Category: Amazon Machine Learning

Generative artificial intelligence (AI) is easy to use but it’s important not to confuse ease of use with effortless deployment. The value of generative AI is inextricably linked to the technology’s reliability and traceability. To achieve this reliability and traceability in any organization, it helps to focus on AI’s potential one use case at a time but also to plan for the bigger picture. Read this blog post for a tried-and-tested AI framework to consider.

On March 20, the Amazon Web Services (AWS) IMAGINE: Nonprofit conference returns to the Washington, DC metropolitan area for our eighth year of learning with nonprofit leaders from around the world. This annual event inspires nonprofits to rethink what’s possible for their mission, through the latest innovations in the cloud. Discover new ideas, build connections, and interact with cutting-edge technology onsite. Whether it’s your first time attending, or your eighth, here are a few tips to make the most of IMAGINE: Nonprofit 2024.

Generative artificial intelligence (AI) allows anyone to leverage machine learning (ML) capabilities using natural language, and it is extremely intuitive to use. When users are able to search, analyze, and draw conclusions in seconds—from extensive information that exists across their organization or the internet—they can make more informed decisions at speed. This blog post takes a quick look at some of the generative AI considerations public sector organizations need to take.

Access Partnership recently conducted a study commissioned by Amazon Web Services (AWS) on artificial intelligence (AI) skills across various industries globally. The results underscored the need to address low rates of AI fluency among healthcare leaders and employees, and this blog post provides a summary and analysis of the study’s key findings.

Amazon Rekognition, a code-free automated machine learning (AutoML) service from Amazon Web Services (AWS), showed impeccable diagnostic performance in categorizing various retinal diseases using optical coherence tomography (OCT) scans. This blog post details the steps to use Amazon Rekognition Custom Labels to train a model that categorizes retinal diseases and the process of training and fine-tuning convolutional neural networks (CNNs), the standard deep learning methodology.

At the end of 2022, Northwestern University’s Kellogg School of Management had a decision to make. The on-premises SQL server used by faculty and students had reached the end of its life, and the school needed to identify a cost-effective way forward while ensuring that the datasets would remain highly available for researchers to use on demand. After weighing various options, Kellogg worked with Amazon Web Services (AWS) to create a data lake that fit its unique needs.

Amazon Web Services is proud to join senior decision-makers and thought leaders from around the world at the Munich Security Conference (MSC) from February 16-18. At MSC 2024, we’re restating our commitment to protecting the defense and national security of the US, its closest allies, and other like-minded countries around the world.

As talent shortages grow, job vacancies are commonplace across governmental agencies. Add the challenge of retaining existing talent and government agencies face a perfect storm. Read this blog post to learn how a technology called intelligent document processing (IDP) can help agencies accomplish their missions faster—even as vacancies mount.

Amazon Web Services (AWS) made more than 140 announcements at re:Invent 2023. In this blog post, we’ll take key announcements from re:Invent and apply them to relevant K12 education use cases. From generative artificial intelligence (AI) to cost optimization, AWS can support your school, district, or educational service agency and enhance both the classroom and administrative experience. 

To improve safety and convenience, transportation agencies amass a substantial volume of data. However, these organizations encounter challenges in data accuracy validation due to issues related to data quality and occasional missing information. With the incorporation of new artificial intelligence and machine learning capabilities from Amazon Web Services (AWS), they can take advantage of no-code solutions to identify and address data gaps.