Nvidia as the AI Infrastructure Powerhouse

Jensen Huang has made it clear during our private analyst session —NVIDIA is not just an AI company; it is an AI infrastructure company. Unlike AI solution providers that build end-user applications, NVIDIA is creating the foundational platform upon which the next generation of AI-driven industries will be built.

Huang’s vision positions AI as an industrial infrastructure, akin to electricity or cloud computing—not merely a product, but a core economic driver that will power everything from enterprise IT to autonomous factories.

The AI Compute Model: A Two-Sided AI Supply Chain

NVIDIA’s strength lies in orchestrating two interconnected supply chains, enabling a comprehensive AI ecosystem:

1. Hardware-Software AI Supply Chain (Upstream)

• NVIDIA supplies the core AI computing stack: GPUs, networking, acceleration frameworks, and system software.
• Technologies such as Blackwell, Spectrum-X, NVLink, and CUDA form the backbone of AI compute.
• Dynamo, NVIDIA’s AI orchestration layer, optimizes GPU resources and AI inference, similar to how Kubernetes transformed cloud workloads.

2. AI Ecosystem & Partner Supply Chain (Downstream)

• NVIDIA does not build end-user AI solutions but enables OEMs, solution providers, and industry partners to integrate AI.
• Major players like Cisco, HPE, Dell, Accenture, Deloitte, and global system integrators (GSIs) take NVIDIA’s foundational technology and deploy it across industries.
• Neural Interface Modules (NIMs) and AI blueprints accelerate partner innovation by providing ready-to-deploy AI infrastructure.

By staying out of the end-user AI business, NVIDIA fosters AI adoption across industries without competing with its partners, ensuring widespread ecosystem growth.

AI Factories: Replacing Data Centers for the Next Industrial Revolution

Huang reinforced the concept of AI factories, a fundamental shift from traditional data centers:

• AI factories are purpose-built for AI training and inference at scale, optimizing power efficiency and extreme compute density.
• Unlike incremental IT upgrades, AI factories demand a complete re-architecture of enterprise IT.
• This mirrors past industrial revolutions, where early adopters of automation and electricity redefined entire sectors.

The Market Strategy: NVIDIA as an AI Platform, Not an AI Product

NVIDIA’s AI infrastructure strategy is built on three key pillars:

1. Standardization, Not Customization

• NVIDIA creates scalable AI compute architectures that partners can adopt with confidence.
• AI enterprises can invest in NVIDIA’s ecosystem without fear of obsolescence.

2. Partner-Driven AI Adoption

• Rather than competing with AI solution providers, NVIDIA empowers them by offering the underlying infrastructure.
• GSIs, OEMs, and vertical software vendors integrate AI into industry-specific workflows, extending NVIDIA’s market reach.

3. Infrastructure, Not Applications

• Unlike companies focused on AI applications, NVIDIA remains the foundational AI provider.
• This ensures that enterprises, cloud providers, and developers are dependent on NVIDIA’s stack for AI-scale computing.

Enterprise IT Re-Architecture: AI as the New Foundation of Business

Huang’s during our closed door session at GTC 2025 underscored a radical shift in enterprise computing:

• Legacy enterprise IT was never designed for AI workloads, creating bottlenecks.
• Traditional CPUs and VMware-based IT stacks are inefficient for AI-scale computing.
• Enterprise AI-first strategies must replace outdated cloud-first models, rethinking storage, networking, and compute architectures.

Inference at Scale: The Hardest AI Problem to Solve

Huang emphasized that AI inference, not training, is the biggest computational challenge today:

• Training is a batch process, but inference is continuous and business-critical.
• Token processing (in tokens per second) has replaced FLOPS as the key benchmark for AI efficiency.
• Power efficiency is the new compute frontier: AI workloads are constrained by power, not hardware availability.

NVIDIA is addressing inference scalability with:

• FP4 Precision Computing, optimizing AI throughput.
• KV Cache Orchestration, enabling multi-turn AI reasoning.
• Dynamo AI OS, orchestrating inference workloads dynamically.

The Future of Software: AI-Driven Development and the End of Explicit Coding

Huang predicts a transformation in how software is built:

• Explicit Programming (Traditional Computing): Developers write precise, brittle instructions.
• Implicit Programming (AI-Augmented Development): AI helps interpret and refine high-level goals.
• Autonomous Programming (AI-Driven Development): AI generates and optimizes code in real time, shifting from coding to orchestration.

Key Takeaways for Developers:

• AI replaces syntax-based programming with goal-oriented development.
• Orchestration overtakes manual coding as AI handles execution details.
• NIMs (Neural Interface Modules) will replace traditional APIs in future AI-native applications.

