ML 11324 arch

Boomi uses BYOC on Amazon SageMaker Studio to scale custom Markov chain implementation

This post is co-written with Swagata Ashwani, Senior Data Scientist at Boomi. Boomi is an enterprise-level software as a service (SaaS) independent software vendor (ISV) that creates developer enablement tooling for software engineers. These tools integrate via API into Boomi’s core service offering. In this post, we discuss how Boomi used the bring-your-own-container (BYOC) approach …

1 UBFqy6l.max 1000x1000 1

No cash to tip? No problem. How TackPay built its digital tipping platform on Google Cloud

Society is going cashless. While convenient for consumers, that’s caused a drastic decrease in income for tipped workers and this is the problem TackPay addresses. TackPay is a mobile platform that allows users to send, receive and manage tips in a completely digital way, providing tipped workers with a virtual tip jar that makes it …

PfamDatabase hero

Google Research, 2022 & beyond: Natural sciences

Posted by John Platt, Distinguished Scientist, Google Research (This is Part 7 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) It’s an incredibly exciting time to be a scientist. With the amazing advances in machine learning (ML) and quantum computing, we …

multi

MLOps deployment best practices for real-time inference model serving endpoints with Amazon SageMaker

After you build, train, and evaluate your machine learning (ML) model to ensure it’s solving the intended business problem proposed, you want to deploy that model to enable decision-making in business operations. Models that support business-critical functions are deployed to a production environment where a model release strategy is put in place. Given the nature …

Document AI Workbench is now Generally Available to train document extraction models for your production use cases

Each day, more documents are created and used across companies to make decisions. However, the value in these documents is primarily expressed as unstructured data, which makes the value difficult and manually intensive to extract and use for business processes.  As the number and variety of documents used by businesses proliferate, machine learning (ML) solutions …

ML 13389 image001

Fine-tune text-to-image Stable Diffusion models with Amazon SageMaker JumpStart

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart. Stable Diffusion is a deep learning model that allows you to generate realistic, high-quality images and stunning art in just a few seconds. Although creating impressive images can find use in industries ranging from …

MQMperformance hero

FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation

Posted by Parker Riley, Software Engineer, and Jan Botha, Research Scientist, Google Research Many languages spoken worldwide cover numerous regional varieties (sometimes called dialects), such as Brazilian and European Portuguese or Mainland and Taiwan Mandarin Chinese. Although such varieties are often mutually intelligible to their speakers, there are still important differences. For example, the Brazilian …

Serving PyTorch models with prebuilt containers on Vertex AI

Machine learning (ML) practitioners using PyTorch tell us that it can be challenging to advance their ML project beyond experimentation. That’s why over the last year, we’ve prioritized development workthat makes it easier for PyTorch users to deploy models in the cloud using Vertex AI. Vertex AI is a fully-managed machine learning platform with tools, …

how should ai systems behave

How should AI systems behave, and who should decide?

We’re clarifying how ChatGPT’s behavior is shaped and our plans for improving that behavior, allowing more user customization, and getting more public input into our decision-making in these areas. OpenAI’s mission is to ensure that artificial general intelligence (AGI)[1] benefits all of humanity. We therefore think a lot about the behavior of AI systems we …

ML13269 Ultracluster

Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. At the server level, such training workloads demand faster compute and increased memory allocation. As models grow to hundreds of billions of parameters, they require a distributed training mechanism that spans multiple nodes (instances). In October 2022, we launched Amazon EC2 …