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Population-based training of neural networks
Neural networks have shown great success in everything from playing Go and Atari games to image recognition and language translation. But often overlooked is that the success of a neural network at a particular application is often determined by a series of choices made at the start of the research, including what…
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An On-Device Deep Neural Network for Face Detection
Apple started using deep learning for face detection in iOS 10. With the release of the Vision framework, developers can now use this…
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Google Brain Toronto
A “vector” is a geometric object with two important properties: magnitude and direction. These two attributes might also describe Canada’s AI sector today, as key inves…
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Keras Tutorial – Traffic Sign Recognition
In this tutorial Tutorial assumes you have some basic working knowledge of machine learning and numpy., we will get our hands dirty with deep learning by solving a real world problem.The problem we...
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WebVR Experiments
We’ve created a showcase of the amazing VR experiences developers are building on the web. To play with them, all you need is a browser.
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Unexpected Consequences of Self-Driving Cars
Many new technologies have unexpected impacts on the physical or social world in which we live.
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Microsoft acquires deep learning startup Maluuba
Today is an exciting day for the advancement of AI at Microsoft. We have agreed to acquire Maluuba, a Montreal-based company with one of the world’s most impressive deep learning research labs for natural language understanding. Maluuba’s expertise in deep learning and reinforcement learning for question-answering and…
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Facets: An Open Source Visualization Tool for Machine Learning Training Data
Posted by James Wexler, Senior Software Engineer, Google Big Picture Team(Cross-posted on the Google Open Source Blog)Getting the best results out ...
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Object detection: an overview in the age of Deep Learning
This guide provides an overview of practical Object Detection applications, its main challenges as a Machine Learning problem and how Deep Learning has changed the way to tackle it.
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TensorFlow machine learning now optimized for the Snapdragon 835 and Hexagon 682
Boost your TensorFlow apps with the Snapdragon 835 and Hexagon 682 DSP. Unleash the power of AI and machine learning. Download the SDK now.
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Using IBM Bluemix Watson APIs to Optimise my CV
Using IBM Bluemix Watson APIs to optimise my CV (resume)
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Agents that imagine and plan
Imagining the consequences of your actions before you take them is a powerful tool of human cognition. When placing a glass on the edge of a table, for example, we will likely pause to consider how stable it is and whether it might fall. On the basis of that imagined consequence we might readjust the glass to prevent…
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Pixel Visual Core: Google’s first custom-designed co-processor
Google’s first custom-designed co-processor for consumer products is built into every Pixel 2. Soon, it will enable more applications to use Pixel 2’s camera for taking …
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My Favorite Deep Learning Papers of 2017
Here are five deep learning papers I felt rose above the rest in 2017.
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Brain vs. Deep Learning (2015)
This blog post compares deep learning to the brain and derives an estimate of computational power for the brain which is used to predict the singularity.
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Using logistic regression to predict parking difficulty
Posted by James Cook, Yechen Li, Software Engineers and Ravi Kumar, Research Scientist"When Solomon said there was a time and a place for everythin...
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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...