This is part of a larger series on the new infrastructure of the era of AI, highlighting emerging technology and trends in large-scale compute. This month, we’re sharing the 2024 edition of the State of AI Infrastructure report to help businesses harness the power of AI now.?
The era of AI is upon us. You’ve heard about the latest advancements in our technology, the new AI solutions powered by Microsoft, our partners, and our customers, and the excitement is just beginning. To continue the pace of these innovations, companies need the best hardware that matches the workloads they are trying to run. This is what we call purpose-built infrastructure for AI—it’s infrastructure that is customized to meet your business needs. Now, let’s explore how Microsoft cloud infrastructure has evolved to support these emerging technologies.
The State of AI Infrastructure
An annual report on trends and developments in AI infrastructure based on Microsoft commissioned surveys conducted by Forrester Consulting and Ipsos
Looking back at Microsoft’s biggest investments in AI infrastructure
2023 brought huge advancements in AI infrastructure. From new virtual machines to updated services, we’ve paved the way for AI advancements that include custom-built silicon and powerful supercomputers.
Some of the highlights of Microsoft AI infrastructure innovations in 2023 include:
- Launching new Azure Virtual Machines powered by AMD Instinct and NVIDIA Hopper graphics processing units (GPUs), optimized for different AI and high-performance computing (HPC) workloads, such as large language models, mid-range AI training, and generative AI inferencing.
- Introducing Azure confidential VMs with NVIDIA H100 GPUs—enabling secure and private AI applications on the cloud.
- Developing custom-built silicon for AI and enterprise workloads, such as Azure Maia AI accelerator series, an AI accelerator chip, and Azure Cobalt CPU series, a cloud-native chip based on Arm architecture.
- Building the third most powerful supercomputer in the world, Azure Eagle, with 14,400 NVIDIA H100 GPUs and Intel Xeon Sapphire Rapids processors and achieving the second best MLPerf Training v3.1 record submission using 10,752 H100 GPUs.
Understanding the state of AI and demand for new infrastructure
2024 is shaping up to be an even more promising year for AI than its predecessor. With the rapid pace of technological advancements, AI infrastructure is becoming more diverse and widespread than ever before. From cloud to edge, CPUs to GPUs, and application-specific integrated circuits (ASICs), the AI hardware and software landscape is expanding at an impressive rate.
To help you keep up with the current state of AI, its trends and challenges, and to learn about best practices for building and deploying scalable and efficient AI systems, we’ve recently published our Microsoft Azure: The State of AI Infrastructure report. The report addresses the following key themes:
- Using AI for organizational and personal advancement
AI is revolutionizing the way businesses operate, with an overwhelming 95% of organizations planning to expand their usage in the next two years. Recent research commissioned by Microsoft highlights the role of AI in driving innovation and competition. Beyond mandates, individuals within these organizations recognize the value AI brings to their roles and the success of their companies. IT professionals are at the forefront of AI adoption and use, with 68% of those surveyed already implementing it in their professional work. But it doesn’t stop there—AI is also being used in their personal lives, with 66% of those surveyed incorporating it into their daily routines.
AI’s transformative potential spans across industries, from improving diagnostic accuracy in healthcare to optimizing customer service through intelligent chatbots. As AI shapes the future of work, it’s essential for organizations to embrace its adoption to stay competitive in an ever-evolving business landscape. - Navigating from AI exploration to implementation
The implementation of AI in businesses is still in its early stages, with one-third of companies exploring and planning their approach. However, a significant segment has progressed to pilot testing, experimenting with AI’s capabilities in real-world scenarios. They’re taking that next critical step towards full-scale implementation. This phase is crucial as it allows businesses to gauge the effectiveness of AI, tailor it to their specific needs, and identify any potential issues before a wider rollout.
Because of this disparity in adoption, organizations have a unique opportunity to differentiate themselves and gain a competitive advantage by accelerating their AI initiatives. However, many organizations will need to make significant tech and infrastructure changes before they can fully leverage AI’s benefits. Those who can quickly navigate from exploration to implementation will establish themselves as leaders in leveraging AI for innovation, efficiency, and enhanced decision-making. - Acknowledging challenges of building and maintaining AI infrastructure
To fully leverage AI’s potential, companies need to ensure they have a solid foundation to support their AI strategies and drive innovation. Like the transportation industry, a solid infrastructure to manage everyday congestion is crucial. However, AI infrastructure skilling remains the largest challenge, both within companies and in the job market. This challenge is multifaceted, encompassing issues such as the complexity of orchestrating AI workloads, a shortage of skilled personnel to manage AI systems, and the rapid pace at which AI technology evolves. These hurdles can impede an organization’s ability to fully leverage AI’s potential, leading to inefficiencies and missed opportunities. - Leveraging partners to accelerate AI innovation
Strategic partnerships play a pivotal role in the AI journey of organizations. As companies delve deeper into AI, they often seek out solution providers with deep AI expertise and a track record of proven AI solutions. These partnerships are instrumental in accelerating AI production and addressing the complex challenges of AI infrastructure. Partners are expected to assist with a range of needs, including infrastructure design, training, security, compliance, and strategic planning. As businesses progress in their AI implementation, their priorities shift towards performance, optimization, and cloud provider integration.
Engaging the right partner can significantly expedite the AI journey for businesses of any size and at any stage of AI implementation. This presents a substantial opportunity for partners to contribute, but it also places a responsibility on them to ensure their staff is adequately prepared to provide consulting, strategy, and training services.
Discover more
To drive major AI innovation, companies must overcome many challenges at a breakneck pace. Our insights in The State of AI Infrastructure report underscore the need for a strategic approach to building and maintaining AI infrastructure that is agile, scalable, and capable of adapting to the latest technological advancements. By addressing these infrastructure challenges, companies can ensure they have a solid foundation to support their AI strategies and drive innovation.
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