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New
The latest blog posts to take off on Hacker News. 3,092 posts.
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How to break a Captcha system in 15 minutes with Machine Learning
Let’s hack the world’s most popular Wordpress CAPTCHA Plug-in
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An Interactive Introduction to Quantum Computing
This article was originally written in 2014, but has had some minor improvements in December 2017 and January 2018 when I received some useful feedback after the article had unexpectedly been posted on Hacker News in December 2017.
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Photo-realistic lip-sync from text
We present ObamaNet , the first architecture that generates both audio and synchronized photo-realistic lip-sync videos from any new text. Contrary to other published lip-sync approaches, ours is only composed of fully trainable neural modules and does not rely on any traditional computer graphics methods. More…
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Neural Network on a Commodore 64 (1987)
Neural Network on a Commodore 64
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Flare: Clojure Dynamic Neural Net Library
I wrote Flare, a Dynamic Neural Net library in Clojure.
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Neural Networks in JavaScript with Deeplearn.js
An extensive tutorial on how to implement a neural network in JavaScript with deeplearn.js to perform machine learning in JavaScript. You can bring neural networks to your browser by using the performance benefits of WebGL. Deeplearn.js makes it possible to implement a WebGL powered neural network ...
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Deep image prior 'learns' on just one image
Deep convolutional networks have become a popular tool for image generation and restoration. Generally, their excellent performance is imputed to their ability to learn realistic image priors from a large number of example images. In this paper, we show that, on the contrary, the structure of a generator network is…
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The impossibility of intelligence explosion
In 1965, I. J. Good described for the first time the notion of “intelligence explosion”, as it relates to artificial intelligence (AI):
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A friendly Introduction to Backpropagation in Python
My aim here is to test my understanding of Karpathy’s great blog post “Hacker’s guide to Neural Networks” as well as of Python, to get a hang of which I rece...
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A Cookbook for Machine Learning: Vol 1
This was a busy week, I had no time to read anything new, so I'm sharing a note that I wrote for myself, for no other reason than to understand things better. It's a kind of cookbook of various "transformations" you can apply to...
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A Guide to Natural Language Processing
A guide to Natural Language Processing (NLP): how to analyze text, extract information and understand documents written in a natural language
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Augmented reality with Python and OpenCV
You may (or may not) have heard of or seen the augmented reality Invizimals video game or the Topps 3D baseball cards. The main idea is to render in the screen of a tablet, PC or smartphone a 3D mo…
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Gaussian Distributions Are Soap Bubbles
This post is just a quick note on some of the pitfalls we encounter when dealing with high-dimensional problems, even when working with something as simple as a Gaussian distribution. Last week I wrote about mixup [https://www.inference.vc/mixup-data-dependent-data-augmentation/] a new data-augmentation...
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Capsule Networks Explained
Assumed Knowledge: Convolutional Neural Networks, Variational Autoencoders Disclaimer: This article does not cover the mathematics behind Capsule Networks, but rather the intuition and motivation behind them. What are Capsule Networks and why do they exist? The Capsule Network is a new type of neural network…
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An Introduction to Deep Learning for Language Modeling
Language models assign probability values to sequences of words. Those three words that appear right above your keyboard on your phone that try to predict the next word you’ll type are one of the uses of language modeling. In the case shown below, the language model is predicting that “from”, “on” and “it” have a high…
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The often-overlooked random forest kernel
Ryan Marcus, assistant professor at the University of Pennsylvania. Using machine learning to build the next generation of data systems.
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Language Models, Word2Vec, and Efficient Softmax Approximations
The Word2Vec model has become a standard method for representing words as dense vectors. This is typically done as a preprocessing step, after which the learned vectors are fed into a discriminative model (typically an RNN) to generate predictions such as movie review sentiment, do machine translation, or even…
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Speech Recognition Is Not Solved
Ever since Deep Learning hit the scene in speech recognition, word error rates have fallen dramatically. But despite articles you may have read, we still don’t have human-level speech recognition. Speech recognizers have many failure modes. Acknowledging these and taking steps towards solving them is critical to…
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A Theory of Sequence Memory in Neocortex
Why neurons have thousands of synapses, a theory of sequence memory in neocortex Hawkins & Ahmad, Front. Neural Circuits 2016 It all began with a fascinating lunchtime conversation with Martin …
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The Neural Net Tank Urban Legend
AI folklore tells a story about a neural network trained to detect tanks which instead learned to detect time of day; investigating, this probably never happened.
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Tensorflow sucks
A detailed analysis