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New
The latest blog posts to take off on Hacker News. 250 posts.
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OpenAI technical goals
OpenAI’s mission is to build safe AI, and ensure AI’s benefits are as widely and evenly distributed as possible.
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Generative Models
This post describes four projects that share a common theme of enhancing or using generative models, a branch of unsupervised learning techniques in machine learning. In addition to describing our work, this post will tell you a bit more about generative models: what they are, why they are important, and where they…
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Announcing Google Research, Europe
Posted by Emmanuel Mogenet, Head of Google Research, EuropeGoogle’s ongoing research in Machine Intelligence is what powers many of the products be...
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Machine Learning 101: What Is Regularization?
Posts and writings by Datanice
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K-Nearest Neighbors from Scratch
Using JavaScript, we implement the k-Nearest Neighbors algorithm from the bottom up.
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A Simple Explanation of How Image Recognition Works
Update: This article is part of a series. Check out the full series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7 and Part 8! You…
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AI produces realistic sounds that fool humans
A video-trained system from MIT’s Computer Science and Artificial Intelligence Lab could help robots understand how objects interact with the world.
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Perceptrons – the most basic form of a neural network
A Go implementation of a perceptron as the building block of neural networks and as the most basic form of pattern recognition and machine learning.
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Machine learning for financial prediction
Machine learning for trading is a huge domain, but not all applications are practical in terms of making your money grow. Let's find out what really works!
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A Simple Content-Based Recommendation Engine in Python
Let's pretend we need to build a recommendation engine for an eCommerce web site. There are basically two approaches you can take: content-based and collaborative-filtering. We'll look at some...
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AI, Deep Learning, and Machine Learning: A Primer [video]
watch time: 45 minutes “One person, in a literal garage, building a self-driving car.” That happened in 2015. Now to put that fact in context, compare this to 2004, when DARPA sponsored the very first driverless car Grand Challenge. Of the 20 entries they received then, the winning entry went 7.2 miles; in 2007, in...
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Elasticsearch Based Image Search Using RGB Signatures
In my previous post , I described some experiments I was doing to reduce images to a Bag of Visual Words (BOVW) . My goal is to build a Con...
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Emoji and Deep Learning
Dango - Your Emoji Assistant
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Boosting Sales with Machine Learning
How we use natural language processing to qualify leads
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Motion Stills – Create Looping GIFs from Live Photos
Posted by Ken Conley and Matthias Grundmann, Machine PerceptionToday we are releasing Motion Stills, an iOS app from Google Research that acts as a...
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Can computers become conscious?: My reply to Roger Penrose
A few weeks ago, I attended the Seven Pines Symposium on Fundamental Problems in Physics outside Minneapolis, where I had the honor of participating in a panel discussion with Sir Roger Penrose. T…
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Open Source Speech Recognition
I’m currently working on the Vaani project at Mozilla, and part of my work on that allows me to do some exploration around the topic of speech recognition and speech assistants. After looking at some of the commercial offerings available, I thought that if we were going to do some kind of add-on API, we’d be best off…
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Intel acquires Itseez, leading developer of OpenCV
Intel Newsroom delivers the latest news, announcements, and updates. Stay informed on Intel innovations.
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DeepText: Facebook's text understanding engine
Visit the post for more.
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Deep Reinforcement Learning: Pong from Pixels
Musings of a Computer Scientist.
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Our Hybrid lda2vec Algorithm
The goal of lda2vec is to make volumes of text useful to humans (not machines!) while still keeping the model simple to modify. It learns the powerful word r...
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Autoencoding Blade Runner: reconstructing films with artificial neural networks
Reconstructing films with artificial neural networks
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Fizz Buzz in Tensorflow
interviewer: Welcome, can I get you coffee or anything? Do you need a break? me: No, I've probably had too much coffee already! interviewer: Great, great. And are you OK with writing code on the...
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