Artificial Intelligence (AI) is becoming increasingly complex, and the development of AI innovations such as Large Language Models (LLMs) has transformed the technology landscape, leading to enterprises needing to invest more in AI solutions to stay competitive. Building a large language model is a complex and resource-intensive process that involves using MLOps tools, devising a data management strategy, and planning for ways to address model drift, data relevancy, and contextual data addition. As AI applications and use cases become increasingly vital to business outcomes, it’s crucial to implement a sound strategy to remain competitive during this pivotal period for AI.

This webinar will explore the critical role of AI systems in driving business success and the key considerations for setting up an effective AI infrastructure. Learn from a panel of experts from Equinix and cnvrg.io strategies to implement an end-to-end AI platform, including data management, model training, and deployment, using a hybrid cloud architecture. You will gain an understanding of how to build a scalable and reliable AI infrastructure that can drive business innovation and competitive advantage.

What you’ll learn:

• The foundations of a unified and effective AI infrastructure 
• What is MLOps and how does it assist with the life cycle of AI applications
• What to pay attention to when approaching a new AI project
• What to look for when building a new distributed AI solution
• How to achieve AI success with Equinix and cnvrg.io