Intuition Machine - Issue #55

By Intuition Machine • Issue #55 • 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.

Artificial Personhood is the Root Cause Why A.I. is Dangerous to Society

When I began writing my book “The Deep Learning A.I. Playbook”, I had given very little thought about the dangers of Artificial Intelligence (AI). I was fortunate however to be able to form a bit of…

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AI’s Symbol Grounding Problem and the Future of Work

Here’s the kicker though, there are plenty of work that people are simultaneously something people love to do, are good at and the world needs. It is hard to find a shortage of these kinds of work…

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Growing a Machine Learning Practice Inside a Large Financial Firm

I recently had the pleasure of speaking with Zachary Hanif, Director in the Center for Machine Learning (C4ML) at Capital One. I was interested in receiving some unique insight on the challenges of…

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The Machine Learning Reproducibility Crisis « Pete Warden's blog

Gosper Glider Gun I was recently chatting to a friend whose startup’s machine learning models were so disorganized it was causing serious problems as his team tried to build on each other’s work and share it with clients. Even the original author sometimes couldn’t train the same model and get similar results! He was hoping…

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IDEA – nonverbal algorithm assembly instructions

IDEA is a series of nonverbal algorithm assembly instructions, created by Sándor P. Fekete, Sebastian Morr, and Sebastian Stiller.

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How artificial intelligence will transform how we gesture

Smartphones are new tools for body rehabilitation, sports training and motor development.

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Clues for Which I Search and Choose – arg min blog

An outsider tour of reinforcement learning, Part 9. Simple methods solve apparently complex RL benchmarks

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MIT 6.S099: Artificial General Intelligence

An introduction to deep learning through the applied task of building a self-driving car. Taught by Lex Fridman.

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Frontiers | Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction | Psychology

The cerebral cortex predicts visual motion to adapt human behaviour to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain’s internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models.

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Building Literate Machines with Dr. Adam Trischler - Microsoft Research

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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. This complexity grants neural networks their power but also earns them their reputation as confusing and opaque black boxes. Understanding how deep neural networks function is critical for explaining their decisions and enabling us to build more powerful systems.

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Smerity.com: Backing off towards simplicity - why baselines need more love

When we lose accurate baselines, we lose our ability to accurately measure our progress over time.

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Style Transfer as a Service· Rodrigo Castro

Picmatix.com is an online tool that creates digital art by transferring styles to user pictures. This blog post outlines the serverless architecture that powers the website.

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Microsoft: FPGA Wins Versus Google TPUs For AI

Microsoft recently disclosed Project Brainwave, which uses pools of FPGA’s for real-time machine-learning inference, marking the first time the company has shared architecture and performance details of their FPGA-based chips. I take an in depth look at the implications for Intel and Xilinx.

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Mini World of Bits benchmark

Each environment is an HTML page that is 210 pixels high, 160px wide (i.e. identical to ATARI ALE simulator dimensions). The top 50 pixels (with a yellow background) contain the task query - a description of what the agent should do in the environment. T

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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. This book is a spin-off from my previous book “The Deep Learning AI Playbook”. The Playbook was meant for a professional audience. This is targeted to a much wider audience. There are two kinds of audiences, those looking to explore and those looking to optimize. There are two ways to learn, learning by exploration and learning by exploitation. This book is about exploration into the emerging field of Deep Learning.

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