Everyone talks about building AI factories, but who's actually powering them. DDN. We are to data what Nvidia is to compute.And that's why the world's biggest AI systems run on DDN. Come to supercomputing. We will show you why.[Music]. ...

Please welcome to the stage president semiameas Joe Stkunis. >> It's Semicon and we are focused on AI today. So it makes sense to start with a presentation from a leader of the most valuable company in the world and the leading semiconductor supplier to the AI community, Nvidia.Dr. . Timothy Costa, general manager industrial and computational engineering at NVIDIA, spearheads the strategic development and implementation of solutions for critical industries including semiconductors. He leads the industrial e ...

Hi everyone, welcome to the Rav show. We are your at NVIDIA GDC in Washington and I'm super excited to be with Joe from DDN. Joe, welcome to the Rav show.Super excited to chat today. >> Thank you. Thank you.Pleasure to be here. Thanks for coming over here. Appreciate it.>> Yes. Uh Joe, uh I know we'll be talking a lot about you know the AI ROI industry impact AI factories and uh what's happening at DDN. But just before getting into that, would you like to quickly introduce yourself.Tell us more about what y ...

But joining us now for an exclusive interview is Naav Zafrier, Checkpoint Software CEO. Naav, it's great to have you back on the show. Uh, welcome.And I do want to start with the AI factories and this deal with Nvidia. I think first just like let's take a step back. What are we talking about when we talk about AI factories and what is so special about them in terms of securing the data and the infrastructure.>> Yeah. Hi Morgan and thank you. So um as we are all struggling to stay relevant, we're moving thro ...

Vertiv matures system-level infrastructure designs to support future NVIDIA AI infrastructure , /PRNewswire/ -- Vertiv (NYSE: VRT), a global leader in critical digital infrastructure, today announced a milestone in its collaboration with NVIDIA to accelerate the next generation of AI factories, detailing its design maturity for 800 VDC power architectures. Building on its strategic alignment announced in May 2025, Vertiv has significantly advanced its platform designs to accelerate its 'unit of compute' s ...

Group 1 - Nvidia's stock has increased approximately 40% this year, driven by significant investments in Intel and OpenAI, indicating a strategic expansion beyond AI product sales [1][2] - The partnership with Intel involves a $5 billion investment, allowing Nvidia to utilize Intel's manufacturing facilities for AI products, which is a strategic move given Intel's current low valuation [4][5][6] - Nvidia's CEO envisions a new era of computing characterized by AI factories, which are data centers designed to meet the high computing power demands of AI systems [6][7] Group 2 - The collaboration with OpenAI and Intel aims to address the inadequacies of current data centers in supporting AI infrastructure, highlighting the need for rapid expansion in this area [7][8] - An example of the growing demand for AI infrastructure is the British government's initiative to increase its AI computing capacity by 20 times over the next five years, with Nvidia supplying up to 31,000 AI chips for this project [8]

Core Viewpoint - Nvidia is positioned as a leading stock to capitalize on global AI growth, driven by its hardware sales for large language models and its expanding role in the AI ecosystem [1][5]. Group 1: AI Factories and Infrastructure - AI factories, as defined by CEO Jensen Huang, are specialized data centers for developing, training, and deploying AI models at scale, with Nvidia promoting its Blackwell-powered factories globally [3]. - Nvidia's next-generation Rubin platform is set to follow the Blackwell GPU architecture in 2026, indicating ongoing innovation in its offerings [3]. - The company is involved in significant projects worldwide, such as the UAE's Stargate data center and Germany's sovereign AI factory with Deutsche Telekom, highlighting its role in the emerging "intelligence infrastructure" [4]. Group 2: Growth Potential - Nvidia is expected to benefit from the expanding AI infrastructure, with its GPU clusters, software, and networking solutions being integral to many large data centers [4]. - The company's growth trajectory is anticipated to continue, making it a recommended addition to investment portfolios over the next year [5].

