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AI and efficiency
We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet (by contrast, Moore’s Law would yield an 11x cost improvement over this period). Our results suggest that for AI tasks with high levels of recent investment, algorithmic progress has yielde
Protecting Deployments
Pushing a change to your project results in a Preview Deployment. Then, once you're ready, merging it into results in a Production Deployment with the domain of your choice.master Even though Preview Deployments receive a unique URL, they might still be accessed by anyone that finds out about the URL. Today, we're introducing two features for easily protecting them right from the Dashboard. Read more
Categorizing Products at Scale
Jukebox
We’re introducing Jukebox, a neural net that generates music, including rudimentary singing, as raw audio in a variety of genres and artist styles. We’re releasing the model weights and code, along with a tool to explore the generated samples.
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