|Bid||393.10 x 1200|
|Ask||0.00 x 1100|
|Day's range||394.03 - 402.80|
|52-week range||147.39 - 402.80|
|Beta (5Y monthly)||1.34|
|PE ratio (TTM)||73.82|
|Earnings date||13 Aug 2020 - 17 Aug 2020|
|Forward dividend & yield||0.64 (0.16%)|
|Ex-dividend date||04 Jun 2020|
|1y target est||389.31|
Nvidia today announced that its new Ampere-based data center GPUs, the A100 Tensor Core GPUs, are now available in alpha on Google Cloud. Nvidia says the A100 can boost training and inference performance by over 20x compared to its predecessors (though you'll mostly see 6x or 7x improvements in most benchmarks) and tops out at about 19.5 TFLOPs in single-precision performance and 156 TFLOPs for Tensor Float 32 workloads. "Google Cloud customers often look to us to provide the latest hardware and software services to help them drive innovation on AI and scientific computing workloads," said Manish Sainani, Director of Product Management at Google Cloud, in today's announcement.
NVIDIA (NASDAQ: NVDA) announced on Tuesday that just weeks after its release, the A100 Tensor Core graphics processing unit (GPU) has been adopted by Google Cloud, a division of Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG). The Accelerator-Optimized VM (A2) family, available on Google Compute Engine, is designed specifically to handle some of the most demanding applications out there, including artificial intelligence (AI) workloads and high performance computing (HPC). This makes Google the first cloud service provider to offer the new NVIDIA GPUs.
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Artificial intelligence (AI) is likewise an important but oft-misunderstood technology. Last month, I talked up Alphabet, salesforce.com, and NVIDIA (NASDAQ: NVDA). When talking about AI hardware, it's easy to default to NVIDIA.
NVIDIA (NASDAQ: NVDA) has a record of outstanding growth, and with its share price close to all-time highs, some investors may be thinking it is already too late to get in. The company's core business is divided into four segments: gaming, data center, professional visualization, and automotive. All are high performers in their fields, providing NVIDIA with a strong, diversified business.
The months leading up to the U.S. presidential election in November will be choppy, especially if Democrat Joe Biden extends his poll lead. The EU needs to agree on a $750 billion recovery fund proposal. A wave of foreign money has hit mainland China's markets as the second half of 2020 kicks in.
NVIDIA (NASDAQ: NVDA) stock rocketed 61.5% higher in the first half of 2020 (January through June), according to data from S&P Global Market Intelligence. Management issued an upbeat outlook in February, when the company released its results for the fourth quarter of fiscal 2020. The bottom-line performance was even better.
NVIDIA (NASDAQ: NVDA) and the Mercedes-Benz division of Daimler AG (OTC: DMLRY) (OTC: DDAIF) are teaming up to truly build a computer on wheels. The two companies recently announced a collaboration to build a new computing system for cars, powered by NVIDIA's DRIVE AGX Orin technology. This new high-performance car computer will be used in new vehicles from Mercedes-Benz starting in 2024.
It's been over a decade since AMD (NASDAQ: AMD) spun off its semiconductor manufacturing segment, the company now known as GlobalFoundries. During the depths of the Great Recession, the deal was deemed necessary to help AMD survive, although AMD maintained the long-term vision was to refocus on technology, chip design, and better investment returns.
A handful of corporate behemoths has skyrocketed YTD. Some of these stocks carry a favorable Zacks Rank and have rallied more than 20% YTD.
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Advanced Micro Devices (NASDAQ: AMD) took NVIDIA (NASDAQ: NVDA) by storm in the first calendar quarter of 2020, clocking nice market share growth in the discrete graphics cards space thanks to a couple of solid products that were launched last year.
Nvidia (NVDA) closed the most recent trading day at $368, moving +0.49% from the previous trading session.
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Autonomous driving gains steam owing to breakthroughs in technology, with the integration of robust AI and ML capabilities in advanced driver-assistance systems.