If you enjoy the newsletter, please consider sharing it on Twitter, Facebook, etc! Really appreciate
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December 11 · Issue #71 · View online
The Wild Week in AI is a weekly AI & Deep Learning newsletter curated by @.
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If you enjoy the newsletter, please consider sharing it on Twitter, Facebook, etc! Really appreciate the support :)
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Butterfly has built a new hand-held Ultrasound device that will revolutionize health care: the Butterfly iQ. This Ultrasound device fits in your pocket, connects to your smart-phone and stores medical data securely in the cloud. Butterfly’s machine learning team works on building intelligence into the device to help clinicians make life-saving decisions. Butterfly is looking for researchers interested in continuing to develop and publish new machine learning algorithms while also having a direct and immense, real-world impact. Find out more at butterflynetwork.com.
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AlphaZero: Mastering Chess and Shogi by Self-Play
DeepMind has published a new paper on AlphaZero, a generalization of AlphaGo, showing that it convincingly defeats world-champion programs in both Chess and Shogi within only 24 hours of training (on a lot of TPUs). See these Reddit and HN threads for interesting discussions.
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Nvidia announces new $2,999 Titan V GPU
According to Nvidia, the Titan V is “the most powerful PC GPU ever created”. Nvidia claims up to 110 teraflops of performance, with 12GB of HBM2 memory, 5120 CUDA cores, and 640 “tensor cores” that are said to offer up to 9 times the deep-learning performance of its predecessor. More importantly, its color is gold!
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Facebook launches AI Research Residency Program
The Facebook AI Research (FAIR) Residency Program is a one-year research training program with Facebook’s AI Research group, designed to give you hands-on experience of machine learning research. The application deadline is January 26, 2018, and a Bachelor’s degree is required.
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Elon Musk says Tesla is working on custom AI chips
Musk revealed the effort at a Tesla party that took place at the intelligence conference NIPS. According to Musk, “I wanted to make it clear that Tesla is serious about AI, both on the software and hardware fronts. We are developing custom AI hardware chips”.
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NIPS Keynotes/Streams on Facebook
The NIPS conference, which took place in Long Beach this year, is the perhaps biggest gathering of AI researchers. This year’s tickets were sold out in record time, and attendance numbers skyrocketed. We expect videos from the conference to be posted online in the coming videos, with some of livestreamed keynotes already available on Facebook.
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Using Artificial Intelligence to Augment Human Intelligence
By creating user interfaces which let us work with the representations inside machine learning models, we can give people new tools for reasoning.
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Ali Rahimi's talk at NIPS (Test-of-time award presentation)
Ali Rahimi’s talk at NIPS struck a nerve with many AI researchers. He called for more rigor in Machine Learning research, comparing many of today’s popular Deep Learning techniques to “Alchemy”. Yann LeCun promptly responded. Also see this Reddit discussion.
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A reply to Francois Chollet on intelligence explosion
This post is a reply to Francois Chollet, the inventor of the Keras wrapper for the Tensorflow and Theano deep learning systems, on his essay “The impossibility of intelligence explosion.” If you liked Francois’ essay, this one is worth a read as well.
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Neural Networks in JavaScript with deeplearn.js
An accessible tutorial on how to implement a neural network in JavaScript with deeplearn.js. The goal is to find matches of font and background color for improved web accessibility.
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PyTorch 0.3.0 Release
The release includes performance improvements, new layers, and the ability to ship models to other frameworks (via ONNX), support for CUDA9 and CuDNNv7.
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Unity ML-Agents v0.2 Release
The new release adds new features to both the Unity SDK and Python API, adds new example environments, and improves the default Reinforcement Learning algorithm (PPO), addition to many bug-fixes.
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Apple's Turi Create Framework
Turi Create simplifies the development of custom machine learning models. You don’t have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.
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[1712.01815] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
In this paper, the authors present single AlphaZero algorithm that can achieve, tabula rasa, superhuman performance in many challenging domains. Starting from random play, and given no domain knowledge except the game rules, AlphaZero achieved within 24 hours a superhuman level of play in the games of chess, and shogi (Japanese chess) as well as Go, and convincingly defeated a world-champion program in each case.
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[1712.01208] The Case for Learned Index Structures
Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, the authors posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. Initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets.
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[1712.00559] Progressive Neural Architecture Search
Learning CNN structures that is more efficient than previous approaches: Instead of using reinforcement learning (RL) or genetic algorithms (GA), the authors use a sequential model-based optimization (SMBO) strategy. The learned model achieves state-of-the-art performance on ImageNet.
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