Category: Amazon Machine Learning

With the advent of artificial intelligence (AI) and machine learning (ML), customers and the general public have become increasingly aware of their privacy, as well as the value that it holds in today’s data-driven world. Enterprises are actively seeking out and marketing privacy-first solutions, especially in the Computer Vision (CV) domain. They need to reassure […]

Amazon SageMaker Serverless Inference was recently announced at re:Invent 2021 as a new model hosting feature that lets customers serve model predictions without having to explicitly provision compute instances or configure scaling policies to handle traffic variations. Serverless Inference is a new deployment capability that complements SageMaker’s existing options for deployment that include: SageMaker Real-Time […]

Deployment guardrails in Amazon SageMaker provide a new set of deployment capabilities allowing you to implement advanced deployment strategies that minimize risk when deploying new model versions on SageMaker hosting. Depending on your use case, you can use a variety of deployment strategies to release new model versions. Each of these strategies relies on a […]

In-person user identity verification is slow to scale, costly, and high friction for users. Machine learning (ML) powered facial recognition technology can enable online user identity verification. Amazon Rekognition offers pre-trained facial recognition capabilities that you can quickly add to your user onboarding and authentication workflows to verify opted-in users’ identities online. No ML expertise […]

AutoML is a powerful capability, provided by Amazon SageMaker Autopilot, that allows non-experts to create machine learning (ML) models to invoke in their applications. The problem that we want to solve arises when, due to governance constraints, Amazon SageMaker resources can’t be deployed in the same AWS account where they are used. Examples of such […]

While the fuel economy of new gasoline or diesel-powered vehicles improves every year, green vehicles are considered even more environmentally friendly because they’re powered by alternative fuel or electricity. Hybrid electric vehicles (HEVs), battery only electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), hydrogen cars, and solar cars are all considered types of green vehicles. […]

Machine learning operations (MLOps) are key to effectively transition from an experimentation phase to production. The practice provides you the ability to create a repeatable mechanism to build, train, deploy, and manage machine learning models. To quickly adopt MLOps, you often require capabilities that use your existing toolsets and expertise. Projects in Amazon SageMaker give […]

Today we announce the general availability of Syne Tune, an open-source Python library for large-scale distributed hyperparameter and neural architecture optimization. It provides implementations of several state-of-the-art global optimizers, such as Bayesian optimization, Hyperband, and population-based training. Additionally, it supports constrained and multi-objective optimization, and allows you to bring your own global optimization algorithm. With […]

It’s almost here! Only 9 days until AWS re:Invent 2021, and we’re very excited to share some highlights you might enjoy this year. The AI/ML team has been working hard to serve up some amazing content and this year, we have more session types for you to enjoy. Back in person, we now have chalk […]

The AWS AI/ML Community has compiled a series of session guides to AWS re:Invent 2021 to help you get the most out of re:Invent this year. They covered four distinct categories relevant to AI/ML. With a number of our guide authors attending re:Invent virtually, you will find a balance between virtually accessible sessions and sessions […]