WELCOME. Simona Jankowski, March 27, 2018

Transcription

1 WELCOME Simona Jankowski, March 27,

2 SAFE HARBOR Forward-Looking Statements Except for the historical information contained herein, certain matters in this presentation including, but not limited to, statements as to: our growth and growth drivers; our market opportunities and TAM; the benefits, impact, and performance of: cinematic games, autonomous vehicles, AI, and our products, technologies, services, and programs; every vehicle being autonomous; the challenges to production of AI cars; our production roadmap and schedules; esports, social, and the growth of gaming; projected three-year datacenter operating expenses; projected exaflops growth; our intended fiscal 2019 capital return; our strategies; market trends; future financial results, estimates and forecasts; and other predictions and estimates are forward-looking statements within the meaning of the Private Securities Litigation Reform Act of These forward-looking statements and any other forward-looking statements that go beyond historical facts that are made in this presentation are subject to risks and uncertainties that may cause actual results to differ materially. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing products and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences and demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems and other factors. For a complete discussion of factors that could materially affect our financial results and operations, please refer to the reports we file from time to time with the SEC, including our Form 10-K for the fiscal period ended January 28,. Copies of reports we file with the SEC are posted on our website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of March 27,, based on information currently available to us. Except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. Financial Measures This presentation contains historical revenue amounts for certain of our market platforms and businesses which provides investors with additional information to supplement the segment reporting information contained in our Form 10-K for the fiscal year ended January 28,. In addition to U.S. GAAP financials, this presentation includes certain non-gaap financial measures. These non-gaap financial measures are in addition to, and not a substitute for or superior to, measures of financial performance prepared in accordance with U.S. GAAP. See our website for a reconciliation between each non-gaap measure and the most comparable GAAP measure. Where we present non-gaap financial measures, including non-gaap gross margin, non-gaap gross margin without IP, non-gaap operating expense, non-gaap operating income, non-gaap operating margin, non-gaap EPS, and free cash flow we generally exclude stock-based compensation, legal settlement, acquisition-related items, restructuring and other charges, product warranty charge, the associated tax impact, provisional tax benefit from tax reform, and other expense, where applicable.

3 AGENDA Rise of GPU Computing Datacenter Automotive Gaming Financials Q&A Jensen Huang Shanker Trivedi Rob Csongor Jeff Fisher Colette Kress All Questions? Please

4 NVIDIA Jensen Huang, CEO

5 THE MOST EXCITING TIME IN TECH HISTORY GAMING PRO VIZ DATACENTER AUTONOMOUS VEHICLES NVIDIA GPU

6 DATACENTER Shanker Trivedi, March 27,

7 : A GREAT YEAR $M DATACENTER REVENUE $1,932M HIGHLIGHTS Volta chosen by all major server OEM/ODMs and all major public clouds $339M 145% $830M 133% 2,000 customers adopt NVIDIA inference platform 86 of Top 500 Supercomputers NVIDIA Tesla Accelerated Top 15 HPC Apps Accelerated; 550 accelerated apps CUDA developers up 75% YoY to 770K Source: NVIDIA FY 2016 FY 2017 FY

8 BIG GROWTH OPPORTUNITY $50B Total Addressable Market (TAM) HIGH PERFORMANCE COMPUTING HYPERSCALE & CONSUMER INTERNET CLOUD COMPUTING & INDUSTRIES $10B $20B $20B Source: NVIDIA

9 NVIDIA DATACENTER STRATEGY DEVELOPERS NVIDIA PLATFORM EVERY MAJOR CLOUD EVERY MAJOR COMPUTER MAKER TOP 15 HPC AMBER ANSYS ANSYS FLUENT BLAST GAMESS Gaussian GROMACS LAMMPS LS-DYNA NAMD OpenFOAM Quantum Espresso Simula Abaqus VASP WRF AI FRAMEWORKS DATA ANALYTICS H20 Kinetica MapD MatLab ENTERPRISE Adobe ANSYS Dassault GE IBM SAP SAS Schlumberger DEVELOPERS APPS & FRAMEWORKS VERTICAL SOLUTIONS SOFTWARE TESLA, DGX GPU & CUDA USERS Source: NVIDIA

