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Nvidia Corporation ( ; more commonly referred to as Nvidia, stylized as NVIDIA, or, due to their logo, nVIDIA) is an American technology company incorporated in and based in Santa Clara, . It designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the and automotive market. Its primary GPU product line, labeled "", is in direct competition with Advanced Micro Devices' (AMD) "" products. Nvidia expanded its presence in the gaming industry with its handheld , and Shield Android TV.

Since 2014, Nvidia has shifted to become a platform company focused on four marketsgaming, professional visualization, data centers and auto. Nvidia is also now focused on artificial intelligence.

In addition to GPU manufacturing, Nvidia provides parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications. They are deployed in sites around the world. More recently, it has moved into the market, where it produces mobile processors for smartphones and tablets as well as vehicle navigation and entertainment systems. In addition to , its competitors include , and (e.g., because of , while Nvidia also licenses Arm's designs).


Company history
In the early 1990s, the three co-founders hypothesized that the proper direction for the next wave of computing would be accelerated or graphics based. They believed that this model of computing could solve problems that general-purpose computing fundamentally couldn't. They also observed that video games were some of the most computationally challenging problems, but would have incredibly high sales volume. With a capital of $40,000, the company was born. The company initially had no name and the co-founders named all their files NV, as in "next version". The need to incorporate the company prompted the co-founders to review all words with those two letters, leading them to "", the Latin word for "envy".


Founders and initial investment
Three people co-founded Nvidia in April 1993:

  • (CEO ), a Taiwanese American, previously director of CoreWare at and a designer at Advanced Micro Devices (AMD)
  • Chris Malachowsky, an electrical engineer who worked at
  • , previously a senior staff engineer and graphics chip designer at Sun Microsystems

The company received $20 million of venture capital funding from and others.


Major releases and acquisitions
The release of the in 1998 solidified Nvidia's reputation for developing capable graphics adapters. In late 1999, Nvidia released the GeForce 256 (NV10), most notably introducing on-board transformation and lighting (T&L) to consumer-level 3D hardware. Running at 120 MHz and featuring four pixel pipelines, it implemented advanced video acceleration, motion compensation and hardware sub-picture alpha blending. The GeForce outperformed existing products by a wide margin.

Due to the success of its products, Nvidia won the contract to develop the graphics hardware for 's Xbox game console, which earned Nvidia a $200 million advance. However, the project took many of its best engineers away from other projects. In the short term this did not matter, and the GeForce2 GTS shipped in the summer of 2000. In December 2000, Nvidia reached an agreement to acquire the intellectual assets of its one-time rival 3dfx, a pioneer in consumer 3D graphics technology leading the field from mid 1990s until 2000. The acquisition process was finalized in April 2002.

In July 2002, Nvidia acquired Exluna for an undisclosed sum. Exluna made software rendering tools and the personnel were merged into the Cg project.Because of the closed nature of the drivers, Nvidia video cards cannot deliver adequate features on some platforms and architectures given that the company only provides x86/x64 and ARMv7-A driver builds.58 As a result, support for 3D graphics acceleration In August 2003, Nvidia acquired MediaQ for approximately US$70 million. On April 22, 2004, Nvidia acquired iReady, also a provider of high performance TCP/IP and iSCSI offload . In December 2004, it was announced that Nvidia would assist with the design of the graphics processor (RSX) in the PlayStation 3 game console. In May 2005, Microsoft chose to license a design by ATI and to make its own manufacturing arrangements for the Xbox 360 graphics hardware, as had for the console (which succeeded the ATI-based Nintendo GameCube).

On December 14, 2005, Nvidia acquired ULI Electronics, which at the time supplied third-party southbridge parts for to , Nvidia's competitor. In March 2006, Nvidia acquired . In December 2006, Nvidia, along with its main rival in the graphics industry AMD (which had acquired ATI), received subpoenas from the U.S. Department of Justice regarding possible antitrust violations in the graphics card industry.

named Nvidia its Company of the Year for 2007, citing the accomplishments it made during the said period as well as during the previous five years. On January 5, 2007, Nvidia announced that it had completed the acquisition of , Inc. In February 2008, Nvidia acquired , developer of the and physics processing unit. Nvidia announced that it planned to integrate the PhysX technology into its future GPU products.

