Vultr Cloud Inference simplifies AI deployment

Vultr launched Vultr Cloud Inference, a new serverless platform.
Leveraging Vultr's global infrastructure spanning six continents and 32 locations, Vultr Cloud Inference provides customers with scalability, reduced latency, and enhanced cost efficiency for their AI deployments.
Today's rapidly evolving digital landscape has challenged businesses across sectors to deploy and manage AI models efficiently and effectively.
This has created a growing need for more inference-optimized cloud infrastructure platforms with both global reach and scalability, to ensure consistent high performance.
This is driving a shift in priorities as organizations increasingly focus on inference spending as they move their models into production.
Developers are being challenged to optimize AI models for different regions, manage distributed server infrastructure, and ensure high availability and low latency.
Vultr Cloud Inference will accelerate the time-to-market of AI-driven features, such as predictive and real-time decision-making while delivering a compelling user experience across diverse regions.
Users can simply bring their own model, trained on any platform, cloud, or on-premises, and it can be seamlessly integrated and deployed on Vultr's global NVIDIA GPU-powered infrastructure.
With dedicated compute clusters available on six continents, Vultr Cloud Inference ensures that businesses can comply with local data sovereignty, data residency, and privacy regulations by deploying their AI applications in regions that align with legal requirements and business objectives.
With the capability to self-optimize and auto-scale globally in real-time, Vultr Cloud Inference ensures AI applications provide consistent, cost-effective, low-latency experiences to users worldwide.
Flexibility in AI model integration and migration: Vultr Cloud Inference, users can get a straightforward, serverless AI inferencing platform that allows for easy integration of AI models, regardless of where they were trained.
For models developed on Vultr Cloud GPUs powered by NVIDIA, in users' own data center, or on another cloud, Vultr Cloud Inference enables hassle-free global inference.
Reduced AI infrastructure complexity: By leveraging the serverless architecture of Vultr Cloud Inference, businesses can concentrate on innovation and creating value through their AI initiatives rather than focusing on infrastructure management.
Cloud Inference streamlines the deployment process, making advanced AI capabilities accessible to companies without extensive in-house expertise in infrastructure management, thereby speeding up the time-to-market for AI-driven solutions.
Automated scaling of inference-optimized infrastructure: Through real-time matching of AI application workloads and inference-optimized cloud GPUs, engineering teams can seamlessly deliver performance while ensuring the most efficient use of resources.
This leads to substantial cost savings and reduced environmental impact, as they only pay for what is needed and used.
Private, dedicated compute resources: With Vultr Cloud Inference, businesses can access an isolated environment for sensitive or high-demand workloads.
This provides enhanced security and performance for critical applications, aligning with goals around data protection, regulatory compliance, and maintaining high performance under peak loads.
As AI continues to push the limits of what's possible and change the way organizations think about cloud and edge computing, the scale of infrastructure needed to train large AI models and to support globally-distributed inference needs has never been greater.
Following the recent launch of Vultr CDN to scale media and content delivery worldwide, Vultr Cloud Inference will provide the technological foundation to enable innovation, increase cost efficiency, and expand global reach for organizations around the world, across industries, making the power of AI accessible to all.


This Cyber News was published on www.helpnetsecurity.com. Publication date: Tue, 19 Mar 2024 11:43:06 +0000


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