Nvidia Corporation · NASDAQ:NVDA

Nvidia — Investor Presentation (October 2024)

32 slides from Nvidia's investor presentation, October 2024

  1. Slide 1: Investor Presentation

    Investor Presentation October 2024 1

  2. Slide 2: Forward-looking statements

    Except for the historical information contained herein, certain matters in this presentation including, but not limited to, statements as to: our financial position; our markets and market opportunity; demand and supply; demand and growth drivers; the benefits, impact, performance, features and avai

  3. Slide 3: NVIDIA

    NVIDIA NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, revolutionized accelerated computing, ignited the era of modern AI, and is fueling industrial digitalization across markets. Today, two transitions are occurring simultaneously—accel

  4. Slide 4: World's First GPU Turns 25

    World’s First GPU Turns 25 NVIDIA released GeForce 256, the world’s first GPU, 25 years ago. This marked a milestone in computing by providing gamers with higher frame rates, smoother gameplay, and life-like graphics. NVIDIA's GPU set the foundation for the big bang of modern AI, a decade later. The

  5. Slide 5: NVIDIA Scaling with AI Scale-Up and Scale-Out

    NVIDIA Scaling with AI Scale-Up and Scale-Out NVIDIA’s chips and systems supply chain expanded significantly in 2024, while demand continues to exceed supply. NVIDIA Blackwell platform in full production – expanding to support x86 and NVIDIA Grace, air and liquid cooling, NVLink 8-GPU to NVLink 72-G

  6. Slide 6: Accelerated Computing and Generative AI Create Trillion-dollar Opportunities

    Accelerated Computing and Generative AI Create Trillion-dollar Opportunities The $1T installed base of general-purpose CPU data center infrastructure is being modernized to a new GPU accelerated computing paradigm. AI Factories AI The entire computing stack has been reinvented – from CPU to GPU, fro

  7. Slide 7: AI Factories—A New Class of Data Centers

    AI Factories—A New Class of Data Centers Production of digital intelligence tokens AI factories are a new form of computing infrastructure. Its purpose is not to store user and company data or run ERP and CRM applications. AI factories are highly optimized systems purpose- built to process raw data,

  8. Slide 8: NVIDIA's Accelerated Computing Platform

    NVIDIA’s Accelerated NeMo CUDA-Accelerated CUDA-X Agentic AI Libraries Omniverse Computing Platform Libraries CUDA-Accelerated Physical AI Libraries CUDA • DOCA • NCCL NIM CUDA- Data center scale innovation across chips, Accelerated Software Stack Cluster-Scale Software Accelerated “All in-a- networ

  9. Slide 9: Extending NVIDIA Networking to Scale-Up and Scale-Out AI

    Extending NVIDIA Networking to Scale-Up and Scale-Out AI in Any Datacenter New NVLink and Spectrum-X Increase Networking Opportunity Beyond InfiniBand to Every Data Center NVLink + InfiniBand / Spectrum-X AI Performance InfiniBand NVIDIA Spectrum-X AI Ethernet Fabric Traditional Ethernet NVIDIA NVID

  10. Slide 10: Accelerated Computing Starts with CUDA Libraries

    Data Processing Accelerated Computing ~200X cuVS, cuDF-Spark, cuDF-pandas, cuDF-Polars, cuGraph, cuML, XGBoost, RAPIDS, NeMo Curator, Starts with CUDA Libraries cuSOLVER, cuIO Delivering up to 200X Speedup Computer Vision Across Major Workloads CV-CUDA, Deepstream, TAO, Holoscan, cuCIM, ~200X Tensor

  11. Slide 11: Accelerated Computing Is Sustainable Computing

    Accelerated Computing Is Sustainable Computing Order-of-Magnitude More Energy-Efficient Accelerated computing requires higher peak Accelerated computing enables full-stack power consumption than CPUs, however, optimization from algorithm to GPU architecture, completes workloads significantly faster