In July 2008, Nvidia took a write-down of approximately $200 million on its first-quarter revenue, after reporting that certain mobile chipsets and GPUs produced by the company had "abnormal failure rates" due to manufacturing defects. Nvidia, however, did not reveal the affected products. In September 2008, Nvidia became the subject of a class action lawsuit over the defects, claiming that the faulty GPUs had been incorporated into certain laptop models manufactured by Apple Inc., , and . In September 2010, Nvidia reached a settlement, in which it would reimburse owners of the affected laptops for repairs or, in some cases, replacement.

On January 10, 2011, Nvidia signed a six-year, $1.5 billion cross-licensing agreement with Intel, ending all litigation between the two companies. In November 2011, after initially unveiling it at Mobile World Congress, Nvidia released its Tegra 3 for mobile devices. Nvidia claimed that the chip featured the first-ever quad-core mobile CPU. In May 2011, it was announced that Nvidia had agreed to acquire , a baseband chip making company in the UK, for $367 million. In January 2013, Nvidia unveiled the Tegra 4, as well as the , an Android-based handheld game console powered by the new system-on-chip. On July 29, 2013, Nvidia announced that they acquired PGI from STMicroelectronics.

On May 6, 2016, Nvidia unveiled the first GeForce 10 series GPUs, the GTX 1080 and 1070, based on the company's new Pascal microarchitecture. Nvidia claimed that both models outperformed its Maxwell-based Titan X model; the models incorporate GDDR5X and GDDR5 memory respectively, and use a 16 nm manufacturing process. The architecture also supports a new hardware feature known as simultaneous multi-projection (SMP), which is designed to improve the quality of multi-monitor and rendering. Laptops that include these GPUs and are sufficiently thin – as of late 2017, under  – have been designated as meeting Nvidia's "Max-Q" design standard.

In July 2016, Nvidia agreed to a settlement for a false advertising lawsuit regarding its GTX 970 model, as the models were unable to use all of their advertised 4 GB of RAM due to limitations brought by the design of its hardware. In May 2017, Nvidia announced a partnership with Toyota Motor Corp. Toyota will use Nvidia's artificial intelligence platform for its autonomous vehicles. In July 2017, Nvidia and Chinese search giant Baidu, Inc. announced a far-reaching AI partnership that includes cloud computing, autonomous driving, consumer devices, and Baidu's open-source AI framework PaddlePaddle. Baidu unveiled that Nvidia 's Drive PX 2 AI will be the foundation of its autonomous-vehicle platform.

Nvidia officially released the NVIDIA TITAN V on December 7, 2017.

Https://nvidianews.nvidia.com/news/nvidia-reinvents-the-workstation-with-real-time-ray-tracing-6683520< /ref>

Nvidia officially released RTX 2080GPUs September 27, 2018.

In 2018, announced that Nvidia's Tesla P4 graphic cards would be integrated into Google Cloud service's artificial intelligence.


Finances
For the fiscal year 2018, Nvidia reported earnings of US$3.047 billion, with an annual revenue of US$9.714 billion, an increase of 40.6% over the previous fiscal cycle. Nvidia's shares traded at over $245 per share, and its market capitalization was valued at over US$120.6 billion in September 2018.


GPU Technology Conference
NVIDIA’s GPU Technology Conference (GTC) is a series of technical conferences held around the world. It originated in 2009 in San Jose, California, with an initial focus on the potential for solving computing challenges through GPUs. In recent years, the conference focus has shifted to various applications of artificial intelligence and deep learning, including: , healthcare, high performance computing, and NVIDIA Deep Learning Institute (DLI) training. GTC 2018 attracted over 8400 attendees.


Product families
Nvidia's family includes primarily graphics, wireless communication, PC processors and automotive hardware/software. Some families are listed below:

  • , consumer-oriented graphics processing products
  • computer-aided design and digital content creation workstation graphics processing products
  • NVS, multi-display business graphics solution
  • , a system on a chip series for mobile devices
  • , dedicated general purpose GPU for high-end image generation applications in professional and scientific fields
  • , a motherboard chipset created by Nvidia for Intel (Celeron, Pentium and Core 2) and AMD (Athlon and Duron) microprocessors
  • Nvidia Grid, a set of hardware and services by Nvidia for graphics virtualization
  • Nvidia Shield, a range of gaming hardware including the , and, most recently, the Shield Android TV
  • Nvidia Drive automotive solutions, a range of hardware and software products for assisting car drivers. The is a high performance computer platform aimed at autonomous driving through deep learning, while Driveworks is an operating system for driverless cars.