10 DATACENTER PLATFORM APPLICATIONS HPC FRAMEWORKS ENTERPRISE DATA ANALYTICS VISUALIZATION INDUSTRY VERTICAL SOLUTIONS NVIDIA GPU CLOUD NVIDIA AI DRIVE: AUTONOMOUS VEHICLES METROPOLIS: SMART CITIES CLARA: HEALTHCARE SOFTWARE, SDKS, ENGINES, LIBRARIES, OS DEEP LEARNING HIGH PERFORMANCE COMPUTING DATA CENTER MGMT cudnn TensorRT DeepStream cublas cusparse cufft OpenACC vgpu DCGM KONG* TESLA DGX CUDA & GPU COMPUTING ARCHITECTURE *Kubernetes on NVIDIA GPUs

11 DEVELOPER ECOSYSTEM HIGH PERFORMANCE COMPUTING Accelerated Computing Developers HYPERSCALE & CONSUMER INTERNET Training cudnn (Downloads) CLOUD COMPUTING & INDUSTRIES Inception Startups (Companies) 75% 350K 200% 840K 133% 2, K 280K 1,200 FY17 FY18 FY17 FY18 FY17 FY18 GPU Ready Apps (Units) % 550+ Inferencing TRT (Downloads) 30K 70 Enterprise DGX Customers 340% FY17 FY18 FY17 FY18 FY17 FY18 Mainstream Adoption AI Leadership Rapid Growth Source: NVIDIA

12 GPU ACCELERATED DATACENTER VALUE The More You Buy, the More You Save WORKLOAD BASELINE CPU-Only HPC (Amber, LAMMPS, NAMD, VASP) AI TRAINING (Caffe2, TensorFlow, MXNet) AI INFERENCE (Image, Speech, Translation) Speed Up 1X 20X >100X 60X Servers 5, <50 84 Capex $45M $11M $7.5M $7M 3 Year Opex (Power + Cooling) $19.5M $2.5M $1M $1.5M TCO Savings N/A 79% 86% 86% Source: NVIDIA Note(s): CPU Baselined to 5000 Servers for each workload Capex Costs: CPU node with 2x Skylake CPU s ~$9K; GPU node with 4x V100 GPU s ~$45K Opex Costs: Power & cooling is $180/kW/month Power: CPU server + n/w = 0.6 KW; GPU server + n/w = 1.6 KW; DGX-1V/HGX-1 Server = 3.2KW HPC: GPU node with 4xV100 compared to 2xCPU Server DL Training: DGX-1V compared to a 2xCPU server DL Inference: HGX-1 based server (8xV100) Compared to 2x CPU Server numbers rounded to nearest $0.5M

13 HIGH PERFORMANCE COMPUTING To Exascale, and Beyond $10B TAM LEADERSHIP MILESTONES EXAPLOPS Top 500 Rest of HPC Top 500 Systems accelerated, 86 NVIDIA systems Public sector investment in AI and exascale Top 15 apps, 70% of top 50 HPC apps accelerated; total 550 2,328 scientific computing papers citing GPUs compared to 1,276 in FY17 Source: NVIDIA, arxiv, PubMed

14 HYPERSCALE & CONSUMER INTERNET AI Powers Consumer Apps $20B TAM APPLICATIONS LEADERSHIP EXAFLOPS Training Inference RECOMMENDATION ENGINE CREDIT SCORING FRAUD DETECTION AD INSERTION AI ASSISTANT EIOPs Source: NVIDIA SPEECH VIDEO IMAGE LANGUAGE

15 HYPERSCALE & CONSUMER INTERNET GPUs Best for Deep Learning Training Increasing Complexity of DNNs Top 10 Hyperscale/Consumer Internet 2 ExaFLOPS FY 16 FY FY Source: NVIDIA

16 HYPERSCALE & CONSUMER INTERNET AI Inferencing is a Large Opportunity: 30M+ Hyperscale Servers AI inference opportunity 30M Hyperscale Servers TensorRT 4 TensorRT 3 Tensor Core TensorFlow Integration Kaldi Optimization TensorRT CNNs TensorRT 2 INT8 ONNX WinML Sep 16 April 16 Sep 17 April X IMAGE - CNN ResNet-50 with TensorFlow Integration 50X NLP - RNN GNMT 45X RECOMMENDER - MLP Neural Collaborative Filtering 36X SPEECH SYNTH - DGN WaveNet 60X SPEECH RECOG RNN++ Deep Speech 2 DNN Source: NVIDIA

