The success of any machine learning (ML) pipeline depends not just on the quality of model used, but also the ability to train and iterate upon this model. One of the key ways to improve an ML model is by choosing better tunable parameters, known as hyperparameters. This is known as hyperparameter optimization (HPO). However, … Read more
With the growth and popularity of online social platforms, people can stay more connected than ever through tools like instant messaging. However, this raises an additional concern about toxic speech, as well as cyber bullying, verbal harassment, or humiliation. Content moderation is crucial for promoting healthy online discussions and creating healthy online environments. To detect … Read more
Globally, there has been an accelerated shift toward frictionless digital user experiences. Whether it’s registering at a website, transacting online, or simply logging in to your bank account, organizations are actively trying to reduce the friction their customers experience while at the same time enhance their security, compliance, and fraud prevention measures. The shift toward … Read more
“Intelligent document processing (IDP) solutions extract data to support automation of high-volume, repetitive document processing tasks and for analysis and insight. IDP uses natural language technologies and computer vision to extract data from structured and unstructured content, especially from documents, to support automation and augmentation.” – Gartner The goal of Amazon’s intelligent document processing (IDP) … Read more
Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. JumpStart also offers example notebooks that use Amazon SageMaker features like spot instance training and experiments over a large variety of model types and … Read more
According to a 2020 survey of data scientists conducted by Anaconda, data preparation is one of the critical steps in machine learning (ML) and data analytics workflows, and often very time consuming for data scientists. Data scientists spend about 66% of their time on data preparation and analysis tasks, including loading (19%), cleaning (26%), and … Read more
Recently, the Amazon SageMaker Studio launched an easy way to run notebooks as batch jobs that can run on a recurring schedule. Amazon SageMaker Studio Lab also supports this feature, enabling you to run notebooks that you develop in SageMaker Studio Lab in your AWS account. This enables you to quickly scale your machine learning … Read more
Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). It provides a single, web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models. Within an Amazon SageMaker Domain, users can provision a personal Amazon SageMaker Studio IDE application, which … Read more
Amazon SageMaker now allows you to compare the performance of a new version of a model serving stack with the currently deployed version prior to a full production rollout using a deployment safety practice known as shadow testing. Shadow testing can help you identify potential configuration errors and performance issues before they impact end-users. With … Read more
As companies are increasingly adopting machine learning (ML) for their mainstream enterprise applications, more of their business decisions are influenced by ML models. As a result of this, having simplified access control and enhanced transparency across all your ML models makes it easier to validate that your models are performing well and take action when … Read more
Administrators of machine learning (ML) workloads are focused on ensuring that users are operating in the most secure manner, striving towards a principal of least privilege design. They have a wide variety of personas to account for, each with their own unique sets of needs, and building the right sets of permissions policies to meet … Read more
The world is at increasing risk of global food shortage as a consequence of geopolitical conflict, supply chain disruptions, and climate change. Simultaneously, there’s an increase in overall demand from population growth and shifting diets that focus on nutrient- and protein-rich food. To meet the excess demand, farmers need to maximize crop yield and effectively … Read more
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step of the ML workflow, from preparing data to building, training, tuning, and deploying models. To access SageMaker Studio, Amazon SageMaker Canvas, or other Amazon ML environments like RStudio on Amazon SageMaker, … Read more
Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In addition to the interactive ML experience, data workers also seek solutions to run notebooks as ephemeral jobs without the need to refactor code as Python modules or learn DevOps tools and best practices … Read more
This is a guest post co-written by Julian Blau, Data Scientist at xarvio Digital Farming Solutions; BASF Digital Farming GmbH, and Antonio Rodriguez, AI/ML Specialist Solutions Architect at AWS xarvio Digital Farming Solutions is a brand from BASF Digital Farming GmbH, which is part of BASF Agricultural Solutions division. xarvio Digital Farming Solutions offers precision … Read more