Open-source software support
Until September 23, 2013, Nvidia had not published any documentation for its hardware, meaning that programmers could not write free and open-source for its products without resorting to (clean room) reverse engineering.

Instead, Nvidia provides its own GeForce graphics drivers for X.Org and an open-source library that interfaces with the , or Solaris kernels and the proprietary graphics software. Nvidia also provided but stopped supporting an obfuscated open-source driver that only supports two-dimensional hardware acceleration and ships with the X.Org distribution.

The proprietary nature of Nvidia's drivers has generated dissatisfaction within . Some Linux and BSD users insist on using only open-source drivers and regard Nvidia's insistence on providing nothing more than a binary-only driver as inadequate, given that competing manufacturers such as offer support and documentation for open-source developers and that others (like AMD) release partial documentation and provide some active development.

An overview of graphic card manufacturers and how well they work with Ubuntu Ubuntu Gamer, January 10, 2011 (Article by Luke Benstead)

Because of the closed nature of the drivers, Nvidia video cards cannot deliver adequate features on some platforms and architectures given that the company only provides x86/x64 and ARMv7-A driver builds. As a result, support for 3D graphics acceleration in Linux on does not exist, nor does support for Linux on the -restricted PlayStation 3 console.

Some users claim that Nvidia's Linux drivers impose artificial restrictions, like limiting the number of monitors that can be used at the same time, but the company has not commented on these accusations.


Deep learning
Nvidia GPUs are used in , artificial intelligence, and accelerated analytics. The company developed GPU-based deep learning in order to use artificial intelligence to approach problems like cancer detection, weather prediction, and self-driving vehicles. They are included in all Tesla vehicles. The purpose is to help networks learn to “think”. According to , Nvidia GPUs "work well for deep learning tasks because they are designed for parallel computing and do well to handle the vector and matrix operations that are prevalent in deep learning". These GPUs are used by researchers, laboratories, tech companies and enterprise companies. In 2009, Nvidia was involved in what was called the "big bang" of deep learning, "as deep-learning neural networks were combined with Nvidia graphics processing units (GPUs)". That year, the used Nvidia GPUs to create Deep Neural Networks capable of machine learning, where determined that GPUs could increase the speed of deep-learning systems by about 100 times.

In April 2016, Nvidia produced the DGX-1 based on an 8 GPU cluster, to improve the ability of users to use deep learning by combining GPUs with integrated deep learning software. It also developed Nvidia Tesla K80 and P100 GPU-based virtual machines, which are available through Google Cloud, which Google installed in November 2016. added GPU servers in a preview offering of its N series based on Nvidia's Tesla K80s, each containing 4992 processing cores. Later that year, AWS's P2 instance was produced using up to 16 Nvidia Tesla K80 GPUs. That month Nvidia also partnered with IBM to create a software kit that boosts the AI capabilities of Watson, called IBM PowerAI. Nvidia also offers its own NVIDIA Deep Learning software development kit. In 2017, the GPUs were also brought online at the Center for Advanced Intelligence Project for . The company's deep learning technology led to a boost in its 2017 earnings.

In May 2018, researchers at the artificial intelligence department of Nvidia realized the possibility that a robot can learn to perform a job simply by observing the person doing the same job. They have created a system that, after a short revision and testing, can already be used to control the universal robots of the next generation. In addition to GPU manufacturing, Nvidia provides parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications. "Robot see, robot do: Nvidia system lets robots learn by watching humans" New Atlas, May 23, 2018


Inception Program
Nvidia's Inception Program was created to support startups making exceptional advances in the fields of AI and Data Science. Award winners are announced at Nvidia's GTC Conference. There are currently 2,800 startups in the Inception Program.


2018 winners
  • Subtle Medical (healthcare)
  • AiFi (enterprise)
  • Kinema Systems (autonomous vehicles)


2017 winners
  • Genetesis (social innovation)
  • Athelas (hottest emerging)
  • (most disruptive)


See also


External links

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