The Foundation for Your AI-Driven Enterprise
Deploy in purpose-built, scalable data centers with the power density and interconnection to support modern workloads.
INFRASTRUCTURE ESSENTIAL FOR AI DEVELOPMENT
CoreSite’s direct onramps to public clouds enable secure, real-time data transfer while reducing data egress costs as much as 70%.* Organizations specializing in AI-scale data transport and AI-specific services can rely on CoreSite data centers for the interconnection, scalability and reliability needed to develop graphics processing unit (GPU) and transaction processing unit (TPU) dependent applications.
PROVEN POWER AND COOLING CAPABILITIES
The compute-intensive workloads our customers run can require as much power and generate the same level of heat that AI applications do. CoreSite works with you to configure a deployment that optimizes power consumption and air cooling best practices while offering the flexibility to integrate emerging techniques such as water cooling.
SCALABILITY CRITICAL TO BUSINESS GROWTH
Your AI-service could start with one GPU-accelerated server but soon need a full rack, cage or data center suite to keep up with business growth. CoreSite data centers are platforms for custom deployments designed with the flexibility to dynamically scale and efficiently store structured and unstructured data.
ENVIRONMENT SUPPORTING DATA INTEGRITY
As much as we focus on data volume, data integrity and relevance are paramount to accurate AI inferences. CoreSite’s networking capabilities protect data in transit among stakeholders in a workflow and to end users. We are committed to providing an environment in which servers run with the reliability and low-latency you need for machine learning and to trust AI-based data analytics.
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ARTIFICIAL INTELLIGENCE
Frequently Asked Questions
WHAT IS ARTIFICIAL INTELLIGENCE?
Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence.
HOW DOES MACHINE LEARNING RELATE TO AI?
Machine learning (ML) is a subset of artificial intelligence that focuses on enabling machines to learn patterns and make decisions from data without explicit programming.
WHAT TYPES OF DATA ARE USED IN AI?
AI relies on diverse datasets, including structured and unstructured data. This can include text, images, videos, sensor data and more. The quality and diversity of the data are crucial for the effectiveness of AI models.
WHY IS DATA INTEGRITY IMPORTANT IN AI?
Data integrity ensures that the data used to train and test AI models is accurate, reliable and representative of real-world scenarios.
HOW DOES CLOUD COMPUTING CONTRIBUTE TO AI DEVELOPMENT?
Cloud computing platforms provide on-demand access to computing resources, allowing organizations to scale their AI infrastructure as needed. Cloud services also offer AI-specific tools and services that facilitate model development, training and deployment.
WHAT SECURITY MEASURES ARE IN PLACE FOR AI EQUIPMENT IN DATA CENTERS?
Security in data centers involves measures to protect data integrity, prevent unauthorized access and ensure the ethical use of AI.