Delivering Responsible, Scalable AI with Amazon Bedrock at Cisco | Amazon Web Services
Scaling AI across regions while maintaining performance and security can be challenging. This video shows how Cisco uses Amazon Bedrock to access multiple models, scale efficiently, and support responsible AI practices. Watch the video to learn how you can scale AI with greater efficiency and control.
How is Cisco approaching responsible generative AI?
Cisco is intentionally building generative AI capabilities with a focus on fairness, transparency, and security so customers can trust how AI is used in their products and services.
This means:
- Fairness: Designing AI features to reduce bias and support consistent outcomes across different users and regions.
- Transparency: Being clear about how AI is used in Cisco solutions and what customers can expect from AI-driven features.
- Security: Protecting data and models with enterprise-grade security practices, aligned with Cisco’s broader security posture.
By combining these principles with AWS’s guidance on responsible AI, Cisco aims to reimagine how AI is embedded into its portfolio while maintaining customer trust.
Why did Cisco choose Amazon Bedrock for its AI features?
Cisco chose Amazon Bedrock to support its generative AI roadmap because it aligns with both technical and business requirements:
- Access to multiple leading models: Bedrock provides easy access to cutting-edge models from several providers through a single managed service, so Cisco can pick the right model for each use case.
- Global scalability: Cisco needs AI features that work reliably across regions. Bedrock’s global footprint helps deliver wide regional availability and low latency for users in different locations.
- Cost-effective deployment: Bedrock lets Cisco support features that may have high geographic reach but relatively low initial load, without overprovisioning infrastructure.
- Security and governance: Using AWS-managed services helps Cisco align AI workloads with existing cloud security, compliance, and governance practices.
Together, these capabilities help Cisco scale AI features efficiently while staying aligned with its responsible AI commitments.
How does Amazon Bedrock help Cisco scale AI securely and efficiently?
Amazon Bedrock gives Cisco a managed foundation to scale AI features without having to build and operate all the underlying AI infrastructure.
Practically, this helps Cisco in several ways:
- Elastic scaling: Cisco can support new AI features that may start with modest usage but need to grow quickly, without large upfront infrastructure investments.
- Low-latency experiences: Bedrock’s global presence helps Cisco deliver AI responses with low latency, improving end-user experience across regions.
- Security and compliance: By running on AWS, Cisco can take advantage of AWS’s security controls and best practices, helping protect data used by AI features.
- Faster innovation cycles: With infrastructure and model access handled by Bedrock, Cisco’s teams can focus more on product capabilities and less on managing AI stacks.
This combination allows Cisco to rethink how AI is integrated into its offerings—scaling responsibly, controlling costs, and maintaining strong security standards.
Delivering Responsible, Scalable AI with Amazon Bedrock at Cisco | Amazon Web Services
published by UPCONNECT LABS LLP
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