  12. Slide 12: AI Scaling Laws Drive Exponential Demand for Compute

    AI Scaling Laws Drive Exponential Demand for Compute New OpenAI o1 Long “Thinking Time” Creates a New Way to Scale Training compute scales exponentially with larger models, multi-modality, reinforcement learning, and synthetic Training data generation Compute Inference compute scales exponentially w

  13. Slide 13: NVIDIA is the Leading Inference Platform

    NVIDIA is the Leading Inference Platform Inference Compute Scales Exponentially with “Long Thinking” Hopper inference performance Installed base & CUDA ➔ rapid software innovation Inference compute scaling exponentially with increased 5X in 1 Year ➔ performance ➔ lower inference cost ➔ large multi-m

  14. Slide 14: NVIDIA AI Infrastructure Roadmap at One Year Rhythm

    NVIDIA AI Infrastructure Roadmap at One Year Rhythm NVIDIA’s newest architecture – Blackwell – is an AI infrastructure platform and integrates seven chips, each contributing to performance at data center-scale. Compute demand for AI is scaling exponentially. Model size, multi-modality, synthetic dat

  15. Slide 15: One Year Rhythm | Supercluster Scale | Full-Stack | CUDA Everywhere

    One Year Rhythm | Supercluster Scale | Full-Stack | CUDA Everywhere “Supercharge AI Scaling Law” X-Factors X-Factors X-Factors Hopper Blackwell Blackwell-Ultra Rubin Hopper GPU Hopper+ GPU Rubin GPU Rubin GPU Blackwell Ultra GPU 8S HBM4 12S HBM4 6S HBM3 6S HBM3e 288GB HBM3e More AI FLOPS Vera CPU Gr

  16. Slide 16: One Year Rhythm Drives Annual Cost and Energy Reduction

    One Year Rhythm Drives Annual Cost and Energy Reduction Significant reduction in TCO with each generation Hopper | 8,000 GPUs | 15MW Blackwell GB200 NVL72 | 2,000 GPUs | 4MW 4X Reduction in Power LLM Training Workload: GPT-MoE-1.8T | Train in 90 days | H100 vs GB200 NVL72

  17. Slide 17: NVIDIA NVLink Enables New Level of AI Training & Inference Scaling

    NVIDIA NVLink Enables New Level of AI Training & Inference Scaling NVLink Switch GB200 NVL72 NVLink Switches 130 TB/s All-to-All BW One Giant Blackwell 1.44 EF FP4 576TB/s HBM3e 17

  18. Slide 18: NVIDIA Addresses The Entire AI Market

    NVIDIA Addresses The Entire AI Market NVIDIA’s accelerated computing platform encompasses a complete computing stack and infrastructure required for customers to build and run AI at scale. CUDA-X libraries and microservices leverage the programmability of CUDA to enable thousands of applications acr

  19. Slide 19: NVIDIA AI Platform and Ecosystem Reaches Every Market

    NVIDIA AI Platform and Ecosystem Reaches Every Market Accelerate Every Workload Full-Stack, Entire AI Infrastructure Every Workload to Address the World's Industries Data Post Pre- Training Agentic AI Robotic AI Training Inference Inference Processing e.g., SDG Heavy Social Media Industries Platform

  20. Slide 20: AI Driving Investment Cycle and Significant Returns

    AI Driving Investment Cycle and Significant Returns AI is accelerating scientific discovery, creativity, and productivity across industries AI Agents & Copilots Search & Social Media AI Content Creation AI Agents, or copilots and AI teammates, automate tasks at superhuman Over 1B $700B in 50M creato

  21. Slide 21: The Enterprise and Industrial AI Wave of Adoption Has Started

    The Enterprise and Industrial AI Wave of Adoption Has Started AI brings computing into the core of the $100T global industries. Companies will leverage AI to unlock new monetizable applications, enhance employee productivity, and transform their business models. NVIDIA AI Enterprise platform, which

