NVIDIA Announces New AI Partners, Courses, Initiatives to Deliver Deep Learning Training Worldwide Nasdaq:NVDA

SANTA CLARA, Calif., Oct. 31, 2017 (GLOBE NEWSWIRE) — NVIDIA today announced a broad expansion of its Deep Learning Institute (DLI), which is training tens of thousands of students, developers and data scientists with critical skills needed to apply artificial intelligence.

The expansion includes:

  • New partnerships with Booz Allen Hamilton and deeplearning.ai to train thousands of students, developers and government specialists in AI.
  • New University Ambassador Program enables instructors worldwide to teach students critical job skills and practical applications of AI at no cost.
  • New courses designed to teach domain-specific applications of deep learning for finance, natural language processing, robotics, video analytics and self-driving cars.

“The world faces an acute shortage of data scientists and developers who are proficient in deep learning, and we’re focused on addressing that need,” said Greg Estes, vice president of Developer Programs at NVIDIA. “As part of the company’s effort to democratize AI, the Deep Learning Institute is enabling more developers, researchers and data scientists to apply this powerful technology to solve difficult problems.”

DLI – which NVIDIA formed last year to provide hands-on and online training worldwide in AI – is already working with more than 20 partners, including Amazon Web Services, Coursera, Facebook, Hewlett Packard Enterprise, IBM, Microsoft and Udacity.

Today the company is announcing a collaboration with deeplearning.ai, a new venture formed by AI pioneer Andrew Ng with the mission of training AI experts across a wide range of industries. The companies are working on new machine translation training materials as part of Coursera’s Deep Learning Specialization, which will be available later this month.

“AI is the new electricity, and will change almost everything we do,” said Ng, who also helped found Coursera, and was research chief at Baidu. “Partnering with the NVIDIA Deep Learning Institute to develop materials for our course on sequence models allows us to make the latest advances in deep learning available to everyone.”

DLI is also teaming with Booz Allen Hamilton to train employees and government personnel, including members of the U.S. Air Force. DLI and Booz Allen Hamilton will provide hands-on training for data scientists to solve challenging problems in healthcare, cybersecurity and defense.

To help teach students practical AI techniques to improve their job skills and prepare them to take on difficult computing challenges, the new NVIDIA University Ambassador Program prepares college instructors to teach DLI courses to their students at no cost. NVIDIA is already working with professors at several universities, including Arizona State, Harvard, Hong Kong University of Science and Technology and UCLA.

DLI is also bringing free AI training to young people through organizations like AI4ALL, a nonprofit organization that works to increase diversity and inclusion. AI4ALL gives high school students early exposure to AI, mentors and career development.

“NVIDIA is helping to amplify and extend our work that enables young people to learn technical skills, get exposure to career opportunities in AI and use the technology in ways that positively impact their communities,” said Tess Posner, executive director at AI4ALL.

In addition, DLI is expanding the range of its training content with: 

  • New project-based curriculum to train Udacity’s Self-Driving Car Engineer Nanodegree students in advanced deep learning techniques as well as upcoming new projects to help students create deep learning applications in the robotics field around the world.
  • New AI hands-on training labs in natural language processing, intelligent video analytics and financial trading.
  • A full-day self-driving car workshop, “Perception for Autonomous Vehicles,” available later this month. Students will learn how to integrate input from visual sensors and implement perception through training, optimization and deployment of a neural network.

To increase availability of AI training worldwide, DLI recently signed new training delivery partnerships with Skyline ATS in the U.S., Boston in the U.K. and Emmersive in India.

More information is available at the DLI website, where individuals can sign up for in-person or self-paced online training.

Keep Current on NVIDIA
Subscribe to the NVIDIA blog, follow us on Facebook, Google+, Twitter, LinkedIn and Instagram, and view NVIDIA videos on YouTube and images on Flickr.

About NVIDIA
NVIDIA’s (NASDAQ:NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.

For further information, contact:
Ken Brown
Corporate Communications
NVIDIA Corporation
(510) 290-2603
kebrown@nvidia.com  

Certain statements in this press release including, but not limited to, statements as to:  the expected numbers of students, developers and government specialists to be trained in AI;  the expansion, benefits, impact and goals of DLI’s offerings and collaborations, including partnerships, the NVIDIA University Ambassador Program and training courses; the new training content to be made available through DLI; and the number DLI’s partners; and the release of new machine translation training materials  are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. 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 product and technologies; market acceptance of our products or our partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission, or SEC, including its Form 10-Q for the fiscal period ended July 30, 2017. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2017 NVIDIA Corporation. All rights reserved. NVIDIA and the NVIDIA logo are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.