Artificial intelligence (AI) is one of the most transformational technologies of our generation and provides huge opportunities to be a force for good and drive economic growth. It can help scientists cure terminal diseases, engineers build inconceivable structures, and farmers yield more crops. AI allows us to make sense of our world as never before—and … Read more
We’re thrilled to announce that Stability AI has selected AWS as its preferred cloud provider to power its state-of-the-art AI models for image, language, audio, video, and 3D content generation. Stability AI is a community-driven, open-source artificial intelligence (AI) company developing breakthrough technologies. With Amazon SageMaker, Stability AI will build AI models on compute clusters … Read more
Amazon SageMaker Autopilot, a low-code machine learning (ML) service that automatically builds, trains, and tunes the best ML models based on tabular data, is now integrated with Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for ML. This enables the automation of an end-to-end flow of building ML models using … Read more
Today we are excited to announce that AI21 Jurassic-1 (J1) foundation models are available for customers using Amazon SageMaker. Jurassic-1 models are highly versatile, capable of both human-like text generation, as well as solving complex tasks such as question answering, text classification, and many others. You can easily try out this model and use it … Read more
Artificial intelligence (AI) and machine learning (ML) are some of the most transformative technologies we will encounter in our generation—to tackle business and societal problems, improve customer experiences, and spur innovation. Along with the widespread use and growing scale of AI comes the recognition that we must all build responsibly. At AWS, we think responsible … Read more
Over the last 5 years, artificial intelligence (AI) and machine learning (ML) have evolved from a niche activity to a rapidly growing mainstream endeavor. Today, more than 100,000 customers across numerous industries rely on AWS for ML and AI initiatives that infuse AI into a broad range of business use cases to automate repetitive and … Read more
In 2019, Amazon co-founded the climate pledge. The pledge’s goal is to achieve net zero carbon by 2040. This is 10 years earlier than the Paris agreement outlines. Companies who sign up are committed to regular reporting, carbon elimination, and credible offsets. At the time of this writing, 377 companies have signed the climate pledge, … Read more
Amazon Kendra is an intelligent search service powered by machine learning (ML). Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. Amazon Kendra users can now quickly find the … Read more
Amazon CodeWhisperer is a machine learning (ML)-powered service that helps improve developer productivity by generating code recommendations based on developers’ prior code and comments. Today, we are excited to announce that AWS administrators can now enable CodeWhisperer for their organization with single sign-n (SSO) authentication. Administrators can easily integrate CodeWhisperer with their existing workforce identity … Read more
Machine learning (ML) models are taking the world by storm. Their performance relies on using the right training data and choosing the right model and algorithm. But it doesn’t end here. Typically, algorithms defer some design decisions to the ML practitioner to adopt for their specific data and task. These deferred design decisions manifest themselves … Read more
This is a guest post by Stephen Carrad, Vice President at JP Morgan Chase & Co. JPMorgan & Chase Co. started its cloud journey four years ago, building the integrations required to deploy cloud-native applications into the cloud in a resilient and secure manner. In the first year, three applications tentatively dipped their toes into … Read more
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step of the ML workflow, from preparing data to building, training, tuning, and deploying models. Studio comes with built-in integration with Amazon EMR so that data scientists can interactively prepare data at … Read more
Cardiovascular diseases (CVDs) are the number one cause of death globally: more people die each year from CVDs than from any other cause. The COVID-19 pandemic made organizations change healthcare delivery to reduce staff contact with sick people and the overall pressure on the healthcare system. This technology enables organizations to deliver telehealth solutions, which … Read more
Amazon Rekognition is a computer vision service that makes it simple to add image and video analysis to your applications using proven, highly scalable, deep learning technology that does not require machine learning (ML) expertise. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos and detect inappropriate content. … Read more
Amazon Forecast is a fully managed service that uses statistical and machine learning (ML) algorithms to deliver highly accurate time-series forecasts. Recently, based on Amazon Forecast, we helped one of our retail customers achieve accurate demand forecasting, within 8 weeks. The solution improved the manual forecast by an average of 10% in regards to the … Read more