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Fast.ai; Google IO; Semantic segmentation, object detection, network graph overviews; algorithms vs. compute; AI perspectives; MT; semantic similarity; Goodfellow, Schmidhuber, & Kaggle #1 profiles; Maths for ML; synthetic data; uncertainty for dialogue

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Hi all! Are you still stressed about your NIPS submission, anxious about the EMNLP deadline or just a
 
May 21 · Issue #23 · View online
NLP News
Hi all!
Are you still stressed about your NIPS submission, anxious about the EMNLP deadline or just annoyed because—let’s face it—it’s Monday again? Grab a coffee ☕️ and relax with this fortnight’s edition!
This time, we have: overviews of semantic segmentation, object detection models, and network graph methods; two articles on the showdown between algorithms vs. compute; essays with different perspectives on AI, from fear and caution to cooperation; articles on advances in machine translation and semantic similarity; profiles of Ian Goodfellow, Jürgen Schmidhuber, and the new #1 Kaggler; a new Maths for ML book; industry news including using synthetic training data and uncertainty for dialogue; and research papers from ACL 2018.

Steve Maine
TIL that changing random stuff until your program works is "hacky" and "bad coding practice" but if you do it fast enough it's "#MachineLearning" and pays 4x your current salary
12:40 AM - 11 May 2018
What's hot 🔥
Tutorials and overviews
Going beyond the bounding box with semantic segmentation
Understanding Deep Learning for Object Detection
How do we capture structure in relational data?
Algorithms vs. compute
An AI speed test shows clever coders can still beat tech giants like Google and Intel
AI and Compute
Perspectives on AI
How Frightened Should We Be of A.I.?
How To Become A Centaur
To Build Truly Intelligent Machines, Teach Them Cause and Effect
How the Enlightenment Ends
Translation
Simultaneous Interpreters May Soon Get Real-Time Help Just When They Need It
Semi-Supervised Universal Neural Machine Translation
Semantic similarity
Advances in Semantic Textual Similarity
The Current Best of Universal Word and Sentence Embeddings
People in ML
How I Fail - Ian Goodfellow
Google, Amazon, and Facebook Owe Jürgen Schmidhuber a Fortune
Profiling Top Kagglers: Bestfitting, Currently #1 in the World
Resources
Mathematics for Machine Learning book
More articles and blog posts
Alexa and Siri Can Hear This Hidden Command. You Can’t.
Artificial Intelligence Opens the Vatican Secret Archives
DeepMind has trained an AI to understand how your brain thinks
Industry news
Volta Tensor Core GPU Achieves New AI Performance Milestones
Alexa developers get 8 free voices to use in skills, courtesy of Amazon Polly
How uncertainty could help a machine hold a more eloquent conversation
AI is learning how to trump purveyors of 'fake news'
Deep learning with synthetic data will democratize the tech industry
Facebook Adds A.I. Labs in Seattle and Pittsburgh, Pressuring Local Universities
Paper picks
A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings (ACL 2018)
Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples (ACL 2018)
Paper Abstract Writing through Editing Mechanism (ACL 2018)
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