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New
The latest blog posts to take off on Hacker News. 292 posts.
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CUDA 10 in Clojure
CUDA 10 support has just landed in ClojureCUDA with the latest version 0.6.0.
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Translating Between Statistics and Machine Learning
This SEI Blog post explores the differences between statistics and machine learning and how to translate statistical models into machine learning models.
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Imaginary worlds dreamed by BigGAN
These are some of the most amazing generated images I’ve ever seen. Introducing BigGAN, a neural network that generates high-resolution, sometimes photorealistic, imitations of photos it’s seen. None of the images below are real - they’re all generated by BigGAN.
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Night Sight: Seeing in the Dark on Pixel Phones
Posted by Marc Levoy, Distinguished Engineer and Yael Pritch, Staff Software Engineer Night Sight is a new feature of the Pixel Camera app that let...
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Real-Time Noise Suppression Using Deep Learning
Imagine waiting for your flight at the airport. Suddenly, an important business call with a high profile customer lights up your phone. Tons of background noise clutters up the soundscape around you…
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Tensorflow 2.0: models migration and new design
Tensorflow 2.0 will be a major milestone for the most popular machine learning framework: lots of changes are coming, and all with the aim of making ML accessible to everyone. These changes, however, require for the old users to completely re-learn how to use the framework: this article describes all the (known)…
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A Google Brain engineer’s guide to entering AI
Technical AI safety is a multifaceted area of research, with many sub-questions in areas such as reward learning, robustness, and interpretability. These will all need to be answered in order to make sure AI development will go well for humanity as systems become more and more powerful. Not all of these questions are…
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Making floating point math highly efficient for AI hardware
In recent years, compute-intensive artificial intelligence tasks have prompted creation of a wide variety of custom hardware to run these powerful new systems efficiently. Deep learning models, suc…
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Using a Keras Long Short-Term Memory Model to Predict Stock Prices
Editor’s note: This tutorial illustrates how to get started forecasting time series with LSTM models. Stock market data is a great choice for this because it’s quite regular and widely available to everyone. Please don’t take this as financial advice… Continue reading Using a Keras Long Short-Term Memory (LSTM) Model…
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Spinning Up in Deep RL
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Real time numbers recognition (MNIST) on an iPhone with CoreML
Learn how to build and train a deep learning network to recognize numbers (MNIST),how to convert it in the CoreML format to then deploy it on your iPhoneX and …
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Learning Concepts with Energy Functions
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Zero-shot learning: Using text to more accurately identify images
WHAT THE RESEARCH IS: Zero-shot learning (ZSL) is a process by which a machine learns to recognize objects it has never seen before. Researchers at Facebook have developed a new, more accurate ZSL …
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Accelerated “Ray Tracing in One Weekend” in CUDA
Recent announcements of NVIDIA’s new Turing GPUs, RTX technology, and Microsoft’s DirectX Ray Tracing have spurred a renewed interest in ray tracing. Using these technologies vastly simplifies the…
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Horizon: Facebook’s Open Source Applied Reinforcement Learning Platform
In this paper we present Horizon, Facebook’s open source applied reinforcement learning (RL) platform. Horizon is an end-to-end platform designed to solve industry applied RL...
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Getting started with linear algebra
I'd like to introduce a series of blog posts and their corresponding Python Notebooks gathering notes on the Deep Learning Book from Ian Goodfellow, Yoshua B...
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Reinforcement Learning with Prediction-Based Rewards
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Neuron, a new VS Code extension for data science
Access to this page requires authorization. You can try signing in or changing directories .
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Introducing AdaNet: Fast and Flexible AutoML with Learning Guarantees
Posted by Charles Weill, Software Engineer, Google AI, NYC Ensemble learning, the art of combining different machine learning (ML) model prediction...
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Foundations of ML and AI: Book recommendations
Here's what I recommend to programmers if they want to understand machine learning. Six fantastic books that you can work with in your spare time to build yo...
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Playing Mortal Kombat with TensorFlow.js
While experimenting with enhancements of the prediction model of Guess.js, I started looking at deep learning. I’ve focused mainly on recurrent neural networks (RNNs), specifically LSTM because of their “unreasonable effectiveness” in the domain of Guess.js. In the same time, I started playing with convolutional…
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Can optical illusions fool AI too?
Deep neural networks (DNN) have made the news recently for their application as a predictive software used to create convincing fake videos of politicians and celebrities. You may not be aware, however, that you have most likely already used the same technology in a much less controversial form: the translation app on…
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End-to-end implementation of a machine learning pipeline (2017)
In the fall of 2016, I was a Teaching Fellow (Harvard's version of TA) for the graduate class on "Advanced Topics in Data Science (CS209/109)" at Harvard University. I was in-charge of designing the class project given to the students, and this tutorial has been built on top of the project I designed for the class.
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