Are you ready to embrace the artificial intelligence (AI) revolution? Many companies are already have made significant strides, driven by the immense potential of AI. According to the IDC, IT spending is rapidly accelerating to capitalize on the AI wave. By 2025, Global 2000 organizations are projected to allocate a staggering 40% of their core IT budgets towards AI-related initiatives. For most IT companies, AI is poised to surpass cloud computing as the primary catalyst for innovation. The race is on.
Know Your AI Acronyms
Before this article reads any further, let's make sure the common acronyms are understood. To navigate the AI landscape, it's essential to understand:
- ML (Machine Learning)
- DL (Deep Learning)
- GenAI (Generative AI)
- LLM (Large Language Models)
- High Performance Computing (HPC)
The Insatiable Appetite of AI
Thanks to groundbreaking advancements like OpenAI's ChatGPT and other forms of GenAI, the ability to generate vast amounts of new content could potentially overwhelm the entire web. Estimates are that by 2027, 90% of the information on the internet will be created by Generative AI. This explosive growth isn’t limited to what AI creates, but what it consumes as well. Despite the remarkable increase in compute capabilities and data capacity over the past 13 years, end users are barely keeping pace with the exponential growth of AI model sizes and their proliferation. What happens if we can’t keep pace?
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What is HPC?
Why is HPC so critical? Because AI has the power to turbocharge nearly every aspect of our lives, and HPC's underlying turbocharged infrastructure is required to make that happen. Simply put, HPC provides the high-performance computing infrastructure to support AI's turbo capabilities.
HPC systems consist of multiple processors working together to perform tasks that would be impossible or take an impractical long time on standard computers. HPC is the backbone that enables the training and deployment of advanced AI models, particularly the computationally intensive large language models and deep learning systems as these require large datasets for training and validation.
HPC systems can process these massive amounts of data quickly and efficiently. Training complex AI models can take an extensive amount of time on regular computing systems. HPC accelerates this process by distributing the computational load across many processors, significantly reducing the time required to train models.
Challenges for AI Implementation
The challenges surrounding AI extend far beyond keeping pace with the rapidly evolving demands. Achieving true success with AI requires addressing several critical factors:
- Flexibility: AI systems must be highly flexible, with an extensible architecture that allows for continuous learning and adaptation as new data becomes available as rigid, static models quickly become obsolete and less useful over time.
- Scalability: The insatiable thirst for data in AI is only going to grow. As model sizes and complexity increase, organizations need elastic infrastructure that provides on-demand scalability to spin up additional compute resources in seamless fashion.
- Data Placement: While cloud computing offers compelling advantages for AI workloads, the data necessary to train AI models may reside on-premises, creating potential issues around latency, cost, and data movement. Intelligent data placement strategies are crucial to ensure optimal performance and cost-efficiency.
The pressure to deliver AI capabilities quickly is immense and it is a delicate balance between rapid deployment and ensuring AI systems are developed and deployed responsibly.
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HPC Expertise from HPE
HPE is a leader in HPC and AI. It only makes sense as HPE has a long-standing legacy and deep expertise in designing and building some of the world's most powerful supercomputers. The HPE Cray Supercomputing EX line powers several of the top supercomputing systems in the world. Their comprehensive portfolio of servers, storage, and networking solutions purpose-built for AI workloads. This includes the Apollo line of servers with support for the latest AI accelerators like NVIDIA GPUs and AMD Instinct GPUs, as well as high-performance storage systems optimized for data-intensive AI training.
HPE Slingshot
Unlocking the full potential of real-time AI hinges on blistering speed. Enter HPE's Slingshot - a cutting-edge interconnect technology that supercharges their high-performance computing (HPC) and AI solutions. With Slingshot, HPE's HPC systems can efficiently handle the massive computational requirements of training the largest AI models and running the most complex simulations in parallel. This interconnect is a key enabler for HPE to deliver powerful, turnkey exascale computing solutions that can tackle the most demanding AI and HPC workloads.
How About AI-as-a-Service?
For those who prefer an on-premises as-a-Service model, HPE GreenLake for AI and Analytics delivers a cloud-like experience for AI/ML and analytics workloads across on-premises, edge, and public cloud environments. This expansive solution allows on-demand scaling of AI/ML infrastructure and capacity and provides customers access to HPE's expertise in AI/ML, HPC, cloud, and edge computing.
HPE GreenLake offers a complete AI infrastructure stack, including high-performance computing, accelerated storage, interconnects, and AI/analytics software and expertise. This enables companies to build and scale AI initiatives with a cloud operating model that combines security, performance, and easy hybrid cloud management through HPE's as-a-service offering.
Don’t Forget What WEI Can Do For You
Don’t get left behind in the AI race. Leverage HPE's advanced technologies, talent, and expertise to accelerate your progress and ensure your AI vision becomes a reality. If you need help defining your vision, contact the AI technology experts at WEI. They can listen to your unique business needs and help you map out a course and strategy to get you started.
Next Steps: Whether you’re a CEO, a business owner, a manager, an IT administrator, or a language translator, it’s crucial to understand AI and how to leverage it in your role. In our free white paper titled, Mastering AI For The Enterprise With HPC: A Comprehensive Guide, discover a deeper understanding of AI and identify the critical role of High-Performance Computing (HPC) in managing extensive datasets and advancing sophisticated machine learning models.
