14 Posts
I’ve been thinking a lot about "small data." If you have an image classification problem and 1,000,000 images, then dozens of teams around the world can build a good classifier.
I’ve been thinking a lot about "small data." If you have an image classification problem and 1,000,000 images, then dozens of teams around the world can build a good classifier.
A lawsuit in London could set precedents for how to allocate responsibility when algorithms make poor predictions.
A lawsuit in London could set precedents for how to allocate responsibility when algorithms make poor predictions.
Corporate executives worldwide are gearing up to take advantage of AI. But those in different countries aim to use the technology differently, and they bring different hopes and fears.
Corporate executives worldwide are gearing up to take advantage of AI. But those in different countries aim to use the technology differently, and they bring different hopes and fears.
Wish you could draw, but your elephants look like crocodiles? Sketchforme doesn’t have that problem. This AI agent roughs out simple scenes based on text descriptions.
Wish you could draw, but your elephants look like crocodiles? Sketchforme doesn’t have that problem. This AI agent roughs out simple scenes based on text descriptions.
Machine learning systems are infamous for making predictions that can’t readily be explained. Now Microsoft offers an open source tool kit providing a variety of ways to interrogate models.
Machine learning systems are infamous for making predictions that can’t readily be explained. Now Microsoft offers an open source tool kit providing a variety of ways to interrogate models.
Larger neural networks can deliver better results, yet researchers found a way to make deep learning models perform just as well at one-tenth the size. Their work was awarded best paper at this year's International Conference on Learning Representations.
Larger neural networks can deliver better results, yet researchers found a way to make deep learning models perform just as well at one-tenth the size. Their work was awarded best paper at this year's International Conference on Learning Representations.
Data wranglers have tried bulking up training data sets with synthetically generated images, but such input often fails to capture real-world variety. Researchers propose a way to generate labeled data for visual tasks that aims to bring synthetic and real worlds into closer alignment.
Data wranglers have tried bulking up training data sets with synthetically generated images, but such input often fails to capture real-world variety. Researchers propose a way to generate labeled data for visual tasks that aims to bring synthetic and real worlds into closer alignment.
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