Soft Power in the Age of Generative Models

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What happens when a post-Trump, reputationally-bruised United States, and improved generative models (the technology behind "deepfakes") collide head-on?


On Saudi Drone Strikes and Adversarial AI

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In world of weaponized drones piloted by algorithms, what new strategic opportunities arise?


Artificial Intelligence and Geopolitics

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I'm beginning to write about the intersection of artificial intelligence and geopolitics.


Deriving Mean-Field Variational Bayes

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A detailed derivation of Mean-Field Variational Bayes, its connection to Expectation-Maximization, and its implicit motivation for the "black-box variational inference" methods born in recent years.


Deriving Expectation-Maximization

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Deriving the expectation-maximization algorithm, and the beginnings of its application to LDA. Once finished, its intimate connection to variational inference is apparent.


Additional Strategies for Confronting the Partition Function

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Stochastic maximum likelihood, contrastive divergence, negative contrastive estimation and negative sampling for improving or avoiding the computation of the gradient of the log-partition function. (Oof, that's a mouthful.)


A Thorough Introduction to Boltzmann Machines

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A pedantic walk through Boltzmann machines, with focus on the computational thorn-in-side of the partition function.


From Gaussian Algebra to Gaussian Processes, Part 2

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Introducing the RBF kernel, and motivating its ubiquitous use in Gaussian processes.


From Gaussian Algebra to Gaussian Processes, Part 1

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A thorough, straightforward, un-intimidating introduction to Gaussian processes in NumPy.


A Practical Guide to the "Open-Source Machine Learning Masters"

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The higher education paradigm is changing. Motivation, logistics and strategic insight re: designing the "Open-Source Masters" for yourself.


© Will Wolf 2020

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