17 CLOUD COMPUTING & INDUSTRIES AI Transforming Every Industry $20B TAM LEADERSHIP MILESTONES Startups Industry Breakdown Healthcare Volta chosen by all major public clouds Future Industries Transportation Manufacturing Public Sector $5B in funding for 2,800 NVIDIA Inception Startups Top segments include: Healthcare, Transportation, AI City Over 2,000 companies using NVIDIA GPU Cloud (NGC) Oil & Gas Source: NVIDIA

18 AI REVOLUTIONIZING MEDICAL IMAGING $100B Market: $35B Instruments, $5B Imaging Software RESEARCH STARTUPS COMPANIES 60% 50% 40% 30% 20% 10% 0% Medical Imaging Papers Using Deep Learning SPIE ISBI MICCAI $800 $600 $400 $200 $- Healthcare AI Financing History H H Disclosed Funding ($M) Deals 300 NVIDIA Inception Members FDA approved AI for Medical Imaging Dedicated supercomputer for AI Pathology Source: NVIDIA, CB Insights

19 AV DATACENTER OPPORTUNITY Data Factory Training on DGX 3D-SIM on DRIVE CONSTELLATION DRIVE AV on DPX RE-SIM on DGX 1+ petabyte per car per year 10+ DNNs, 1+ million images per DNN 10B+ miles to ensure safe driving Self driving cars by petaflops for every paved road in the US in 1 day Sources: NVIDIA, RAND Corporation

20 DATA CENTER SUMMARY $50B TAM Compelling platform strategy Leadership in HPC and deep learning training Large AI inference opportunity Increasing enterprise adoption HIGH PERFORMANCE COMPUTING $10B HYPERSCALE & CONSUMER INTERNET $20B CLOUD COMPUTING & INDUSTRIES $20B Growing developer ecosystem Extensible flexible architecture Source: NVIDIA

21 AUTOMOTIVE Rob Csongor March 27,

22 AUTOMOTIVE GROWTH REVENUE DRIVE PARTNERS AI ENGAGEMENTS % $558M DPX2 DX Millions FY14 FY15 FY16 FY17 FY18 0 FY17Q2 FY17Q3 FY17Q4 FY18Q1 FY18Q2 FY18Q3 FY18Q4 Current 0 FY17Q1 FY17Q2 FY17Q3 FY17Q4 FY18Q1 FY18Q2 FY18Q3 FY18Q4

23 AV REVOLUTIONIZING $10T INDUSTRY Every Vehicle Will Be Autonomous DRIVING MOBILITY SERVICES TRUCKING $2.4T MARKET AV will save lives, $Ms in lost productivity (3000 lives/day, $0.5T/yr) $5.3T MARKET AV will reduce parking footprint, lowering cost of ownership $2T MARKET AV will extend the range of truckers, help cover shortage of trucker. (10% decline from ELD, $500B loss due to accidents)

24 AV IS A $60B OPPORTUNITY Every Vehicle Will Be Autonomous 120M vehicles $60B TAM (2035) AV REVENUE 10M Robotaxis $20B Development DRIVE Systems Development NRE Training, testing & validation systems L2 L5 Shipments 100M SDC $40B L5 Robo-taxi L4 Full AV L3 Partial AV L2 Human backup Source: ABI Research

25 THE CHALLENGE AUTOMAKERS FACE PROCESSING REQS Up to 100s of TOPs, 10s of TFLOPs, 1000s of KDMIPs POWER, COST Up to 1000s of Watts, 10000s of $ TESTING, VALIDATION Up to 100s of billions of driving miles, 100s of years

26 NVIDIA GAME CHANGERS Key Strategies AI XAVIER PROCESSOR NVIDIA DRIVE END-TO-END SYSTEM OPEN PLATFORM The Computing Model for AV One Architecture From L2 to L5 Collect Data Train Models Simulate Drive 370+ Partner Ecosystem

27 ONE SCALABLE ARCHITECTURE L2 through L5 Driving Solutions ONE SW ARCHITECTURE ORIN DRIVE Parker DRIVE PX 2 DRIVE Xavier DRIVE Pegasus DRIVE Orin 1x Perf 20x Perf 20x Perf 200x Perf 200x Perf 1 Chip 4 chips 1 chip 4 chips 2 chips Samples: Now Samples: Now Samples: Now Samples: Q3 Production: Now Production: Now Production: Q Production: Q3 2019

