Conference Presentation
Kevin Cochrane, CMO, Vultr: Building the AI-ready Enterprise, Modernizing Your Cloud Infrastructure
- The next decade is projected to shift from enterprise AI experimentation to the large-scale production deployment of agentic AI, necessitating the reinvention of application architectures and infrastructure stacks.
- Organizations are expected to transform every line of business operation while establishing centralized governance frameworks to enforce single points of control over data, privacy, security, and local market compliance.
- Enterprises will prioritize avoiding vendor lock-in by adopting open ecosystems, with a specific anticipation that the European community will lead in developing open source and open standards for AI infrastructure.
- Future infrastructure strategies will rely on composability principles—such as mock compliance, core microservices, API-first approaches, and orchestrated multi-cloud environments—to prevent the creation of unique "snowflake" solutions.
- AI infrastructure is predicted to evolve into an integrated stack combining CPU and GPU resources within a single cloud-native engineering pipeline to ensure consistent customer and employee experiences.
- Vulture plans to implement a hybrid architecture integrating cloud-native engineering services with AI-native practices and GPU compute to safely stream data from on-premises locations to GPU clusters for training, tuning, and inference.
- The industry is expected to move toward a platform engineering approach with centralized teams pre-building and governing application artifacts, enabling a self-service experience where developers and data scientists automate pipelines for on-demand scaling.
- Global AI innovation will be supported by the automatic provisioning of accelerated GPU compute, CPU compute, AI-optimized storage, and networking resources across 32 data center regions on six continents.
- A next-generation, AI-first public cloud is planned to integrate with existing data center infrastructure to facilitate secure data use for model training, specifically addressing the security risks associated with using lightweight wrappers on external models like ChatGPT.
- Data sovereignty will be strictly enforced, with expectations that data originating in France must remain resident there, utilizing hybrid cloud architecture to ensure compliance with privacy and residency requirements.
- Vulture aims to reduce challenges related to computational complexity, security, cost, and global scaling by templatizing use cases to accelerate time to market.
- A specific future scenario in healthcare anticipates the secure streaming of lab data to Vulture clusters to enable patients to receive agent-driven health habit insights immediately via mobile applications.
- The industry outlook emphasizes a transition to owning proprietary AI models and data rather than relying on external providers, driven by the need for secure and controlled data environments.