​​Google AI research on learning better simulation methods for partial differential equations

New research shows how machine learning can improve high-performance computing for solving partial differential equations, with potential applications that range from modeling #climatechange to simulating fusion reactions. Learn all about it here

Link: https://ai.googleblog.com/2019/07/learning-better-simulation-methods-for.html

#PDE #DE #GoogleAI

On the concept of 'intellectual debt'

There is technical debt — when you know you should rewrite some stuff, or implement some features, but they don't seem critical at the moment. So article introduces a concept of 'intellectual debt', which resies with more broad and common use of #MachineLearning and #DeepLearning (specially, the latter). What happens when AI gives us seemingly correct answers that we wouldn't have thought of ourselves, without any theory to explain them?

Link: https://www.newyorker.com/tech/annals-of-technology/the-hidden-costs-of-automated-thinking

#Meta #common #lyrics

​​New dataset with adversarial examples

Natural Adversarial Examples are real-world and unmodified examples which cause classifiers to be consistently confused. The new dataset has 7,500 images, which we personally labeled over several months.

ArXiV: https://arxiv.org/abs/1907.07174
Dataset and code: https://github.com/hendrycks/natural-adv-examples

#Dataset #Adversarial

​​Release of 27 pretrained models for NLP / NLU for PyTorch

Hugging Face open sources a new library that contains up to 27 pretrained models to conduct state-of-the-art NLP/NLU tasks.

Link: https://medium.com/dair-ai/pytorch-transformers-for-state-of-the-art-nlp-3348911ffa5b

#SOTA #NLP #NLU #PyTorch #opensource

ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.

Filter autoselect in VSCO by Google

#VSCO used #TensorFlow Lite to develop the 'For This Photo' feature, which uses on-device ML to suggest photo filter presets from a curated list.

YouTube: https://www.youtube.com/watch?v=fHbjfeitIvE
Link: https://medium.com/tensorflow/suggesting-presets-for-images-building-for-this-photo-at-vsco-9b94041c4ba4

#mobile #device #cv #dl

Baidu's recent paper: Hubless Nearest Neighbor Search

Hubless Nearest Neighbor Search, a new method for Bilingual Lexicon Induction, improves retrieval accuracy significantly. Empirical results show HNN outperforms NN, ISF and other state-of-the-art.

Github: https://github.com/baidu-research/HNN
Paper: https://github.com/baidu-research/HNN/blob/master/doc/HNN.pdf

#ACL2019 #NLP #NLU

​​Plato Research Dialogue System: A Flexible Conversational AI Platform

The Plato Research Dialogue System is a platform #Uber developed to enable experts and non-experts alike to quickly build, train, and deploy conversational AI agents.

Link: https://eng.uber.com/plato-research-dialogue-system/

#ConversationalAI #converstaion #NLP #NLU

​​Model for tweaking graph visualization layout parameters

New #MachineLearning model builds a WYSIWYG interface to intuitively produce a layout you want!

Demo: http://kwonoh.net/dgl
Paper: http://arxiv.org/abs/1904.12225

#Visualization #ML

​​GSCNN: video segmetation architecture

Semantic segmentation GSCNN significantly outperforms DeepLabV3+ on Cityscapes benchmark.

Paper: https://arxiv.org/abs/1907.05740
Github (Project): https://github.com/nv-tlabs/GSCNN

#DL #CV #NVidiaAI #Nvidia #autonomous #selfdriving #car #RL #segmentation

​​Large Scale Adversarial Representation Learning

DeepMind shows that GANs can be harnessed for unsupervised representation learning, with state-of-the-art results on ImageNet. Reconstructions, as shown in paper, tend to emphasise high-level semantics over pixel-level details.

Link: https://arxiv.org/abs/1907.02544

#DeepMind #GAN #CV #DL #SOTA

Overview of 10 Stanford's Data Science courses

A survivor’s guide to Artificial Intelligence courses at Stanford

Link: https://huyenchip.com/2018/03/30/guide-to-Artificial-Intelligence-Stanford.html

#Staford #MOOC #course #free #rating #learning

Top 8 trends from ICLR 2019

Overview of trends on #ICLR2019:
1. Inclusivity
2. Unsupervised representation learning & transfer learning
3. Retro ML
4. RNN is losing its luster with researchers
5. GANs are still going on strong
6. The lack of biologically inspired deep learning
7. Reinforcement learning is still the most popular topic by submissions
8. Most accepted papers will be quickly forgotten

Link: https://huyenchip.com/2019/05/12/top-8-trends-from-iclr-2019.html

#ICLR #overview

​​The new ResNet PoseNet model is much more accurate than the MobileNet one (the trade off being size & speed). The model is quantized & 25MB.
Pose estimation model, capable of running on devices

This model is really great for art installations or running on desktops.

Demo (requires camera, will work on desktop): https://storage.googleapis.com/tfjs-models/demos/posenet/camera.html?linkId=69346544
Github: https://github.com/tensorflow/tfjs-models/tree/master/posenet

#tensorflow #tensorflowjs #js #pose #poseestimation #posenet #ResNet #device #ondevice

Estimating the success of re-identifications in incomplete datasets using generative models

99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes, suggesting that even heavily sampled anonymized datasets are unlikely to satisfy the modern standards for anonymization set forth by GDPR.

This is a big concern about privacy and a problem for Data Engineering, especially for those working with anonymized personal information. Paper provides a way to re-identify person from anonymized dataset, this can be useful for people who work for government or security companies

https://www.reddit.com/r/science/comments/chko43/9998_of_americans_would_be_correctly_reidentified/

#privacy #gdpr #federatedlearning #ml

🔥Neural Point-Based Graphics

Breakthrough work on generating realistic 3D scenes in AR.

Demo: https://www.youtube.com/watch?v=7s3BYGok7wU
Project page: https://dmitryulyanov.github.io/neural_point_based_graphics
ArXiV: https://arxiv.org/pdf/1906.08240.pdf

#CV #AR #DL #SamsungAI

​​Baidu’s Optimized ERNIE Achieves State-of-the-Art Results in Natural Language Processing Tasks

#Baide developed ERNIE 2.0, a continual pre-training framework for language understanding. The model built on this framework has outperformed #BERT and #XLNet on 16 tasks in Chinese and English.

Link: http://research.baidu.com/Blog/index-view?id=121

#NLP #NLU

​​🔥Interactive demo of GAN turning doodles into beautiful pictures

NVidia released #GauGAN for anyone to use. Trained on 1M images, the #GAN tool automatically turns doodles into photorealistic landscapes.

Project page: https://www.nvidia.com/en-us/research/ai-playground/
Interactive demo: http://nvidia-research-mingyuliu.com/gaugan

#Nvidia #CV #DL

Great article on text preprocessing, covering cleaning, #tokenization, #lemmatization and other aspects

Link: https://medium.com/@datamonsters/text-preprocessing-in-python-steps-tools-and-examples-bf025f872908

#NLP #NLU #datacleaning

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