28 DRIVE AV ON XAVIER

29 TODAY S ADAS Four Separate Computers Side Surround Camera Side Radar Front Surround Camera Front Radar NCAP Camera NCAP ECU Surround View ECU Parking ECU Driving Monitor ECU Rear Radar Rear Surround Camera Forward Camera L2 ECU Side Radar Driving Monitor Camera Side Surround Camera

30 DRIVE XAVIER VALUE One Computer One SW, Lower Cost Side Surround Camera Side Radar Front Surround Camera Front Radar NCAP Camera NCAP ECU Rear Radar Rear Surround Camera Forward Camera One AI AV Computer Side Radar Driving Monitor Camera Side Surround Camera

31 ROBO TAXI DRIVE VALUE

32 ROBO TAXI DRIVE VALUE

33 ROBO TAXI DRIVE VALUE L5 ROBO-TAXI USE CASE 2x PCs in the Trunk 2x DRIVE PEGASUS TOPs KDMIPs GFLOPs 39,000 38,000 Power 3 kw 1/3 rd pwr Size 1x 1/10 th size Cost 1x 1/5 th cost

34 END-TO-END SYSTEM From Training to Testing to Driving Data Factory Training on DGX 3D-SIM on DRIVE CONSTELLATION DRIVE AV on DPX RE-SIM on DGX 1+ petabyte per car per year 10+ DNNs, 1+ million images per DNN 10B+ miles to ensure safe driving Self driving cars by petaflops for every paved road in the US in 1 day Sources: NVIDIA, RAND Corporation

35 ANNOUNCING NVIDIA DRIVE SIM AND CONSTELLATION AV VALIDATION SYSTEM Virtual Reality AV Simulator Same Architecture as DRIVE Computer HIL and PIL Support Simulate Rare and Difficult Conditions, Recreate Scenarios, Run Regression Tests, Drive Billions of Virtual Miles 10,000 DRIVE Constellations Drive 3B Miles per Year 35

36 DRIVE SIM SIMULATING VS DRIVING THE WORLD VALUE PROPOSITION Per the Rand Corporation report, to drive ten billion miles Would require 50,000 drivers, $10 billion dollar cost over 3 years The same task using DRIVE Constellations would take 7 months, at a fraction of the cost.

37 CARS THE POWER OF AN OPEN PLATFORM 370+ PARTNERS DEVELOPING ON NVIDIA DRIVE TRUCKS MOBILITY SERVICES SUPPLIERS MAPPING SENSORS STARTUPS RESEARCH

38 KEY ANNOUNCEMENTS Progress This Year XAVIER IS HERE DRIVE PEGASUS VW AI BAIDU APOLLO AUDI DEPLOYS ZFAS MERCEDES-BENZ AI DRIVE SIM DRIVE AV VOLVO / AUTOLIV AURORA CONTINENTAL DEUTSCHE POST DHL DRIVE IX DRIVE AR ZF / CHERY UBER TUSIMPLE PACCAR PRODUCTS PARTNERS

39 SUMMARY Every vehicle will be autonomous $60B opportunity $0.5B business transitioning to AV Revenue NVIDIA s coming Key from Strategies development systems, NRE, AI, Xavier, simulating/testing/training End to End System, systems Open Platform are game changers for car Every makers vehicle will be autonomous - $60B TAM opportunity by Testing & validation for AV Announcing NVIDIA s DRIVE Key Strategies Constellation - AI, Xavier, end to end AI Validation system, open in the platform Data are Center game changer strategies for NVIDIA. The world is building on NVIDIA s open platform Moment 370+ partners and growing 39

40 GAMING Jeff Fisher, March 27,

41 GAMING HAD A GREAT YEAR Pascal:1080Ti/1070Ti/Titan Xp Max-Q Gaming Notebooks Nintendo Switch Powered by NV Surpassed 100M GFE Clients GFN Beta Launched $6,000 $5,000 $4,000 $3,000 $2,000 $1,000 TOTAL GAMING $M 36% YOY Crypto Came to Town $0 FY17 FY18

