PhD position now open.

Are you interested in evolution? Can you work with global data sets? Do you want to develop machine learning techniques? Are you excited by the global underground?

Evolutionary Biogeography of Microbial Networks

https://workingat.vu.nl/ad/evolutionary-biogeography-of-microbial-networks/v9ydfv

Google releases millions of free datasets. (from January 23rd, 2020)
https://blog.google/products/search/discovering-millions-datasets-web/
https://news.1rj.ru/str/ArtificialIntelligenceArticles

Sebastian Raschka

STAT 453 -- Introduction to Deep Learning and Generative Models (Spring 2020)

http://pages.stat.wisc.edu/~sraschka/teaching/stat453-ss2020/

https://github.com/rasbt/stat453-deep-learning-ss20/blob/master/L06-pytorch/code/adaline-with-autograd.ipynb

Fast and Easy Infinitely Wide Networks with Neural Tangents
Blog by Samuel S. Schoenholz and Roman Novak: https://ai.googleblog.com/2020/03/fast-and-easy-infinitely-wide-networks.html
#ArtificialIntelligence #MachineLearning #DeepLearning

MIT’s deep learning found an antibiotic for a germ nothing else could kill | ZDNet
https://www.zdnet.com/article/mits-deep-learning-found-an-antibiotic-for-a-germ-nothing-else-could-kill/

A great opinion piece by Robert M. Sapolsky.

https://edition.cnn.com/2020/03/13/opinions/coronavirus-neuroscience-brain-decisions-sapolsky/index.html

Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China
https://link.springer.com/article/10.1007/s00134-020-05991-x

TensorFlowJS for natural language processing
EXPLORING HELPFUL USES FOR BERT IN YOUR BROWSER WITH TENSORFLOW.JS
Blog by Philip Bayer, Ping Yu and Jason Mayes: https://blog.tensorflow.org/2020/03/exploring-helpful-uses-for-bert-in-your-browser-tensorflow-js.html

Softmax Splatting for Video Frame Interpolation
Paper: https://arxiv.org/pdf/2003.05534.pdf
Github: https://github.com/sniklaus/softmax-splatting

Machine learning in physics: The pitfalls of poisoned training sets
Fang et al.: https://arxiv.org/abs/2003.05087
https://news.1rj.ru/str/ArtificialIntelligenceArticles
#MachineLearning #NeuralNetworks #Physics

A database with over 24,000 research papers related to the coronavirus pandemic is now live. The database not only helps scientists consolidate existing research but also makes the body of literature easier to mine for insights with artificial intelligence.
https://www.technologyreview.com/s/615367/coronavirus-24000-research-papers-available-open-data/

CORD-19: A Kaggle challenge for the Natural Language Processing community.

Dataset of 29,000 scholarly article (including 13,000 with full text), about COVID-19 and related coronaviruses.
Help answers questions like "what do we know about COVID-19 risk factors?" by mining the literature.
@ArtificialIntelligenceArticles
Created by the Allen Institute for AI in partnership with the Chan-Zuckerberg Initiative, Georgetown University, Microsoft Research, and the National Library of Medicine.
https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge
https://news.1rj.ru/str/ArtificialIntelligenceArticles

White House urges researchers to use AI to analyze 29,000 coronavirus papers
Paresh Dave, Reuters: https://www.reuters.com/article/us-health-coronavirus-tech-research-idUSKBN2133E6
#ArtificialIntelligence #CoronaVirus #CoronaOutbreak #DeepLearning #MontrealAI

EfficientDet: Scalable and Efficient Object Detection
New scaling techniques:
Backbone: we employ the more advanced EfficientNets as our backbone networks.
BiFPN: we propose a new bi-directional feature network, named BiFPN, to enable easy and fast feature fusion. In addition to the bi-directional topology, we also propose a new fast normalized fusion that enables better fusion with negligible latency cost.
Scaling: we propose to use a single compound scaling factor to govern the network depth, width, and resolution for all backbone, feature network, and prediction networks.
Paper: https://arxiv.org/abs/1911.09070
Code: https://github.com/google/automl/tree/master/efficientdet

Application of Machine Learning in monitoring and fighting COVID-19
Big Data Helps Taiwan Fight Coronavirus: https://spectrum.ieee.org/the-human-os/biomedical/devices/big-data-helps-taiwan-fight-coronavirus
Satellites and AI Monitor Chinese Economy’s Reaction to Coronavirus: https://spectrum.ieee.org/view-from-the-valley/artificial-intelligence/machine-learning/satellites-and-ai-monitor-chinese-economys-reaction-to-coronavirus
Could Supercomputers and Rapid Treatment Trials Slow Down Coronavirus? https://spectrum.ieee.org/the-human-os/biomedical/devices/could-supercomputers-and-rapid-treatment-trials-slow-down-coronavirus
Is Coronavirus Speeding the Adoption of Driverless Technology? https://spectrum.ieee.org/cars-that-think/transportation/self-driving/will-coronavirus-speed-adoption-of-driverless-technology

NSERC Presents 2 Minutes with Geoffrey Hinton
https://www.youtube.com/watch?v=Z_JFUuSet4U

Deep Reinforcement Learning Course
https://simoninithomas.github.io/Deep_reinforcement_learning_Course/

This Artificial Intelligence solution developed by Coimbatore- based AES Technologies needs no swab test, kits or laboratories that take days to issue the results. A CT scan is all that it takes to determine whether you and positive or negative and this, in LESS THAN A MINUTE!


https://www.youtube.com/watch?v=fqyFWQNqWpI