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Speed up your time series forecasting by up to 50 percent with Amazon SageMaker Canvas UI and AutoML APIs

AWS Machine Learning

SageMaker Canvas supports a number of use cases, including time-series forecasting used for inventory management in retail, demand planning in manufacturing, workforce and guest planning in travel and hospitality, revenue prediction in finance, and many other business-critical decisions where highly-accurate forecasts are important.

APIs 86
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Enhance customer service efficiency with AI-powered summarization using Amazon Transcribe Call Analytics

AWS Machine Learning

Transcribe Call Analytics is a generative AI-powered API for generating highly accurate call transcripts and extracting conversation insights to improve customer experience, agent productivity, and supervisor productivity. Simply turn the feature on from the Amazon Transcribe console or using the start_call_analytics_job API.

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How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

AWS Machine Learning

It offers solutions for media transcription, facial recognition, content summarization, object detection, and other AI capabilities to solve the unique challenges professionals face across industries. Amazon Transcribe The transcription for the entire video is generated using the StartTranscriptionJob API.

APIs 98
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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning

Services range from financing and investment to property management. AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards.

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Efficient continual pre-training LLMs for financial domains

AWS Machine Learning

The resulting LLM outperforms LLMs trained on non-domain-specific datasets when tested on finance-specific tasks. Collecting and preparing finance data Domain continual pre-training necessities a large-scale, high-quality, domain-specific dataset. the SEC assigned identifier). and FinPythia 6.9B.

Finance 90
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Amazon SageMaker model parallel library now accelerates PyTorch FSDP workloads by up to 20%

AWS Machine Learning

Customers are now pre-training and fine-tuning LLMs ranging from 1 billion to over 175 billion parameters to optimize model performance for applications across industries, from healthcare to finance and marketing. Training performant models at this scale can be a challenge.

Scripts 93
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 88