NVIDIA Sets Conference Call for Third-Quarter Financial Results Nasdaq:NVDA

| Source: NVIDIA


SANTA CLARA, Calif., Oct. 26, 2017 (GLOBE NEWSWIRE) — NVIDIA will host a conference call on Thursday, Nov. 9, at 2 p.m. PT (5 p.m. ET) to discuss its financial results for the third quarter of fiscal year 2018, ending October 29, 2017.

The call will be webcast live (in listen-only mode) at the following websites: www.nvidia.com and www.streetevents.com. The company’s prepared remarks will be followed by a question and answer session, which will be limited to questions from financial analysts and institutional investors.

Ahead of the call, NVIDIA will provide written commentary on its third-quarter results from its CFO. This material will be posted to www.nvidia.com/ir immediately after the company’s results are publicly announced at approximately 1:20 p.m. PT.

To listen to the conference call, dial (877) 223-3864 or, for those outside the United States, (574) 990-1377, conference ID 96232617.

A replay of the conference call will be available until Nov. 16, 2017, at (855) 859-2056, conference ID 96232617. The webcast will be recorded and available for replay until the company’s conference call to discuss financial results for its fourth quarter and fiscal year 2018.

Keep Current on NVIDIA
Subscribe to the NVIDIA blog, follow us on Facebook, Google+, Twitter, LinkedIn and Instagram, and view NVIDIA videos on YouTube and images on Flickr.

About NVIDIA
NVIDIA’s (NASDAQ:NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.  

 
For further information, contact:    
Simona Jankowski   Robert Sherbin
Investor Relations      Corporate Communications
NVIDIA Corporation    NVIDIA Corporation
(408) 566-6474      (408) 566-5150
sjankowski@nvidia.com    rsherbin@nvidia.com 
     

© 2017 NVIDIA Corporation. All rights reserved. NVIDIA and the NVIDIA logo are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries.  




NVIDIA, Taiwan’s Ministry of Science and Technology to Accelerate Taiwan AI Revolution with NVIDIA AI Computing Platform Nasdaq:NVDA

TAIPEI, Taiwan, Oct. 26, 2017 (GLOBE NEWSWIRE) — GTC Taiwan  NVIDIA today announced that it is collaborating with Taiwan’s Ministry of Science and Technology (MOST) to accelerate the development of artificial intelligence across Taiwan’s commercial sector in support of its recently announced AI Grand Plan to help foster domestic AI-related industries.

The collaboration — kicked off with a jointly hosted AI Symposium during NVIDIA’s GPU Technology Conference in Taiwan, which is being attended by more than 1,400 scientists, developers and entrepreneurs — calls for NVIDIA to help MOST promote AI across Taiwan through five initiatives.

“Taiwan has been the epicenter of the PC revolution, and it will serve as a key center for the next industry revolution focused on AI,” said NVIDIA founder and CEO Jensen Huang. “We are delighted to be working closely with MOST to ensure that Taiwan fully harnesses the power of this technological wave.”

“AI is the key to igniting Taiwan’s next industrial revolution, building on the long-established strength of our IT manufacturing capabilities,” said Dr. Liang-Gee Chen, Minister of Science and Technology. “Our focus is on drawing academics, industry and young talent into our AI Grand Plan to create an ecosystem based on AI innovation.”

Under the agreement, the National Center for High-Performance Computing will build Taiwan’s first AI-focused supercomputer powered by NVIDIA® DGX™ AI computing platforms and Volta architecture-based GPUs. Its target is to create a platform for accelerating advanced research and industry applications that next year reaches 4 petaflops of performance – placing it in the top 25 fastest supercomputers in the Top500 list – and 10 petaflops within four years.