  22. Slide 22: Enterprise AI Wave is Here

    Enterprise AI Wave is Here Co-Pilots, AI Teammates, and Agents are the New Digital Workforce to Revolution Enterprise Productivity This is Mayfield’s webpage of AI companies in their portfolio. The illustration and description provide a framework of enterprise AI – agents are a new digital workforce

  23. Slide 23: NVIDIA AI Enterprise Enables IT Ecosystem with State-of-the-Art AI Models

    NVIDIA AI Enterprise Enables IT Ecosystem with State-of-the-Art AI Models and Libraries to Build Agentic AI NVIDIA AI Enterprise Ecosystem System Integrators User ... AI Agent Enterprise ISVs ... Database Data Platforms Action NVIDIA NIM NVIDIA NeMo Retriever ... Vector Database Data Cloud and On-Pr

  24. Slide 24: NVIDIA Omniverse and AI Revolutionizing Manufacturing & Robotics

    NVIDIA Omniverse and AI Revolutionizing Manufacturing & Robotics 100M Cars Billions in Future The next AI wave is physical AI - models that can perceive, understand, and interact with the physical world. Physical AI will embody robotic systems – from autonomous vehicles to industrial robots and huma

  25. Slide 25: Sovereign AI

    Sovereign AI Nations produce AI using their own data, infrastructure, workforce, and business networks Sovereign AI Nations are awakening to the imperative to produce artificial intelligence using their own infrastructure, data, workforces and business networks. Nations are building domestic computi

  26. Slide 26: Driving Strong and Profitable Growth

    Driving Strong and Profitable Growth Revenue ($M) Operating Income ($M) $37,997 Operating Margin % $37,134 $60,922 68% 61% $56,084 $26,914 $26,974 $12,690 $6,803 $9,040 $16,675 $3,735 47% 34% $10,918 34% 41% FY20 FY21 FY22 FY23 FY24 H1 FY25 FY20 FY21 FY22 FY23 FY24 H1 FY25 Non-GAAP Fiscal year ends

  27. Slide 27: Strong Cash Flow Generation

    Strong Cash Flow Generation Free Cash Flow Capital Allocation (Non-GAAP) $26.9B $28.4B Share Repurchase • Utilized $14.9B of cash for repurchases in H1 FY25 • Additional $50B in stock repurchase authorization, adding to $7.5B which remained as of the end of Q2 Dividend • $344M in H1 FY25 • Dividend

  28. Slide 28: Our Market Platforms at a Glance

    Our Market Platforms at a Glance Data Center Gaming Professional Visualization Automotive 78% of FY24 Revenue 17% of FY24 Revenue 3% of FY24 Revenue 2% of FY24 Revenue FY24 Revenue $47.5B FY24 Revenue $10.4B FY24 Revenue $1.6B FY24 Revenue $1.1B 5-YR CAGR 75% 5-YR CAGR 11% 5-YR CAGR 7% 5-YR CAGR 11%

  29. Slide 29: Reconciliation of Non-GAAP to GAAP Financial Measures

    Reconciliation of Non-GAAP to GAAP Financial Measures 29

  30. Slide 30: Reconciliation of Non-GAAP to GAAP Financial Measures

    Reconciliation of Non-GAAP to GAAP Financial Measures Operating Income Acquisition-Related Stock-Based and Margin Acquisition Termination Other Non-GAAP and Other Costs Compensation GAAP ($ in Millions & Cost (C) (A) (B) Margin Percentage) $3,735 — (31) (844) (14) $2,846 FY 2020 34.2% — (0.3) (7.7)

  31. Slide 31: Reconciliation of Non-GAAP to GAAP Financial Measures

    Reconciliation of Non-GAAP to GAAP Financial Measures Purchases Related to Property Principal Payments Net Cash ($ in Millions) Free Cash Flow and Equipment on Property Provided by and Intangible Assets and Equipment and Intangible Assets Operating Activities FY 2020 $4,272 489 — $4,761 FY 2021 $4,6

  32. Slide 32: NVIDIA

    NVIDIA.

NVIDIA — Investor Presentation (October 2024) on 6ix