Exploring Prediction Targets in Masked Pre-Training for Speech Foundation Models

Speech foundation models, such as HuBERT and its variants, are pre-trained on large amounts of unlabeled speech data and then used for a range of downstream tasks. These models use a masked prediction objective, where the model learns to predict information about masked input segments from the unmasked context. The choice of prediction targets in …

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How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular. However, inference of LLMs as single model invocations or …

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10 months to innovation: Definity’s leap to data agility with BigQuery and Vertex AI

At Definity, a leading Canadian P&C insurer with a history spanning over 150 years, we have a long tradition of innovating to help our customers and communities adapt and thrive. To stay ahead in our rapidly evolving industry, we knew a unified data foundation was key to realizing the business and customer experience opportunities offered …

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Exploring creative possibilities: A visual guide to Amazon Nova Canvas

Compelling AI-generated images start with well-crafted prompts. In this follow-up to our Amazon Nova Canvas Prompt Engineering Guide, we showcase a curated gallery of visuals generated by Nova Canvas—categorized by real-world use cases—from marketing and product visualization to concept art and design exploration. Each image is paired with the prompt and parameters that generated it, …