In other steps:

  • MOST and NVIDIA’s Deep Learning Institute will train 3,000 developers over the next four years on the use of deep learning in smart manufacturing, the Internet of Things, smart cities and healthcare. Launched last year, the Deep Learning Institute provides hands-on training for developers, data scientists and researchers through self-paced online labs and instructor-led workshops that use open-source frameworks, as well as NVIDIA’s GPU-accelerated deep learning platforms.
  • NVIDIA is rolling out domestically its Inception program to help MOST establish its “Youth Technology Innovation and Entrepreneurship Base” for local AI startups. NVIDIA’s Inception program is a virtual incubator for startups focused on AI and deep learning, providing young companies with hardware grants, marketing support and access to NVIDIA’s larger deep-learning ecosystem. Just last week, it added its 2,000th member company.
  • NVIDIA will support MOST’s overseas talent training program for post-doctorates by offering high-level internship programs.
  • NVIDIA will provide NVIDIA Deep Learning Accelerator (NVDLA) technology for IoT and SoC devices, plus technical support, to MOST’s Project Moon Shot, AI Edge – its NT$4 billion, four-year program to use AI to increase the competitiveness of the domestic semiconductor industry by focusing on memory, sensors and edge products.

And in a related effort, MOST will provide domestic robotics experts with access to NVIDIA DGX Station™ AI deskside supercomputers and NVIDIA Jetson™ TX2 AI modules through the Central and Southern Taiwan Science Parks. NVIDIA is making available DGX-1 systems for MOST’s Formosa Speech Grand Challenge, in which 150 teams from local universities and high schools will compete at the end of October on creating networks capable of Chinese speech recognition. Taiwan’s AI Grand Plan, which was announced in August, aims to create a strong environment for fostering AI innovations and connect with industrial leadership from around the world.

About MOST
In 1959, the National Science Council was established to promote overall S&T development, academic research and constructing science parks nationwide. The institution was later reorganized and in 2014 became the Ministry of Science and Technology (MOST), aiming to facilitate stronger connections among the industries and boost Taiwanese competitiveness at the international level.

About NVIDIA
NVIDIA‘s (NASDAQ:NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.

For further information, contact:
Melody Tu
Sr. Manager PR, APAC
NVIDIA Corporation
+886-6605-5856
metu@nvidia.com

Certain statements in this press release including, but not limited to, statements as to: the goals, benefits and impact of the collaboration between NVIDIA and MOST; the benefits impact, goals and performance of NVIDIA AI computing platforms, NVIDIA Volta architecture-based GPUs, and the benefits and impact of NVIDIA helping to train of developers and providing access to the NVIDIA Inception program, internship programs, NVIDIA DGX Station AI deskside supercomputers, Jetson TX2 AI modules, DGX-1 systems and the NVIDIA Deep Learning Accelerator; and Taiwan serving as a key center of the next industry revolution focused on AI are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. 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 product and technologies; market acceptance of our products or our partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission, or SEC, including its Form 10-Q for the fiscal period ended July 30, 2017. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2017 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, DGX, DGX Station and Jetson are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.

Has Delphi Abandoned The BMW/Intel/Mobileye Ship For Nvidia? – NVIDIA Corporation (NASDAQ:NVDA)

Rethink Technology business briefs for October 24, 2017.

Delphi buys nuTonomy, an autonomous vehicle software startup with Nvidia as a key partner

Source: nuTonomy

Delphi Automotive’s (DLPH) announcement today that it was buying nuTonomy was stunning in that it seemed a reversal of the course the company had set only a few months before when it joined the BMW/Intel/Mobileye (OTCPK:BMWYY) (NASDAQ:INTC) team as a systems integrator.

Strictly speaking, the acquisition of nuTonomy changes nothing insofar as Delphi’s role in the BMW team. Yet, it changes everything. NuTonomy early on partnered with Nvidia (NVDA) for processing hardware. Even now, its webpage prominently displays the Nvidia logo, as shown above.

NuTonomy is primarily focused on developing autonomous vehicle software. And nuTonomy’s job listings feature an ad for an Embedded/GPU Software Engineer with CUDA experience. CUDA is Nvidia’s proprietary GPU programming environment for general computation on its GPUs.

The ad is similar to the ad for the Senior GPU engineer by GM’s (GM) Cruise Automation that I recently highlighted. As in the case with Cruise, it can’t be said with certainty whether nuTonomy is using some form of Nvidia’s Drive PX 2, or simply its GPUs. However, the San Jose Mercury News recently confirmed that nuTonomy used Nvidia chips.

One of my readers pointedly asked me today why Delphi had suddenly decided “to sleep with the enemy.” I replied that it appears that Delphi is hedging its bet on the BMW/Intel team.

I would too. It appears that the companies that have made the most rapid progress towards an autonomous vehicle solution have adopted Nvidia’s Drive PX 2 or some variant. Doing this affords the companies a reliable, compact and energy-efficient computing platform so that they can focus on developing software.