The Full-Stack AI Datacenter Revolution: Rebuilding Infrastructure for AI

NVIDIA is reinventing the datacenter with AI-native principles:

1. Compute Scaling: From Traditional Servers to AI Factories

• High-density AI compute racks are replacing conventional IT configurations.
• Blackwell GPUs and NVLink interconnects maximize AI efficiency.

2. Networking Innovations: Spectrum-X & Packaged Optics

• AI workloads require petabyte-scale, low-latency interconnects that traditional Ethernet cannot provide.
• Packaged optics and silicon photonics will replace copper interconnects to scale AI across datacenters.
• Spectrum-X Supercharged Ethernet optimizes AI networking, reducing bottlenecks.

3. Power & Cooling Innovations: AI Datacenters at 100kW Per Rack

• Liquid cooling is now a necessity, as AI racks surpass 100kW power consumption.
• AI-driven power optimization is essential for scaling compute infrastructure.

Competitive Landscape: NVIDIA’s Position in the AI Market

Huang’s shared his strategy that positions NVIDIA beyond traditional chip competitors:

• AMD and Intel lack NVIDIA’s deep software integration and AI ecosystem.
• Google, AWS, and Microsoft invest in custom silicon (TPUs, Inferentia), but NVIDIA’s full-stack approach ensures widespread adoption across cloud providers.
• No major player currently matches NVIDIA’s vertical AI integration—from GPUs to AI orchestration software.

Conclusion: NVIDIA as the AI Backbone of the Future

Jensen Huang’s message this year at GTC 2025 was clear:

• AI is no longer an innovation; it is the next industrial revolution.
• NVIDIA is the core AI infrastructure provider, fueling AI adoption across industries.
• AI-native computing will replace traditional IT, requiring a full enterprise transformation.
• Businesses that adopt AI-first strategies today will dominate tomorrow.

NVIDIA is not just building faster chips—it is architecting the future of intelligence production at scale. As AI factories replace data centers and inference scales to new levels, NVIDIA’s infrastructure will be indispensable to enterprises, hyperscalers, and innovators driving the next wave of AI-native applications.

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Michael Dell on AI Factories, Digital Transformation, and the Future of Computing at GTC 2024

At NVIDIA GTC 2024, Michael Dell, CEO of Dell Technologies, sat down with John Furrier of theCUBE to discuss the rapid evolution of AI infrastructure, enterprise computing, and the role of AI in reshaping the modern economy. As Dell Technologies cements its position as a leader in AI-powered data centers, AI PCs, and full-stack solutions, the conversation highlighted the company’s pivotal role in accelerating AI adoption at scale.

Key Takeaways from the Discussion:

1. AI Factories: The New Backbone of Enterprise Computing

Dell Technologies has been at the forefront of AI infrastructure, delivering over 2,200 AI factories to customers in the past year alone. These AI factories are revolutionizing enterprise computing, shifting from traditional data centers to AI-driven, intelligent infrastructure.

“For 60 years, we’ve been building machines that calculate and compute. Now, we’re building machines that think and create intelligence,” said Michael Dell.

The AI factory model is the next big step in computing, requiring high-performance compute, storage, and networking—all of which Dell is uniquely positioned to deliver at scale.

2. AI Infrastructure is Scaling Rapidly

AI adoption is moving from proof-of-concept to full-scale deployment, and Dell is leading the charge in providing end-to-end AI solutions. With $10 billion in AI infrastructure delivered last year, Dell is well-positioned to scale AI for enterprises across industries.

“We’re only in the single-digit percentage of AI adoption. The real explosion is still ahead,” Dell emphasized.

AI’s impact is not just limited to large enterprises—it will expand to small and medium-sized businesses, governments, and consumers, making AI a universal productivity tool.

3. The Rise of AI PCs: Boosting Productivity with Personal AI Assistants

A major highlight of GTC was NVIDIA’s vision for AI-powered PCs, with Dell Technologies playing a key role in bringing these devices to market. These next-gen AI PCs are expected to offer personal AI assistants, enabling users to work smarter, faster, and more efficiently.

“When you get a Dell AI PC, it’s going to give you 10 or 20 more IQ points,” Dell remarked, emphasizing AI’s role in enhancing human intelligence and productivity.

4. Dell’s Partnership with NVIDIA: Full-Stack AI Solutions

The Dell-NVIDIA partnership continues to deepen, with Dell playing a crucial role in providing the compute and storage backbone for NVIDIA’s AI strategy.

“Every part of the AI system is improving at an accelerating rate, and Dell is at the center of that transformation,” said Dell.

Dell’s AI data platform has been designed to operate at 97% of the network’s performance, ensuring that AI models and applications run with maximum efficiency.

