Archives for Few-Shot Learning
Flamingo’s ability to handle interwoven text and visuals makes it a natural fit for in-context few-shot learning, similar to GPT-3, which also used few-shot text prompting.
A study in 2019 titled ‘Meta-Transfer Learning for Few Shot Learning’ addressed the challenges that few-shot settings faced.
Vision Transformers (ViTs) is emerging as an alternative to convolutional neural networks (CNNs) for visual recognition.
OpenAI's machine learning models are now available on Microsoft's Azure platform thanks to a new service called the Azure OpenAI Service.
OpenAI's machine learning models are now available on Microsoft's Azure platform thanks to a new service called the Azure OpenAI Service.
Few-shot learning can also be called One-Shot learning or Low-shot learning is a topic of machine learning subjects where we learn to train the dataset with lower or limited information.
The latest tool provides a sandbox for writers to probe the boundaries of transformer-based language models
The post Google Introduces Wordcraft, A Human-AI Collaborative Editor For Story Writing appeared first on Analytics India Magazine.
05
May
GPT-3’s Cheap Chinese Cousin
Chinese company Huawei has developed PanGu Alpha, a 750-gigabyte model that contains up to 200 billion parameters.
The post GPT-3’s Cheap Chinese Cousin appeared first on Analytics India Magazine.
Prototypical networks are more efficient than the recent meta-learning algorithms, making them an appealing approach to few-shot and zero-shot learning.
The post What Are Prototypical Networks? appeared first on Analytics India Magazine.