Teachable Machine lets you train a model to help you wave at cats.
Our favorite example is Teachable Machine, which walks you through a training process using images from your webcam to trigger response GIFs. It shows how training in the browser can help the model adapt to different contexts. For example, if you want your model to spot when a user raises their hand, a pre-trained model might have trouble if the user is sitting in a room surrounded by mannequins. Because you can train the Teachable Machine model with specific examples of both “raised hand” and “unraised hand,” there’s a good chance it will perform well in your weird mannequin room (a very specific situation). A related webcam-based example is the work Oz Ramos is doing to build a system for navigation using facial gestures, to help people with mobility impairments use the web.
Minsuk Kahng’s deeplearning.js node lets you edit the code and immediately view the results.
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Apr 19 2018
by — Today we are launching a mini-site featuring our collection of short stories inspired by new developments in machine learning. Beginning with our fourth report, we started including a science-fiction story along with the technical and strategic overviews that are the bulk of each report. Using these stories, we can look at the technologies we profile from a different angle and explore their c...
Apr 25 2018
Are novel, complex, and specialized neural network architectures always better for language modeling? Recent papers have shown otherwise. Language models are used to predict the next token given the preceeding tokens. Most operate at word-level or character-level. Word-level models have large vocabulary sizes (how many words are there in the English language?) compared to character-level models...
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