Core Viewpoint - Nvidia shares have rebounded significantly, recovering 48% since early April, outperforming the Nasdaq Composite's 27% rebound, and are now only 10% off their all-time high [1][2] Group 1: Growth Drivers - The first phase of the AI wave has led to a fourfold increase in Nvidia's data center sales over the last two years, driven by the demand for advanced GPUs [4] - Nvidia's CEO highlighted a tenfold surge in AI inference token generation within a year, indicating strong global demand for Nvidia's AI infrastructure [5] - The complexity and volume of queries processed by AI models are increasing, with Nvidia maintaining a dominant position in AI inference [8] Group 2: AI Factories - Nvidia is at the forefront of developing AI factories, which are advanced data centers that support the entire AI lifecycle from data input to inference [9][10] - The company provides software that optimizes GPU performance, significantly reducing costs for customers, with some reductions reaching up to 20-fold compared to older technologies [11] Group 3: Market Position and Future Outlook - Nvidia has established itself as a primary supplier for AI infrastructure, benefiting from the mainstream adoption of AI technologies like chatbots [13] - The company is expanding its offerings with software stacks and services around large language models (LLMs), positioning itself for continued revenue growth despite potential competition in GPU supply [14] - Nvidia's partnership with Saudi Arabia's state-owned AI company Humain to build AI factories demonstrates its global market strategy and commitment to leveraging its advanced GPU technology [12]

Core Insights - NVIDIA's earnings call highlighted strong demand for GPUs, significant revenue growth from AI factories, and challenges related to the China market [1][2][17] GPU Demand - NVIDIA delivered 1,500 GB200 architectures in April and projects at least 5,000 units for Q2, with potential for over 10,000 units, indicating strong investor sentiment [3][5] - Major hyperscalers are deploying nearly 1,000 NVL 72 racks weekly, translating to 72,000 Blackwell GPUs, with Microsoft leading the charge [4][8] AI Factories - Datacenter revenue grew by 73%, driven by AI factory build-outs, with nearly 100 NVIDIA-powered AI factories launching this quarter, doubling from last year [6][16] - The average number of GPUs per AI factory has also doubled, showcasing increasing demand for NVIDIA's infrastructure [16] China Predicament - Jensen Huang emphasized the importance of the $50 billion AI market in China, arguing that U.S. export controls may hinder American technology leadership [17][18] - The U.S. policy may inadvertently strengthen Chinese chipmakers and innovation, as China continues to develop its AI capabilities independently [19][20] Future Outlook - NVIDIA is projected to achieve $500 billion in annual revenues over the next five years, with a compound annual growth rate of 38%, positioning it for potential $1 trillion sales by the 2030s [22][23]

Core Insights - Nvidia is pivotal to the current state of AI technology, with its innovations being essential for advancements in the field [6][8][24] - Jensen Huang, Nvidia's CEO, is focused on maintaining a competitive edge without directly competing with customers like OpenAI [33] Company Overview - Nvidia has transitioned through various technology cycles, including gaming and cryptomining, before focusing on AI, which has infinite demand for computing power [7][9][10] - The company operates as a cutting-edge R&D laboratory, outsourcing manufacturing while relying heavily on Taiwanese suppliers [17][19] Market Dynamics - The current capital expenditure (CapEx) cycle is expected to continue growing, driven by increasing demand for AI computing power [21][22] - Nvidia's market cap could potentially increase by $3 trillion, with significant opportunities in healthcare and robotics [24][25] Competitive Landscape - Nvidia's competitive advantage lies in its software development kits and close relationships with scientists, which are difficult for competitors to replicate [28][32] - Concerns about tariffs and competition from Chinese manufacturers are significant risks for Nvidia, as they could impact profit margins and market position [17][19][20] Technological Innovations - The concept of "AI factories" is emerging, where Nvidia's hardware operates in industrial settings to process AI requests efficiently [15][26] - Nvidia's Omniverse platform aims to revolutionize robotics training through high-fidelity simulations, potentially leading to substantial market opportunities [27][25]