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NVIDIA Announces Financial Results for Second Quarter Fiscal…

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And still going strong, NVIDIA reported revenue for the second quarter ended July 30, 2017, of $2.23 billion. That would be up 56 percent from $1.43 billion a year earlier, and up 15 percent from $1.94 billion in the previous quarter.

Adoption of NVIDIA GPU computing is accelerating, driving growth across our businesses,” said Jensen Huang, founder and chief executive officer of NVIDIA. “Datacenter revenue increased more than two and a half times. A growing number of car and robot-taxi companies are choosing our DRIVE PX self-driving computing platform. And in Gaming, increasingly the world’s most popular form of entertainment, we power the fastest growing platforms – GeForce and Nintendo Switch.

  • Record revenue of $2.23 billion, up 56 percent from a year ago
  • GAAP EPS of $0.92, up 124 percent from a year ago
  • Non-GAAP EPS of $1.01, up 91 percent from a year ago
  • Broad growth across all platforms
  • GAAP earnings per diluted share for the quarter were $0.92, up 124 percent from $0.41 a year ago and up 16 percent from $0.79 in the previous quarter. Non-GAAP earnings per diluted share were $1.01, up 91 percent from $0.53 a year earlier and up 19 percent from $0.85 in the previous quarter.

“Nearly every industry and company is awakening to the power of AI. Our new Volta GPU, the most complex processor ever built, delivers a 100-fold speedup for deep learning beyond our best GPU of four years ago. This quarter, we shipped Volta in volume to leading AI customers. This is the era of AI, and the NVIDIA GPU has become its brain. We have incredible opportunities ahead of us,” he said.

 
GAAP
($ in millions except earnings per share)   Q2 FY18   Q1 FY18   Q2 FY17   Q/Q   Y/Y
Revenue   $2,230   $1,937   $1,428   Up 15%   Up 56%
Gross margin   58.4%   59.4%   57.9%   Down 100 bps   Up 50 bps
Operating expenses   $614   $596   $509   Up 3%   Up 21%
Operating income   $688   $554   $317   Up 24%   Up 117%
Net income   $583   $507   $261   Up 15%   Up 123%
Diluted earnings per share   $0.92   $0.79   $0.41   Up 16%   Up 124%
                     
 
Non-GAAP
($ in millions except earnings per share)   Q2 FY18   Q1 FY18   Q2 FY17   Q/Q   Y/Y
Revenue   $2,230   $1,937   $1,428   Up 15%   Up 56%
Gross margin   58.6%   59.6%   58.1%   Down 100 bps   Up 50 bps
Operating expenses   $533   $517   $448   Up 3%   Up 19%
Operating income   $773   $637   $382   Up 21%   Up 102%
Net income   $638   $533   $313   Up 20%   Up 104%
Diluted earnings per share   $1.01   $0.85   $0.53   Up 19%   Up 91%
                     

Capital Return
During the first half of fiscal 2018, NVIDIA paid $758 million in share repurchases and $166 million in cash dividends. For fiscal 2018, NVIDIA intends to return $1.25 billion to shareholders through ongoing quarterly cash dividends and share repurchases.NVIDIA will pay its next quarterly cash dividend of $0.14 per share on September 18, 2017, to all shareholders of record on August 24, 2017.

NVIDIA’s outlook for the third quarter of fiscal 2018 is as follows:

  • Revenue is expected to be $2.35 billion, plus or minus two percent.
  • GAAP and non-GAAP gross margins are expected to be 58.6 percent and 58.8 percent, respectively, plus or minus 50 basis points.
  • GAAP operating expenses are expected to be approximately $672 million. Non-GAAP operating expenses are expected to be approximately $570 million.
  • GAAP other income and expense is expected to be an expense of approximately $2 million, inclusive of additional charges from early conversions of convertible notes. Non-GAAP other income and expense is expected to be nominal.
  • GAAP and non-GAAP tax rates are both expected to be 17 percent, plus or minus one percent, excluding any discrete items. GAAP discrete items include excess tax benefits or deficiencies related to stock-based compensation, which we expect to generate variability on a quarter by quarter basis.
  • Capital expenditures are expected to be approximately $65 million to $75 million.

Second Quarter Fiscal 2018 Highlights

Datacenter:

  • Announced and began shipping NVIDIA Tesla V100 GPU accelerators, the first GPU based on the new Volta architecture.
  • Unveiled new lineup of NVIDIA DGX AI supercomputers, with a large installation at Facebook.
  • Announced the NVIDIA GPU Cloud Platform, giving developers a comprehensive software suite for AI development.
  • Disclosed that the world’s 13 most energy-efficient supercomputers on the Green 500 list run on NVIDIA Tesla accelerators.
  • Announced partnerships with VW and Baidu to bring AI deeper into their organizations.

Gaming:

  • Introduced Max-Q, a design approach to make gaming laptops thinner, quieter and faster.
  • Collaborated with Activision and Bungie to bring Destiny 2 to the PC for the first time.
  • Expanded GeForce Experience to China, at the ChinaJoy gaming conference.

Professional Visualization:

  • Introduced Project Holodeck, a photorealistic, collaborative VR environment.
  • Announced steps to bring AI to ray tracing to advance the iterative design process, including the launch of NVIDIA OptiX 5.0 SDK.
  • Launched NVIDIA TITAN X and NVIDIA Quadro external GPU support for the 25 million creative professionals using thin and light notebooks.
  • Released the NVIDIA VRWorks 360 Video SDK, which enables high-quality, 360-degree live stereo streaming.

Automotive:

  • Toyota selected NVIDIA DRIVE PX for its next-generation autonomous cars.
  • Volvo and Autoliv selected DRIVE PX for self-driving cars targeted to hit the market by 2021.
  • ZF and HELLA, two leading automotive suppliers, announced a system based on DRIVE PX to deliver the highest NCAP safety ratings for cars.
  • Baidu announced that its Project Apollo open-source self-driving platform for the China market will use DRIVE PX.

Edge Computing:

  • Introduced the NVIDIA Isaac robot simulator for training intelligent machines in simulated real-world conditions before deployment.
  • Announced the NVIDIA Metropolis platform, used by more than 50 partners to make cities safer and smarter by applying deep learning to video streams.

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