More companies are building generative AI applications on AWS

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Kimberly Dixon, senior worldwide security specialist at AWS, said at an online ASEAN security briefing on July 3 that the company made key announcements about its products and solutions at AWS Re:inforce, which took place in Philadelphia from June 10 to 12, demonstrating the company's commitment to enabling customers to build generative AI and AI applications on AWS.

More companies are building generative AI applications on AWS
Kimberly Dixon, Senior Worldwide Security Specialist at AWS

“Generative AI requires a defense-in-depth approach. Generative AI is incredibly powerful and is transforming the way we do business and innovate. Customers choose AWS because we give them the tools to run their AI workloads in a secure, private, and reliable way,” she added.

“The addition of these capabilities to our services makes three important things clear: First, AWS is the most secure cloud platform. Second, our commitment to security is why customers are increasingly choosing AWS to build their generative AI applications. Finally, customers are improving security outcomes and building innovative generative AI applications on AWS,” she elaborated.

She gave several examples of how customers are using AWS to build defense-in-depth strategies, including companies in Singapore, Thailand, and Vietnam. Specifically, Synapxe, Singapore's national health technology organization, has a HealthX Innovation Sandbox that allows public healthcare organizations to experiment and demonstrate medical innovations in a cost-effective, secure, simulated production environment on its Healthcare Commercial Cloud built on AWS.

Synapxe is also working with AWS on AI and data applications that enable healthcare providers to leverage data analytics and AI across the healthcare system. The sandbox will leverage Amazon Bedrock, a service that enables customers to build and extend generative AI applications using foundational models.

To protect its sandboxes and the medical data within them, Synapxe leverages AWS security services and tools such as AWS Shield Advanced, a managed DDoS protection service, and AWS Web Application Firewall, which protects web applications from common vulnerabilities like SQL injection.

Meanwhile, Arcanic.ai is a Vietnamese company developing a culturally sensitive all-in-one AI platform for Vietnamese businesses and using Amazon SageMaker to fine-tune language models at scale.

Meanwhile, Temus Singapore is a company that provides digital transformation solutions to both the private and public sectors. Temus is leveraging Amazon CodeWhisperer, an AI coding assistant, to provide recommendations to improve quality and security, which has increased developer productivity by 35%, improved code quality, and improved maintainability across all its services with built-in security scanning.

“These customers are building their generative AI applications on AWS because they understand our three-tiered approach to modern application security. AWS integrates three tiers into our generative AI technology stack. Starting at the bottom, we provide secure physical hardware for building and training large-scale language models and foundational models. One key component is our Nitro system, which continuously monitors, protects, and validates instance hardware, including that running our generative AI services. At the middle tier, we provide tools that help build generative AI models, such as Amazon Bedrock, and we developed Amazon Bedrock Guardrails, which filter harmful content to prevent the models from being misused. At the top tier, we have the applications that leverage the large-scale language models and foundational models,” explains Dickson.

During the briefing, building When asked which sectors or industries are most vulnerable to security threats, Dixon responded: “When it comes to security threats, no industry or sector is inherently more vulnerable than another. AWS democratizes access to security tools so that both startups and large enterprises have the same security capabilities. The key is to build a defense-in-depth strategy. AWS continues to reduce the cost of security services like Amazon Macie, which has reduced spending by 80% since its release. This means that regardless of your industry or sector, you can stay secure by leveraging these tools and building layered security configurations.”

“With a Vietnam case study like Arcanic.ai, this example shows how AWS security tools and best practices are being leveraged to develop and secure generative AI applications in Vietnam,” she noted.

More companies are building generative AI applications on AWS
AWS Re-Strengthening 2024

At Re:Inforce 2024, AWS made important announcements and releases designed to help customers build a solid, secure foundation on AWS. First, Amazon GuardDuty now supports malware protection for Amazon S3. Customers often upload large amounts of data to Amazon S3, an object storage service. With this growth in data volume on a global scale, it is critical for customers to be able to automatically detect potential malware in newly uploaded objects to Amazon S3 without having to build complex data scanning pipelines. GuardDuty uses industry-leading third-party malware scanning engines directly within the service to provide robust threat detection.

Second, in identity and access management, AWS IAM now supports passkeys for multi-factor authentication (MFA). Starting in July, AWS is enhancing security by enforcing MFA for all root account users of administrative accounts within AWS organizations. This allows users to verify their identity with more than just a username and password.

Another upgrade to IAM is AWS IAM Access Analyzer, which helps customers achieve least privilege and refine permissions. It introduces recommendations to review and remove unused access keys, passwords, and roles, reducing the attack surface. Additionally, AWS has released custom policy checks to help customers ensure their IAM policies comply with security standards, helping to prevent the deployment of overly permissive policies and improving the security of their overall AWS environment.

More companies are building generative AI applications on AWS

Third, AWS CloudTrail Lake is a managed data lake for all AWS API activity logs, including user, service, and machine logs, and now supports natural language query generation. AWS announced in preview that CloudTrail Lake now supports natural language query generation. For example, customers no longer need to write complex SQL queries to analyze data in CloudTrail Lake. Using natural language, customers can ask CloudTrail Lake questions such as “How many database instances were created without encryption enabled?” or “How many users logged into the AWS console yesterday?” CloudTrail Lake will interpret these questions and generate the appropriate queries for customers to use in their data lake.

Finally, AWS Audit Manager, a service that assists customers with preparing evidence for compliance, reporting, and IT audits, has released updated AI best practices frameworks for Amazon SageMaker. These best practices frameworks for generative AI enable customers to collect evidence and gain visibility into whether their generative AI workloads comply with controls around governance, data security, privacy controls, and business continuity.

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