42 GAMING IS A HUGE MARKET AND GROWING WW GAME REVENUE 2500 WW GAMERS GAMERS FOR LIFE $100B ,000M 2003 Game Revenue $80B $60B $40B $20B 3X Gamers ,500M ,000M M M 3X 2017 Emerging $B Less Than 35 Yrs Old Over 35 Yrs Old Source: DFC Source: DFC (2007), NewZoo (2017) Source: ESA

43 PC IS WHERE THE ACTION IS OPEN PLATFORM DEVELOPERS CHOOSE PC 1000s of GAMES RECORD BREAKING SALES 60% 8000 MOST WATCHED..EVER Game Developers Surveyed on Games in Development 50% 40% 30% 20% 10% Games Released on Steam Each Yr % PC Phone Console PS4 Source: Steam, Twitchstats, SteamSpy, BlueHole Source: GDC Annual Survey Source: Statista, SteamSpy, GameStop

44 GEFORCE: WORLD S LARGEST GAMING PLATFORM GAMING GPU REVENUE $M 5Yr CAGR INSTALLED BASE LEADERSHIP $5B $4B 21% YOY REV 29% ASP 11% 30% Steam Gamers $3B UNITS 15% $2B END MARKET 70% VR $1B $B FY17 FY18 Developed +27% Emerging +40% Pascal Other GeForce Other Source: NVIDIA Source: NVIDIA Source: NVIDIA Source: Steam, Oculus

45 ESPORTS MOMENTUM FUELS GAMING ESPORTS AUDIENCE PRIZE MONEY 40M 400M $120M 30M esports Viewers 350M 300M 250M 200M 150M 100M 50M M 2016 Total esports Tournament Prize Money $100M $80M $60M $40M $20M $M +70% WW Gamers WW Gamers 20M 10M M 100M 75M 50M 25M 5/16 8/16 10/16 1/17 4/17 10/17 86% OF ESPORTS GAMERS PLAY ON GEFORCE M Source: NewZoo, esportsearnings.com, NewZoo discrete GPU share of esports gamers Source: Statista, Blizzard & Riot Games

46 SOCIAL EXPANDS GAMING REACH GAMES WANT TO SHARE GAMERS WANT TO CONNECT MOST VIEWED, MOST SHARED GO VIRAL Twitch Concurrent Viewers Discord App User Growth GeForce Weekly Gamers 1.0M 0.8M 100M 80M Total Gamers Playing + 20% 0.6M 60M 0.4M 40M 0.2M 20M 0.0M Jan 16 Jan 18 CNN /17 7/17 10/17 1/18 70% OF GAMERS PLAY GAMES TO BE SOCIAL RISE OF PUBG AND FORTNITE IS GROWING THE GAMING COMMUNITY - Goldman Sachs Source: Twitchtracker, Discord, Nielsen Source: NVIDIA

47 GEFORCE EXPERIENCE GAMING PLATFORM 100M Clients WW Over 1B In-Game Captures in 2017: 800M Game Videos 200M Game Highlights 100M Game Photographs 500M so far in NVIDIA ANSEL NVIDIA HIGHLIGHTS

48 CINEMATICS KEEP PUSHING PLATFORM RAYTRACING GAMES MORE DEMANDING GAMERS BUY UP 5X $300 Console ASP $275 NVIDIA GPU New Class of Ray Traced Games Microsoft DXR NVIDIA GameWorks Ray Tracing NVIDIA RTX Technology GPU Perf Required for High Settings 4X 3X 2X 1X 0X Console Perf RTX 4K VR ASP $250 $225 $200 $175 $150 $125 $200* GeForce ASP $160* FY15 FY16 FY17 FY18 Source: NVIDIA, 1080p, High Settings * Est ASP of Graphics Card (based on Actual GPU ASP)

49 Gaming is BIG and Growing G-SYNC GeForce is Number One Game Platform Gaming Growth Fueled by Esports and Social GEFORCE EXPERIENCE Cinematic Gaming Needs Bigger GPUs An Exciting Future MAX-Q DESIGN GEFORCE GTX NVIDIA SHIELD

50 FINANCIALS Colette Kress, March 27,

51 RECORDS REVENUE GROSS MARGIN OPERATING INCOME EPS $9.7B 100 BPS 59.2% 60.2% $3.6B $ % 63% 61% $6.9B $2.2B $3.06 FY 2017 FY FY 2017 FY FY 2017 FY FY 2017 FY Gross Margin, Operating Income and EPS are Non-GAAP measures.

