ARIES is a networked software technology that redefines ecosystem service assessment and valuation for decision-making. The ARIES approach to mapping natural capital, natural processes, human beneficiaries, and service flows to society is a powerful new way to visualize, value, and manage the ecosystems on which the human economy and well-being depend.
https://www.youtube.com/watch?v=vsWGkMBpI9Y
https://www.youtube.com/watch?v=vsWGkMBpI9Y
YouTube
ARIES k.Explorer: Introduction and early preview
A quick, early preview of the ARIES (ARtificial Intelligence for Ecosystem Services) Explorer, due for public release in 2019. ARIES, the flagship project of...
On the Morality of Artificial Intelligence
Alexandra Luccioni, Yoshua Bengio : https://arxiv.org/abs/1912.11945
#Society #AIEthics #ArtificialIntelligence
Alexandra Luccioni, Yoshua Bengio : https://arxiv.org/abs/1912.11945
#Society #AIEthics #ArtificialIntelligence
Mila AI Institute is looking for interns to help on applied Machine Learning projects in different AI for Humanity areas (health, environment, humanitarian aid,etc.)
The ideal candidate would have a working knowledge of AI/ML and would be willing to work on projects supervised by mentors at Mila and supported by domain experts.
The goal of these internships is not to publish scientific papers, but to design and deploy ML solutions that can make meaningful impact on problems that are important for society.
Apply here: https://docs.google.com/forms/d/e/1FAIpQLSflOoGyOLhw02UmBCwFTZZMKcuojw33lVQT_m3p0t2RSzeP1A/viewform
The ideal candidate would have a working knowledge of AI/ML and would be willing to work on projects supervised by mentors at Mila and supported by domain experts.
The goal of these internships is not to publish scientific papers, but to design and deploy ML solutions that can make meaningful impact on problems that are important for society.
Apply here: https://docs.google.com/forms/d/e/1FAIpQLSflOoGyOLhw02UmBCwFTZZMKcuojw33lVQT_m3p0t2RSzeP1A/viewform
Different languages use very different approaches to construct meaning
and to understand the many ways languages express meaning
TyDi QA: A Multilingual Question Answering Benchmark https://ai.googleblog.com/2020/02/tydi-qa-multilingual-question-answering.html
and to understand the many ways languages express meaning
TyDi QA: A Multilingual Question Answering Benchmark https://ai.googleblog.com/2020/02/tydi-qa-multilingual-question-answering.html
blog.research.google
TyDi QA: A Multilingual Question Answering Benchmark
Self-Distillation Amplifies Regularization in Hilbert Space
https://arxiv.org/abs/2002.05715v1
https://arxiv.org/abs/2002.05715v1
Yann lecun
Very impressive speed-up of physics simulations using ConvNets emulators obtained through architecture search.
Results on 10 applications in climate modeling, plasma, etc.
https://arxiv.org/abs/2001.08055
Very impressive speed-up of physics simulations using ConvNets emulators obtained through architecture search.
Results on 10 applications in climate modeling, plasma, etc.
https://arxiv.org/abs/2001.08055
How to implement a YOLO (v3) object detector from scratch in PyTorch: Part 1
Blog by Ayoosh Kathuria: https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PatternRecognition
Blog by Ayoosh Kathuria: https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PatternRecognition
Paperspace by DigitalOcean Blog
Tutorial on implementing YOLO v3 from scratch in PyTorch
Tutorial on building YOLO v3 detector from scratch detailing how to create the network architecture from a configuration file, load the weights and designing input/output pipelines.
Capsules with Inverted Dot-Product Attention Routing
New routing algorithm for capsule networks, in which a child capsule is routed to a parent based only on agreement between the parent’s state and the child’s vote.
Code: https://github.com/apple/ml-capsules-inverted-attention-routing
Paper: https://openreview.net/pdf?id=HJe6uANtwH
New routing algorithm for capsule networks, in which a child capsule is routed to a parent based only on agreement between the parent’s state and the child’s vote.
Code: https://github.com/apple/ml-capsules-inverted-attention-routing
Paper: https://openreview.net/pdf?id=HJe6uANtwH
GitHub
GitHub - apple/ml-capsules-inverted-attention-routing
Contribute to apple/ml-capsules-inverted-attention-routing development by creating an account on GitHub.
Recurrent Neural Networks | MIT 6.S191
https://www.youtube.com/watch?v=SEnXr6v2ifU
join
https://t.me/ArtificialIntelligenceArticles
https://www.youtube.com/watch?v=SEnXr6v2ifU
join
https://t.me/ArtificialIntelligenceArticles
YouTube
MIT 6.S191 (2020): Recurrent Neural Networks
MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Soleimany
January 2020
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 - Introduction
2:39 - Sequence modeling
9:57…
Recurrent Neural Networks
Lecturer: Ava Soleimany
January 2020
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 - Introduction
2:39 - Sequence modeling
9:57…
Lecture by Vladimir Vapnik in January 2020, part of the MIT Deep Learning Lecture Series.
https://www.youtube.com/watch?v=Ow25mjFjSmg
https://www.youtube.com/watch?v=Ow25mjFjSmg
YouTube
Complete Statistical Theory of Learning (Vladimir Vapnik) | MIT Deep Learning Series
Lecture by Vladimir Vapnik in January 2020, part of the MIT Deep Learning Lecture Series.
Slides: http://bit.ly/2ORVofC
Associated podcast conversation: https://www.youtube.com/watch?v=bQa7hpUpMzM
Series website: https://deeplearning.mit.edu
Playlist: ht…
Slides: http://bit.ly/2ORVofC
Associated podcast conversation: https://www.youtube.com/watch?v=bQa7hpUpMzM
Series website: https://deeplearning.mit.edu
Playlist: ht…
Data used to train #AI can contain implicit racial, gender, or ideological biases. How can we champion processes to remove bias from AI?
https://www.anaconda.com/machine-learning-bias-fairness/
https://www.anaconda.com/machine-learning-bias-fairness/
Anaconda
Anaconda | What Can AI Teach Us about Bias and Fairness?
By: Peter Wang & Natalie Parra-Novosad As researchers, journalists, and many others have discovered, machine learning algorithms can deliver biased results. One notorious example is ProPublica’s discovery of bias in a software called COMPAS used by the U.S.…
HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models. http://arxiv.org/abs/2002.05271
Reinforcement learning is one powerful paradigm for doing so, and it is relevant to an enormous range of tasks, including robotics, game playing, consumer modeling, and healthcare.
https://www.youtube.com/watch?v=FgzM3zpZ55o
https://www.youtube.com/watch?v=FgzM3zpZ55o
YouTube
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction - Emma Brunskill
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai
Professor Emma Brunskill, Stanford University
https://stanford.io/3eJW8yT
Professor Emma Brunskill
Assistant Professor, Computer…
Professor Emma Brunskill, Stanford University
https://stanford.io/3eJW8yT
Professor Emma Brunskill
Assistant Professor, Computer…
2.7 million have enrolled in Andrew Ng’s Machine Learning course
- Geoffrey Hinton has been cited 340k times
- TensorFlow has been used in 60k OSS projects
Hypothesis: in 5 years, when these millions of students have gained hands-on experience, we'll have AI skills overflow.
- Geoffrey Hinton has been cited 340k times
- TensorFlow has been used in 60k OSS projects
Hypothesis: in 5 years, when these millions of students have gained hands-on experience, we'll have AI skills overflow.