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Neanderthal vs. ND4J – Native Performance, Java and CPU
Today, Java has a choice of a few well maintained libraries that can use Intel's MKL for fast native operations. MKL is basically as fast as you can get toda...
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The latest blog posts to take off on Hacker News. 3,092 posts.
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Debugging with intelligence via probabilistic inference
Debugging with intelligence via probabilistic inference Xu et al., ICSE’18 Xu et al. have built a automated debugger that can take a single failing test execution, and with minimal interactio…
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Face recognition in images and video with Python
Learn how to perform face recognition using OpenCV, Python, and dlib by applying deep learning for highly accurate facial recognition.
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AI Nationalism
For the past 9 months I have been presenting versions of this talk to AI researchers, investors, politicians and policy makers. I felt it was time to share these ideas with a wider audience. Thanks to the Ditchley conference on Machine Learning in 2017 for giving me a fantastic platform to get ear
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Machine learning can run on tiny, low-power chips
Photo by Kevin Steinhardt When Azeem asked me to give a talk at CogX, he asked me to focus on just a single point that I wanted the audience to take away. A few years ago my priority would have bee…
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Attacks against machine learning – an overview
This blog post surveys the attacks techniques that target AI (Artificial Intelligence) systems and how to protect against them.
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AI winter is well on its way
Deep learning has been at the forefront of the so called AI revolution for quite a few years now, and many people had believed that it is the silver bullet that will take us to
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Empiricism and the limits of gradient descent
This post is actually about artificial intelligence, and argues a position that many AI researchers will disagree with. Specifically, it arg...
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Dissecting Reinforcement Learning
Explaining the basic ideas behind reinforcement learning. In particular, Markov Decision Process, Bellman equation, Value iteration and Policy Iteration algorithms, policy iteration through linear algebra methods. It includes full working code written in Python.
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ML Beyond Curve Fitting: An Intro to Causal Inference and Do-Calculus
Since writing this post back in 2018, I have extended this to a 4-part series on causal inference: * ➡️️ Part 1: Intro to causal inference and do-calculus [https://www.inference.vc/untitled] * Part 2: Illustrating Interventions with a Toy Example…
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Letting neural networks be weird
Machine learning algorithms are not like other computer programs. In the usual sort of programming, a human programmer tells the computer exactly what to do. In machine learning, the human programmer merely gives the algorithm the problem to be solved, and through trial-and-error the algorithm has to figure out how to…
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A Deep Dive into Monte Carlo Tree Search
(This was originally a sponsor talk given at PyCon 2018. Unfortunately there is no video.)
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Counting Bees on a Raspberry Pi with a ConvNet
the first thing i thought when we setup our bee hive was "i wonder how you could count the number of bees coming and going?"
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Reinforcement Learning – Bandit Problems
Table of Contents
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Executing gradient descent on the earth
A common analogy for explaining gradient descent goes like the following: a person is stuck in the mountains during heavy fog, and must navigate their way down. The natural way they will approac......
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Recurrent Neural Network Tutorial for Artists (2017)
Recurrent Neural Network Tutorial for Artists
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Interactive computational neuroscience – part 1, spiking neurons
An interactive introduction to spiking neuron models -- all in the browser. Learn about modeling neurons as dynamical systems and the computational properties of neurons.
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Lessons Learned Reproducing a Deep Reinforcement Learning Paper
There are a lot of neat things going on in deep reinforcement learning. One of the coolest things from last year was OpenAI and DeepMind’s work on training an agent using feedback from a human rather than a classical reward signal. There’s a great blog post about it at Learning from Human Preferences , and the…
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Why collision avoidance is harder for an AI-based system
Recent incident where Uber car was involved in an accident where a cyclist got killed has sparked many comments and opinions. Many blame…
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Exploring Word2Vec
In my previous blog post, I explored some of the early ways of word embeddings and their shortcomings. The purpose of this post is to explo...
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How to build a brain – An introduction to neurophysiology for engineers
How does the brain work? While neuroscience provides insights on small-scale processes and overall behavior, we don’t know much for sure about the learning and processing algorithms in between. In this blog post, I will give an introduction to what we know. Let’s take an engineering perspective and play evolution: How…
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PyTorch – Internal Architecture Tour
Update 28 Feb 2019: I added a new blog post with a slide deck containing the presentation I did for PyData Montreal. Introduction Short intro to Python extension objects in C/C++ Zero-copy PyTorch Tensor to Numpy and vice-versa Tensor Storage Shared Memory DLPack: a hope for the Deep Learning frameworks Babel…