That focus on software is made that much easier by the software stack that Nvidia provides. That software stack has continued to mature and expand, so that Nvidia is now offering a full operating system called Drive OS in addition to its DriveWorks SDK.

Source: Anandtech

The nuTonomy acquisition is a vote of no-confidence in BMW/Intel/Mobileye. Sure, Intel and company can throw together enough hardware to satisfy the processing requirements of software developers such as nuTonomy or Cruise, but the software support is not nearly as comprehensive as what Nvidia offers now.

And it’s doubtful that BMW/Intel will be able to offer as energy-efficient a processor as Nvidia’s recently announced Drive PX Pegasus. Pegasus is geared towards SAE Level 5 autonomy and features dual GPUs and dual Xavier SOCs.

Source: Nvidia

Nvidia CEO Jensen Huang reveals that Xavier is still in tapeout

Nvidia’s Xavier SOC features next-generation custom ARM 64 bit CPU cores tied to a Volta architecture GPU section. The Volta GPU even carries over the Tensor Cores that provide acceleration to certain machine-learning tasks.

Source: Nvidia

When first announced over a year ago on Nvidia’s Blog, Xavier was to be available on a sampling basis by now. At Nvidia’s GTC Beijing, Nvidia’s CEO Jensen Huang updated the timetable so that sampling would begin in early 2018.

Yesterday, TSMC (TSM) held a panel discussion in honor of its 30th anniversary. The panel included Jensen Huang. During the Q&A, Huang stated that Xavier was still in tapeout. I was absolutely stunned. Tapeout is the process of creating a set of digital files that the foundry can use to build a given electronic component. I would have expected that to have been done a long time ago. After all, Nvidia has been talking up the capabilities of Xavier for more than a year.

I suspect that this final tapeout follows one or more iterations. The reason for it is unclear, but it probably has to do with the fact that Xavier was originally targeted for TSMC’s 16 nm process. That probably didn’t turn out to offer the performance that Nvidia wanted.

This new tapeout could be for TSMC’s 10 nm process, or even for its 7 nm process. During TSMC’s 2017 Q3 earnings conference call, TSMC management indicated that it expected 7 nm mass production to start in the first half of 2018. So it’s not inconceivable that Xavier could first appear on 7 nm.

Nvidia’s BB8 autonomous test vehicle sprouts LIDAR

I came across this picture of the latest incarnation of BB8, Nvidia’s autonomous vehicle test bed. The car was on display at GTC Europe in Munich.

Source: Nvidia

BB8 has sprouted a roof full of new sensors, including what are probably Velodyne LIDAR sensors. This is a fairly dramatic change from the version of BB8 we were shown around the time of CES in January.

After watching this video a few times (at full HD), I concluded that the sensors that were visible attached to the roof and side-view mirrors were probably just video cameras, and that Nvidia had opted to go with a mostly passive sensing approach that avoided LIDAR.

Tesla (TSLA) had also opted for passive video cameras, coupled to radar and ultrasonic sensors. The appearance of the LIDAR sensors on top of BB8 suggests that Nvidia has learned that they are necessary, at least to achieve SAE level 5 autonomy.

Nvidia is part of the Rethink Technology Portfolio and is a recommended buy.

Disclosure: I am/we are long NVDA, TSM.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Nvidia: Earnings Forecast – NVIDIA Corporation (NASDAQ:NVDA)

Thesis

Nvidia (NVDA) is likely to produce a revenue and earnings beat as the company’s new Volta architecture is in high demand as well as enjoying a higher ASP.

Introduction

Nvidia is one of the most promoted stocks on Wall Street. With good reason, we would argue. The company is at the forefront of AI innovation while continuing to produce stellar results. Unlike, for example, a stock like Tesla (NASDAQ:TSLA). While we believe that creating affordable electric cars definitely constitute as innovation, as of yet, the company has yet to deliver. Meanwhile, the financial results continue to be dismal.

With Nvidia, both the story and the results are impressive. So much so that the company has received ten buy recommendations since its last earnings report, with most of them accompanied by price target increases. For perspective, this is almost one buy recommendation per week. One would be hard-pressed to find similar levels of Wall Street adoration elsewhere. The slew of recommendations and price target increases are mostly based on favorable views of the company’s Volta architecture. Needless to say, this much sell-side gunpowder has had a favorable effect on the stock price.