52 MARKET PLATFORMS GAMING 3-YEAR CAGR ~40% PRO VISUALIZATION 3-YEAR CAGR 6% $ Billions $2.1 $2.8 $4.1 36% $5.5 FY 2015 FY 2016 FY 2017 FY $ Millions 1, $795 $750 $835 12% $934 FY 2015 FY 2016 FY 2017 FY DATACENTER 3-YEAR CAGR ~85% AUTO 3-YEAR CAGR 45% $ Millions 2,000 1,500 1, $317 $339 $ % $1,932 FY 2015 FY 2016 FY 2017 FY $ Millions $183 $320 $487 15% $558 FY 2015 FY 2016 FY 2017 FY

53 GAMING GFE USERS MARKET PLATFORMS Diversified and Growing PRO VISUALIZATION EMERGING APPLICATIONS Millions M 100M 40% 30% 20% 10% 15% 30% 50 FY 2017 FY 0% Q4 FY 2017 Q4 FY DATACENTER HYPERSCALE 7 CUSTOMER REVENUE AUTOMOTIVE DRIVE PARTNERS $ Millions +155% FY 2017 FY 100 FY 2017 FY

54 GROSS MARGIN EXPANSION Value Added Platforms Expand Margins 7 6 GM% Excl IP GM% Value Added Platforms IP All Other 60.2% 64% Gross Profit, $ Billions % 56.8% 59.2% 62% 60% 58% 56% 1 54% 0 FY 2015 FY 2016 FY 2017 FY 52% Gross Margin excluding IP and Gross Margin are Non-GAAP measures.

55 GROSS MARGINS BY PLATFORMS Company GM% Gross Profit Gross Profit, $ Billions Auto OEM & Embedded GPU Gaming Pro Vis Data Center 0% 60.2% 100% FY Gross Margin % Gross Margin is a Non-GAAP measure.

56 OPERATING EXPENSES YoY Investments Focused on Gaming, AI, and Auto 3.0 Operating Expenses Operating Expenses as a % of Revenue 45% % 34% $1.9 19% $2.2 35% $ Billions 27% % 25% 0.0 $1.7 $1.7 FY 2015 FY 2016 FY 2017 FY 15% Operating Expenses and Operating Expenses as a % of Revenue are Non-GAAP measures.

57 INVESTMENT IN R&D Cumulative $15B 2.0 R&D Investment Cumulative R&D Investment 16 R&D, $ Billions Cumulative R&D, $ Billions 0.0 0

58 OUR LEVERAGED MODEL ENGINEERS BY PLATFORM FY 2013 Gaming AI Auto Software ~40% FY GPU Architecture ~50% Software Hardware FY

59 OPERATING MARGIN EXPANSION 4.0 Operating Income Operating Margin 37% 45% % 35% $ Billions % 22% $3.6 25% 1.0 $2.2 15% 0.0 $1.0 $1.1 FY 2015 FY 2016 FY 2017 FY 5% Operating Income and Operating Margin are Non-GAAP measures.

60 CASH AND CASH FLOW Cash Flow Increased 109%; Net Cash Increased 28% 8 Cash as a % of Market Capitalization $6.8 $7.1 6 $5.1 $ Billions 4 $3.5 $ % 4.8% 2 $1.7 0 FY 2017 FY FY 2017 FY FY 2017 FY Cash Flow Net Cash Total Cash Cash Flow = Cash Flow from Operations; Net Cash = Total Cash Total Debt; FY 2017 Total Debt = $2.8B; FY Total Debt = $2.0B; Total Cash = Cash, Cash Equivalents + Marketable Securities

61 CAPITAL RETURN Since FY 2013: $5B+, 70% FCF 1,600 Share Repurchase Dividend Intended Return 1,200 $1.1B $1.0B $1.0B $1.25B $1.25B $ Millions 800 $0.8B 400 $147M 0 FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 FY FY 2019 Free Cash Flow is a Non-GAAP measure.

62 USES OF CASH OPEX FY Engineers Sales Infrastructure 2.5 CAPEX Datacenters 2.0 Facilities Software license M&A and Investments Capital Return Dividends Share Repurchases $ Billions $2.2 OPEX $0.6 CAPEX M&A $1.25 CAPITAL RETURN OPEX is a Non-GAAP measure.

