Intuition Machine - Issue #56

By Intuition Machine • Issue #56 • View online

Welcome to the weekly newsletter of Deep Learning AI and Blockchain Convergence. We hope that this newsletter will appeal to all those interested in Deep Learning developments and its relationship to decentralized consensus architectures.

Deep Learning’s Uncertainty Principle

DeepMind has a new paper where researchers have uncovered two “surpising findings”. The paper is described in “Understanding Deep Learning through Neuron Deletion”. In networks that generalize well…

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Drawing the Ethical Line on Weaponized Deep Learning Research

Good AI and Deep Learning researchers place a lot of passion into their work. Although they may rarely reflect on the ethical consequences of their creations, there is a belief and even an…

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Tesla’s Factory Woes Reveals Why You Shouldn’t Automate Everything

There are new reports that Tesla’s AI strategy to automate their entire manufacturing process is failing to deliver the productivity they had hoped for. Business Insider reports that “Wall Street…

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The Scientific Paper Is Obsolete. Here's What's Next. - The Atlantic

Here’s what’s next.

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Scientific Communication As Sequential Art

This page presents a scientific paper that has been redesigned as a sequence of illustrations with captions. This comic-like format, with tightly-coupled pictures and prose, allows the author to depict and describe simultaneously — show and tell.

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AI Engineers Must Open Their Designs to Democratic Control | American Civil Liberties Union

In many ways, the most pressing issues of society today — increasing income disparity, chronic health problems, and climate change — are the result of the dramatic gains in higher productivity we’ve achieved with technology and science.

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Brain-Computer Interfaces Show That Neural Networks Learn by Recycling | Quanta Magazine

Using a brain-computer interface, scientists are beginning to learn why learning is hard.

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Buzzword Convergence: Making Sense of Quantum Neural Blockchain AI—Stephen Wolfram Blog

Do the results of stringing popular buzzwords together have meaning? Stephen Wolfram discusses the backgrounds of quantum, neural, blockchain and AI and explores common themes among them, like complexity generation, reversibility and irreversibility.

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Visualising Machine Learning: How do we humanise the intelligence? – Gramener blog

These are exciting times for data science professionals. With the rapid advances being made in analytics, specifically around machine learning, deep learning and AI, researchers and practitioners around the world have started adapting these technologies for deep, human-impacting applications.

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France to spend $1.8 billion on AI to compete with U.S., China | Reuters

French President Emmanuel Macron promised 1.5 billion euros ($1.85 billion) of public funding into artificial intelligence by 2022 in a bid to reverse a brain drain and catch up with the dominant U.S. and Chinese tech giants.

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AI Now Institute

The AI Now Institute at New York University is an interdisciplinary research center dedicated to understanding the social implications of artificial intelligence. Our work focuses on four core domains:

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MIT 6.S191: Introduction to Deep Learning

An introductory course on deep learning methods with applications to machine translation, image recognition, game playing, image generation and more. A collaborative course incorporating labs in TensorFlow and peer brainstorming along with lectures. Course concludes with project proposals with feedback from staff and panel of industry sponsors.

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Understanding Deep Learning through Neuron Deletion | DeepMind

Deep neural networks are composed of many individual neurons, which combine in complex and counterintuitive ways to solve challenging tasks, ranging from machine translation to Go.

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models/research/differential_privacy/pate at master · tensorflow/models · GitHub

GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects.

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Retro Contest

We’re launching a transfer learning contest that measures a reinforcement learning algorithm’s ability to generalize from previous experience.

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Visualizing TensorFlow's streaming shufflers

If you’ve ever played Magic: The Gathering or other card games involving large, unwieldy decks of cards, you’ve probably wondered: How the heck am I supposed to shuffle this thing? How would I even know if I were shuffling properly?

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The UX of AI - Library - Google Design

Using Google Clips to understand how a human-centered design process elevates artificial intelligence

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Deep learning-based methods in biology and medicine | Journal of The Royal Society Interface

Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields.

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Lessons Learned Reproducing a Deep Reinforcement Learning Paper

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Artificial Intuition : The Improbable Deep Learning Revolution

I challenge you to find a field as interesting and exciting as Deep Learning.

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The Annotated Transformer

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Interactive supervision with TensorBoard – TensorFlow – Medium

The TensorBoard projector features t-distributed Stochastic Neighborhood Embedding (t-SNE) for visualizing high-dimensional datasets, since it is a well-balanced dimensionality reduction algorithm…

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Learn about ASLens – A deep learning project that uses AWS DeepLens to translate the American Sign Language alphabet to speech | AWS Machine Learning Blog

For the AWS DeepLens Challenge Hackathon he created the project called ASLens.

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The Mathematics of 2048: Optimal Play with Markov Decision Processes

Finding provably optimal strategies for 2048 using Markov Decision Processes

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Concept2vec: Metrics for Evaluating Quality of Embeddings for Ontological Concepts – Arxiv Vanity

Although there is an emerging trend towards generating embeddings for primarily unstructured data, and recently for structured data, there is not yet any systematic suite for measuring the quality of embeddings.

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