By Ken Kaplan
Many enterprises are well down their path toward implementing artificial intelligence, whereas others are still unsure how they’ll use it to run their business. Either way, CIOs and IT teams have many choices to make as AI continues to evolve at lightning speed.
AI Challenges and Infrastructure Needs
To get their IT operations AI-ready, forward-thinking leaders are re-evaluating their entire IT ecosystem in order to build the right infrastructures to handle both existing and future AI-powered functions.
"It takes data scientists, AI engineers, and machine learning operational engineers, and then it takes good infrastructure people, along with the developers who build the apps," said Rajiv Ramaswami, president and CEO of Nutanix. "The set of tools that you need to put together AI applications and get them going to market, that’s not easy either. On top of that, there is a shortage of hardware."
Managing IT Infrastructure that Runs AI
According to Donahue, IT teams are exploring three key elements: choosing language models, leveraging AI from cloud services, and building a hybrid multicloud operating model to get the best of on-premise and public cloud services.
"We’re finding that very, very, very few people will build their own language model," he said. "That’s because building a language model in-house is like building a car in the garage out of spare parts."
Conclusion
Prioritizing infrastructure modernization is essential. Embracing AI effectively demands that enterprises reassess and revitalize their underlying IT systems, focusing on the future and achieving the key scalability, capacity, efficiency, and analytical capabilities required to keep up in a fast-changing IT world.
Frequently Asked Questions
Q: What are the key elements of AI adoption?
A: Choosing language models, leveraging AI from cloud services, and building a hybrid multicloud operating model.
Q: Why is infrastructure modernization essential for AI adoption?
A: To achieve the key scalability, capacity, efficiency, and analytical capabilities required to keep up in a fast-changing IT world.
Q: What is GPT-in-a-Box?
A: A comprehensive, pre-configured solution that combines hardware and software to support the deployment of AI models directly on-premises, in the cloud, or at the edge.
Q: What is hybrid multicloud?
A: A cloud model that integrates diverse computing resources and data storage types, facilitating efficient data management and processing, pivotal for the performance of AI systems.