63 Q&A

64 SILICON VALLEY MARCH 26-29, #GTC18

65 RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES

66 RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES GROSS MARGIN ($ IN MILLIONS & MARGIN PERCENTAGE) NON-GAAP without IP IP NON-GAAP STOCK-BASED COMPENSATION (A) PRODUCT WARRANTY (B) OTHER (C) GAAP FY 2015 FY 2016 FY 2017 FY $2,367 (244) $2,611 (12) $2, % (2.2) 55.8% (0.3) 55.5% $2,602 (244) $2,846 (15) (20) $2, % (2.0) 56.8% (0.3) (0.4) 56.1% $3,844 (244) $4,088 (15) (10) $4, % (1.4) 59.2% (0.2) (0.2) 58.8% $5,821 (23) $5,844 (21) (1) $5, % 60.2% (0.3) 59.9% A. Stock-based compensation charge was allocated to cost of goods sold. B. Consists of warranty charge associated with a product recall. C. Consists of legal settlement and other related costs.

67 RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES (CONTD.) OPERATING EXPENSES ($ IN MILLIONS & % OF REVENUE) NON-GAAP STOCK-BASED COMPENSATION (A) ACQUISITION- RELATED ITEMS (B) OTHER (C) GAAP FY 2015 FY 2016 FY 2017 FY $1, $1,840 35% % $1, $2,064 34% % $1, $2,129 27% 4 31% $2, $2,612 23% 4 27% A. Stock-based compensation charge was allocated to research and development expense, and sales, general and administrative expense. B. Consists of amortization of acquisition-related intangible assets, transaction costs, compensation charges, and other credits related to acquisitions. C. Comprises of legal settlement costs, contributions, and restructuring and other charges.

68 RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES (CONTD.) OPERATING MARGIN ($ IN MILLIONS & MARGIN PERCENTAGE) NON-GAAP STOCK-BASED COMPENSATION (A) PRODUCT WARRANTY (B) ACQUISITION- RELATED ITEMS (C) OTHER (D) GAAP FY 2015 FY 2016 FY 2017 FY $954 (158) (37) $759 20% (3) (1) 16% $1,125 (205) (20) (22) (131) $747 22% (4) (3) 15% $2,221 (248) (16) (23) $1,934 32% (4) 28% $3,617 (391) (13) (3) $3,210 37% (4) 33% A. Stock-based compensation charge was allocated to cost of goods sold, research and development expense, and sales, general and administrative expense. B. Consists of warranty charge associated with a product recall. C. Consists of amortization of acquisition-related intangible assets, transaction costs, compensation charges, and other credits related to acquisitions. D. Comprises of legal settlement costs, contributions, and restructuring and other charges.

69 RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES (CONTD.) ($ IN MILLIONS, EXCEPT SHARES & EPS) NON-GAAP STOCK-BASED COMPENSATION (A) ACQUISITION- RELATED ITEMS (B) OTHER (C) TAX IMPACT OF ADJUSTMENTS PROVISIONAL TAX BENEFIT FROM INCOME TAX REFORM GAAP FY 2017 Net income $1,851 (248) (16) (65) 144 $1,666 Shares used in diluted per share calculation Diluted EPS $3.06 $2.57 FY Net income $3,085 (391) (13) (24) $3,047 Shares used in diluted per share calculation Diluted EPS $4.92 $4.82 A. Stock-based compensation charge was allocated to cost of goods sold, research and development expense, and sales, general and administrative expense. B. Consists of amortization of acquisition-related intangible assets, transaction costs, compensation charges, and other credits related to acquisitions C. Other comprises of legal settlements, contributions, restructuring and other charges, gains from non-affiliated investments, interest expense related to amortization of debt discount and loss on early debt conversions. Other also comprises anti-dilution impact from note hedge that is excluded from GAAP weighted average diluted share calculation.

70 RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES (CONTD.) ($ IN MILLIONS) FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 FY GAAP net cash flow provided by operating activities $824 $835 $905 $1,175 $1,672 $3,502 Purchase of property and equipment and intangible assets (183) (255) (122) (86) (176) (593) Free cash flow $641 $580 $783 $1,089 $1,496 $2,909