48 Posts
Large datasets often contain overly similar examples that consume training cycles without contributing to learning. A new paper identifies similar training examples, even if they’re not labeled.
Large datasets often contain overly similar examples that consume training cycles without contributing to learning. A new paper identifies similar training examples, even if they’re not labeled.
Training a model to separate the objects in a picture typically requires labeled images for best results. Recent work upped the ante for training without labels.
Training a model to separate the objects in a picture typically requires labeled images for best results. Recent work upped the ante for training without labels.
Images in the wild may not come with labels, but they often include metadata. A new training method takes advantage of this information to improve contrastive learning.
Images in the wild may not come with labels, but they often include metadata. A new training method takes advantage of this information to improve contrastive learning.
Machine learning is helping lawyers sift through mountains of documents to find evidence. The legal technology company Everlaw launched a clustering feature that automatically organizes up to 25 million documents for lawyers gathering evidence to be used during a trial.
Machine learning is helping lawyers sift through mountains of documents to find evidence. The legal technology company Everlaw launched a clustering feature that automatically organizes up to 25 million documents for lawyers gathering evidence to be used during a trial.
Itching to get your hands on a fully trained large language model? The wait is over. Meta introduced the OPT family of transformer-based language models with nearly unfettered access to source code and trained weights.
Itching to get your hands on a fully trained large language model? The wait is over. Meta introduced the OPT family of transformer-based language models with nearly unfettered access to source code and trained weights.
Vision Transformer (ViT) outperformed convolutional neural networks in image classification, but it required more training data. New work enabled ViT and its variants to outperform other architectures with less training data.
Vision Transformer (ViT) outperformed convolutional neural networks in image classification, but it required more training data. New work enabled ViT and its variants to outperform other architectures with less training data.
Amazon reported long-term success using machine learning to shrink its environmental footprint. The online retailer developed a system that fuses product descriptions, images, and structured data to decide how an item should be packed for shipping.
Amazon reported long-term success using machine learning to shrink its environmental footprint. The online retailer developed a system that fuses product descriptions, images, and structured data to decide how an item should be packed for shipping.
Facebook released a chatbot that summarizes dialog on the fly and uses the summary to generate further repartee.
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