While you can train simple neural networks with relatively small amounts of training data with TensorFlow, for deep neural networks with large training datasets you really need to use CUDA-capable ...

Deep learning is changing our lives in small and large ways every day. Whether it’s Siri or Alexa following our voice commands, the real-time translation apps on our phones, or the computer vision ...

Overview: The choice of deep learning frameworks increasingly reflects how AI projects are built, from experimentation to ...

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When the time comes to add an object recognizer to your hack, all you need do is choose from many of the available ones and retrain it for your particular objects of interest. To help with that, [Edje ...

Android development is not limited to cute little apps that split the bill in restaurants (that seems to be everyone’s “genius app idea,” or is it just me?). Android is a powerful platform with ...

Ben Khalesi writes about where artificial intelligence, consumer tech, and everyday technology intersect for Android Police. With a background in AI and Data Science, he’s great at turning geek speak ...

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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google today introduced TensorFlow Lite 1.0, its framework for developers ...

TensorFlow was created simply to develop your own machine-learning (ML) models. You might even experience it daily and not know it, like recommendation systems that suggest the next YouTube video, ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Despite some of the inherent complexities of using FPGAs for implementing deep neural networks, there is a strong efficiency case for using reprogrammable devices for both training and inference.