Christie’s has sold its first piece of AI art, a canvas named the Portrait of Edmond Belamy, for $432,500

Investigation by Verge: https://www.theverge.com/2018/10/23/18013190/ai-art-portrait-auction-christies-belamy-obvious-robbie-barrat-gans

GitHub: https://github.com/robbiebarrat/art-DCGAN

Dynamic Meta-Embeddings for Improved Sentence Representations

While one of the first steps in many NLP systems is selecting what pre-trained word embeddings to use, we argue that such a step is better left for neural networks to figure out by themselves. To that end, we introduce dynamic meta-embeddings, a simple yet effective method for the supervised learning of embedding ensembles, which leads to state-of-the-art performance within the same model class on a variety of tasks. We subsequently show how the technique can be used to shed new light on the usage of word embeddings in NLP systems.

Paper: https://research.fb.com/wp-content/uploads/2018/10/Dynamic-Meta-Embeddings-for-Improved-Sentence-Representations.pdf
Link: https://research.fb.com/publications/dynamic-meta-embeddings-for-improved-sentence-representations/

P.S. Note the date of the publication

#embeddings #NLP #facebook

Facebook is open-sourcing QNNPACK, a kernel library that is optimized for mobile AI.

Site: https://code.fb.com/ml-applications/qnnpack/
Github: https://github.com/pytorch/QNNPACK

#dl #mobile #facebook

Really scary

An agent which learned to play Mario without rewards. Instead, it was incentivized to avoid "boredom" (that is, getting into states where it can predict what will happen next). Discovered warp levels, how to defeat bosses, etc.

Link: https://blog.openai.com/reinforcement-learning-with-prediction-based-rewards/

#RL #openai

Facebook open sourced Horizon, an end-to-end applied reinforcement learning platform built on #PyTorch 1.0. Horizon uses RL to optimize systems in large-scale production environments and we're excited to make it accessible to anyone using #RL at scale.

https://code.fb.com/ml-applications/horizon/

#facebook

XNLI dataset published by Facebook AI & NYU.

New dataset have been released recently to promote cross-lingual approaches to natural language understanding (#NLU).

This dataset builds on the commonly used Multi-Genre Natural Language Inference (MultiNLI) corpus, adding 14 languages to that English-only data set, including two low-resource languages: Swahili and Urdu.

Link: https://code.fb.com/ai-research/xlni/

#NLP #facebook

#DeepMind ’s library for deep learning on graphs.


ArXiV: https://arxiv.org/abs/1806.01261
Github: https://github.com/deepmind/graph_nets

Reversible RNNs

Paper about how to reduce memory costs of GRU and LSTM networks by 10-15x without loss in performance. Also 5-10x for attention-based architectures. New paper with Matt MacKay, Paul Vicol, and Jimmy Ba, to appear at NIPS.

Link: https://arxiv.org/abs/1810.10999

#dl #RNN #NIPS2018

Faster R-CNN and Mask R-CNN in #PyTorch 1.0

Another release from #Facebook.

Mask R-CNN Benchmark: a fast and modular implementation for Faster R-CNN and Mask R-CNN written entirely in @PyTorch 1.0. It brings up to 30% speedup compared to mmdetection during training.

Webcam demo and ipynb file are available.

Github: https://github.com/facebookresearch/maskrcnn-benchmark

#CNN #CV #segmentation #detection

Mask R-CNN Benchmark Demo

A set of best where-to-start-with-python resources.

This is the collection of beginners resources from a tweet by fast.ai cofounder, covering any resource which helped people to learn python from scratch.

https://telegra.ph/A-collection-of-where-to-start-python-resources-11-05

#beginner #novice #CS #python #tutorial

Making floating point math highly efficient for AI hardware.

Fresh FB article on accelerating ML.

https://code.fb.com/ai-research/floating-point-math/

#facebook

Analyzing Experiment Outcomes: Beyond Average Treatment Effects

Cool piece from Uber's engineering department about why you can't just use the average customer experience to see if product changes are worth it. You have to consider the DISTRIBUTIONAL changes of the customer experience.

Link: https://eng.uber.com/analyzing-experiment-outcomes/

#statistics #uber #abtest

​​TL-GAN: transparent latent-space GAN

GANs to generate photo-realistic faces with some control over characteristics.


Demo: https://www.kaggle.com/summitkwan/tl-gan-demo
Medium Post: https://blog.insightdatascience.com/generating-custom-photo-realistic-faces-using-ai-d170b1b59255
Github: https://github.com/SummitKwan/transparent_latent_gan#1-instructions-on-the-online-demo

#GAN #cv

Amazon’s SageMaker Object2Vec, a highly customizable algorithm that can learn embeddings of various types high-dimensional objects.

Link: https://aws.amazon.com/ru/blogs/machine-learning/introduction-to-amazon-sagemaker-object2vec/

#Object2Vec #Amazon #Embeddings

Prototypical Clustering Networks for Dermatological Disease Diagnosis

Paper will be presented at the ML4D workshop at #NIPS2018

Link: https://arxiv.org/abs/1811.03066

#nn #bio #medical

Monitor Your PyTorch Models With Five Extra Lines of Code



Ever felt like manually managing your Visdom / TensorBoard server and logs is a pain across experiments, projects and teams?
Weights & Biases provides a simple cloud-based experiment logging and plotting system, with easy integration for PyTorch models.

Link: https://www.wandb.com/blog/monitor-your-pytorch-models-with-five-extra-lines-of-code

#pytorch

New paper on Lipschitz neural net architectures. Uses sorting as an activation function, with matrix norm constrained weights. Universal Lipschitz function approx. Enforce adversarial robustness (margin) using hinge loss.

Link: https://arxiv.org/abs/1811.05381

#nn #lipschitz

​​Neural network 3D visualization framework. Very nice in-depth visualizations.

Now you can actually see how the layers look.

Github: https://github.com/tensorspace-team/tensorspace
LiveDemo (!): https://tensorspace.org/html/playground/vgg16.html

#visualization #nn