AWS Public Sector Blog
Tag: best practices
Gamification: Accelerating generative AI and cloud skills development
Generative AI, machine learning (ML), and cloud technologies are revolutionizing the way we work. To succeed in the workforce, proficiency in these technologies is becoming increasingly important. At Amazon Web Services (AWS), we understand the challenges of acquiring new skills and have developed innovative, gamified solutions to make learning more engaging and effective.
6 EdTech AI trends: How artificial intelligence is reshaping education
At AWS, we work with EdTechs of all sizes, giving us unique insight into how AI is shaping the industry. Based on our work with EdTechs and educational institutions around the world, we’ve identified six key trends shaping the future of AI in education.
From vision to reality: Inspiring your educational institution’s first steps in AI with AWS
To support education leaders on their AI journey, we’ve developed a practical guide that maps real-world challenges to proven AI use cases. While not exhaustive, these examples serve as inspiration—highlighting what others have achieved and helping you explore how AI can address your institution’s priorities
Cloud cost savings: 10 tips for academic institutions
For academic institutions leveraging cloud services, it is important to proactively manage and optimize cloud costs. In this post, we explore 10 tips to help control cloud costs using Amazon Web Services (AWS).
Defining organizational roles with a RACI matrix
This post is part four of a four-part series that addresses how a Cloud Center of Excellence (CCOE) can be a viable solution to address the challenges of digital transformation. In this post, we discuss a framework for defining organizational areas of responsibility.
Leverage generative AI for biocuration using Amazon Bedrock and Amazon Nova foundation models
Personalized therapy for diseases such as cancer utilizes an individual’s unique genomic profile to guide treatment decisions. However, the effect and clinical significance of most genetic variants are uncertain. Accurate classification of the clinical significance of novel genetic variants requires extensive curation of peer-reviewed biomedical literature. In recent years, generative AI has demonstrated promising results in information extraction and text summarization. In this post, we explore how various AWS-native solutions can be used to create a secure, retrieval-augmented, and cost-effective biomedical chatbot designed to facilitate biocuration.
How AWS can help partners grow in the Middle East
One of the primary strategies for growth for partners is through global expansion. Amazon Web Services (AWS) continues to invest in infrastructure around the globe. The Middle East is one region with huge potential for growth. According to IDC, more than 75 percent of workloads are on premises in the United Arab Emirates (UAE) and Saudi Arabia. The AWS and IDC report “Unlocking the Full Potential of AI in the Middle East” points out that 28 percent of organizations surveyed in the UAE and Saudi Arabia are currently investing in AI while another 50 percent plan to invest. Read this post to learn more.
4 best practices to enhance research IT operations with AWS
Academic research IT departments around the world face the same challenge: how to balance their existing on-premises infrastructure with the opportunities of cloud computing. At the Supercomputing 2024 (SC24) conference, Amazon Web Services hosted a panel featuring two research IT leaders: Circe Tsui, associate director of solutions architecture at Emory University in the Office of Information Technology, and Dr. Robert Shen, director of the RMIT AWS Supercomputing Hub (RACE) at the Royal Melbourne Institute of Technology (RMIT). During the panel, Tsui and Shen shared how their institutions use AWS to augment and enhance their research operations with more scalability, security, and collaboration alongside their on-premises infrastructure. Read this post to learn more.
How Amazon Redshift ML can help enhance outcomes for underperforming, at-risk students
Higher education institutions are under increasing pressure to demonstrate the effectiveness of their programs and provide students with a clear path to degree completion. Data analytics can help these institutions proactively identify and support at-risk students, allowing them to develop personalized intervention strategies to improve student retention and graduation rates. In this post, we’ll explore how Amazon Redshift ML, a powerful machine learning (ML) capability within the Amazon Redshift data warehouse, can enable higher education leaders to quickly predict student outcomes and communicate insights to key stakeholders.
Securely onboarding countries to the AWS Cloud
In an increasingly digital world, governments and public sector entities are seeking secure and efficient ways to use cloud technologies. As we’ve innovated and expanded the Amazon Web Services (AWS) Cloud, we continue to prioritize making sure customers are in control and able to meet their national regulatory requirements. In this post, we share how AWS is collaborating with national cyber regulators and other public sector entities to enable secure adoption of the AWS Cloud across countries’ public sectors.