After reporting its 2Q17 earnings, the stock price fell roughly 8% to around $159 before rallying to $198 per share. At the time, we argued that, while Nvidia would likely report better than expected results, the share price would still fall:

“Nvidia (NVDA) will likely crush EPS estimates again this quarter but report inline revenues. The more important factor with Nvidia is what the earnings imply about the company’s valuation. I believe a guidance range is currently priced in, but I’m not convinced that this is a likely occurrence. Nvidia’s short-term risk is skewed to the downside.”

Our main argument was that Nvidia’s stock price appreciation was mainly based on investors granting the company a multiple expansion. To deserve this multiple expansion, the company would have to guide numbers that we considered unrealistic.

Unfortunately for non-premium readers, estimations of price movements are now exclusive to the Forecasting Earnings community, as we focus to continue to add as much value to the Marketplace offering as possible. However, we will continue to release our earnings estimate to the general public.

Revenues

One might recall that Nvidia delivered disappointing data center growth in 2Q17, which some pointed out as the cause of the roughly 8% drop. We argued that this “slow” in data center growth was vastly over-exaggerated, particularly because the deceleration was not caused by any fundamental demand issue.

According to the CEO. the slowdown in growth was attributed to the company ramping up Volta into production:

“So first of all, Q2 was a transition quarter for our data center. I thought we did great. We almost tripled year over year, and we ramped Volta into volume production. And because Volta was so much better than our last generation processor – Volta is 100 times faster than Kepler, 100 times faster than Kepler just four years ago, and Kepler was already 10 times faster than CPUs. And so Volta was such a giant leap when we announced it in GTC right at the beginning of the quarter. I thought the team did fantastically transitioning the customer base to Volta, and now Volta is in high-volume production.”

It was also clarified that Volta was now, meaning as of the time of the conference call, in high-volume production. So investors can expect to see the first full quarter of Volta. As for how the Volta is being received from a customer standpoint, the CEO relayed that:

“Customers are clamoring for it. The leap generationally for deep learning is quite extraordinary. And so we’re expecting Volta to be very, very successful.”

Jen-Hsun Huang, the CEO, has never been one to exaggerate financial and demand performance. Quite the contrary, the company is usually very conservative with statements that would indicate anything on its top or bottom line. As such, I do not feel that the above statement should be taken with a grain of salt and can even be taken at face value albeit applying the regular CEO optimism discount.

Secondly, Volta is going to be very expensive, which is good for investors. Even though management was being a bit vague surrounding ASP, the comments that were made suggest a significantly higher ASP and better gross margins. The cost of manufacturing a Volta is close to $1000, according to management. At the same time, management claims that Volta saves customers several hundred thousand dollars. After having said that, the CEO concludes with:

“and so I guess the pricing – your question relates is pricing. We expect pricing to be quite favorable for Volta.”

In spite of the information below, Wall Street analysts are expecting the company to report $2.36 billion revenue. Sequentially, that translates to a $130 million increase in revenue while it implies a $360 million revenue increase (18%) on a year-over-year basis. This may seem like a lot, but actually implies a significant slowdown in the company’s growth rate. To us, this sounds like complete nonsense given the brand new in high demand new architecture and we would offer that analysts are deliberately lowballing estimates.

The counter-argument might be that data center while growing fast, is still a relatively small part of consolidated revenues and thus can’t be expected to drive top-line growth as much as the company’s gaming segment. Secondly, last year’s Q3 saw additional upside based on the release of the then new gaming cards based on Pascal. Finally, these cards must now also compete with AMD’s newest Vega GPU’s.

We concur that not having a new gaming release will indeed dampen the company’s growth rate. However, given the high ASP of Volta and the high demand, I expect the datacenter revenue, together with the rest of the segments to be able to increase the company’s revenue by at least $200 million on a sequential basis. We should note that this estimate regards the older Pascal models as competitive with the new AMD GPUs.

Conclusion

In other words, I expect Nvidia to report at least $2.43B in revenues which result in a revenue beat. From there, we simply apply margin and tax rate estimates to get to an EPS of $1.00 which is higher than Wall Street consensus of $0.94 EPS.

Earnings estimate: Revenue beat $2.43B versus $2.36B consensus and EPS beat of $1.00 versus $0.94 consensus.
Confidence interval estimate: Exclusive to subscribers.
Post-earnings direction: Exclusive to subscribers.
Confidence interval direction: Exclusive to subscribers.
Key earnings metric to watch: Exclusive to subscribers.

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Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.