5. The AI Revolution is as Big as the Internet and Electricity

Dell framed AI as a technological revolution on the scale of the Industrial Revolution, the Internet, and electricity. The productivity gains, new capabilities, and AI-driven business models emerging from this shift will redefine industries across the board.

“This is not an evolutionary change in computing. It’s a revolution,” Dell emphasized.

6. AI for Good: A Positive Future for Humanity

While AI presents risks, Dell remains optimistic about its potential to solve global challenges, from education and healthcare to economic growth and scientific discovery.

“AI will propel humanity forward. It’s an infinitely patient tutor, a tool for scientific breakthroughs, and a driver of prosperity,” he said.

Final Thoughts: AI is Now Priority #1, #2, and #3

AI is not just a business trend—it’s a fundamental shift that will impact every industry, workforce, and economy. With Dell Technologies positioned as a key enabler of AI infrastructure, AI PCs, and AI-driven business solutions, the company is poised to lead this transformation at scale.

As Dell Technologies gears up for Dell Tech World, the company’s focus remains clear: accelerating AI adoption, delivering AI-driven infrastructure, and enabling enterprises to build the future of intelligence-driven computing.

Stay tuned for more insights from GTC 2024 as theCUBE continues its coverage of AI’s impact on the enterprise world.

HPE CEO Antonio Neri on AI Infrastructure, Private Cloud AI, and the Future of Data Centers

At NVIDIA’s GTC 2024 in San Jose, HPE CEO Antonio Neri sat down with John Furrier of theCUBE at the HPE booth to discuss the rapid transformation of AI infrastructure, data centers, and private cloud AI. The conversation highlighted the critical role of HPE’s technology, hybrid cloud solutions, and strategic partnership with NVIDIA in shaping the next generation of AI-driven enterprises.

Key Takeaways from the Discussion:

1. AI Factories Are Reshaping Data Centers

As enterprises transition from traditional data centers to AI factories, the demand for high-performance computing (HPC), energy efficiency, and intelligent storage solutions is at an all-time high. HPE is leading this shift by integrating liquid cooling, scalable AI infrastructure, and edge computing capabilities to support AI workloads.

“AI is a business productivity tool that requires massive infrastructure, and that’s where HPE is leading the way,” said Antonio Neri.

2. Hybrid Cloud and Private AI: The Future of Enterprise AI

HPE pioneered the concept of hybrid cloud over a decade ago, and today, it is at the forefront of private AI—a solution designed to make AI adoption seamless for enterprises.

“Private AI is a game-changer because enterprises don’t have to worry about integrating separate servers, networking, and storage—it’s an all-in-one solution that’s cloud-native and scalable,” Neri explained.

3. HPE’s Deep Partnership with NVIDIA

The HPE-NVIDIA partnership extends beyond hardware to include co-engineering of AI solutions that deliver time-to-value for enterprises. Jensen Huang, CEO of NVIDIA, highlighted the importance of networking in AI computing, a domain where HPE’s Juniper acquisition will play a critical role.

“It’s not just about the chips—NVIDIA’s AI libraries, combined with HPE’s ability to deploy large-scale infrastructure, create a powerful AI ecosystem for enterprises,” Neri emphasized.

4. The Rise of AI Agents and Enterprise AI Adoption

Neri shared his insights on how enterprises are leveraging AI agents to re-engineer workflows, digitize processes, and drive automation. While large language models (LLMs) require extensive training, specialized AI agents can deliver targeted solutions more efficiently.

“AI adoption in enterprises is accelerating because of this agentic approach—specific AI agents can handle tasks with fewer tokens, making them faster and more efficient,” he noted.

5. HPE GreenLake: AI and Cloud Convergence

HPE’s GreenLake platform has grown into a $2 billion annualized subscription business, with a 45% growth rate per quarter. Neri attributed this success to HPE’s ability to integrate AI-driven cloud-native experiences with enterprise infrastructure, making AI deployment faster and more scalable.

“Customers want a unified experience. Whether they consume AI infrastructure via CapEx or OpEx, GreenLake provides a flexible, cloud-native, AI-driven experience,” Neri explained.

Final Thoughts: AI is Reshaping Every Industry

The discussion concluded with reflections on the scale of AI transformation, with Neri highlighting that enterprises risk being left behind if they do not adopt AI. The convergence of business model transformation, digital transformation, and AI-driven automation is creating an inflection point across industries.

“No one wants to be left behind. AI is not just a business opportunity—it’s a survival imperative,” Neri warned.

As AI agents, private AI, and hybrid cloud solutions gain traction, HPE’s strategic focus on infrastructure, networking, and AI-driven services positions it as a critical player in the AI economy.

Stay tuned for more insights from GTC 2024 as theCUBE continues its coverage of AI’s impact on the enterprise world.