeepLearning #MachineLearning #ArtificialIntelligence #UnsupervisedLearning
Xie et al.: https://arxiv.org/abs/1904.12848
#DeepLearning #MachineLearning #ArtificialIntelligence #UnsupervisedLearning
arXiv.org
Unsupervised Data Augmentation for Consistency Training
Semi-supervised learning lately has shown much promise in improving deep learning models when labeled data is scarce. Common among recent approaches is the use of consistency training on a large...