Tag: tensorflow
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Welcome to a New Era of Building in the Cloud with Generative AI on AWS | Amazon Web Services
We believe generative AI has the potential over time to transform virtually every customer experience we know. The number of companies launching generative AI...
Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements | Amazon Web Services
Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML)...
Scale foundation model inference to hundreds of models with Amazon SageMaker – Part 1 | Amazon Web Services
As democratization of foundation models (FMs) becomes more prevalent and demand for AI-augmented services increases, software as a service (SaaS) providers are looking to...
Explore advanced techniques for hyperparameter optimization with Amazon SageMaker Automatic Model Tuning | Amazon Web Services
Creating high-performance machine learning (ML) solutions relies on exploring and optimizing training parameters, also known as hyperparameters. Hyperparameters are the knobs and levers that...
Stream large language model responses in Amazon SageMaker JumpStart | Amazon Web Services
We are excited to announce that Amazon SageMaker JumpStart can now stream large language model (LLM) inference responses. Token streaming allows you to see...
How Veriff decreased deployment time by 80% using Amazon SageMaker multi-model endpoints | Amazon Web Services
Veriff is an identity verification platform partner for innovative growth-driven organizations, including pioneers in financial services, FinTech, crypto, gaming, mobility, and online marketplaces. They...
Whisper models for automatic speech recognition now available in Amazon SageMaker JumpStart | Amazon Web Services
Today, we’re excited to announce that the OpenAI Whisper foundation model is available for customers using Amazon SageMaker JumpStart. Whisper is a pre-trained model for...
Reinventing a cloud-native federated learning architecture on AWS | Amazon Web Services
Machine learning (ML), especially deep learning, requires a large amount of data for improving model performance. Customers often need to train a model with...
Data Availability a Pathway to Informed Decision Making- PrimaFelicitas
Life in a fast-paced world, in particular a ‘modern world’ where making decisions has become increasingly challenging, whether steering own life or overseeing large...
Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson’s Max-Cut at Low Circuit Depths
Reuben Tate1, Jai Moondra2, Bryan Gard3, Greg Mohler3, and Swati Gupta41CCS-3 Information Sciences, Los Alamos National Laboratory, Los Alamos, NM 87544, USA2Georgia Institute of...
Train and deploy ML models in a multicloud environment using Amazon SageMaker | Amazon Web Services
As customers accelerate their migrations to the cloud and transform their business, some find themselves in situations where they have to manage IT operations...
Orchestrate Ray-based machine learning workflows using Amazon SageMaker | Amazon Web Services
Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. This complexity often leads to the need...
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