Alpha's Manifesto

A black and white figure's thought-hive

My sh*tpost generator: screaming-bot

Text generation with nltk, markovify, Tumblr, docker

(Image used without permission from Gunshow comic: Robot that screams.)

If the word offends you, below the fold I use it a lot, so you might not want to read this article. However, I think it’s the most appropriate term.

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The future of work, aided by AI?

How machine learning algorithms may take on our work

Bee-Drones image

I recently came across the article Using Artificial Intelligence to Augment Human Intelligence, by Shan Carter and Michael Nielsen. I’d like to tell you a bit about the ideas that this essay mentions, and a few interpretations of my own about them.

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Correlation ≠ causation

But causation ⇒ correlation

Correlation vs causation

In my earlier post I explained how certain type of machine learning models, specifically neural networks, find the correlations between two sets of values. For predictive models, we feed correlated variables to train our models. However, sometimes, we don’t know if or how variables correlate, and part of the machine learning intelligence is to actually find that out.

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Neural Networks can learn anything

A simple explanation on the basis of neural network learning

Neural Networks

This is a question I’ve been recently asked, and I think it’s interesting enough to share about. A few people asked me how is it that machines can learn, and specifically, how is it that neural networks can learn to understand data that may be really complex. The goal of this article is not to give an in-depth explanation, but rather one that can be easily understood.

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