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   Technology StocksArtificial Intelligence, Robotics and Automation


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From: Frank Sully9/6/2021 2:18:58 AM
   of 2185
 
Volkswagen and Argo AI reveal first ID Buzz test vehicle for autonomous driving

Rebecca Bellan @rebeccabellan
8:18 PM EDT•September 5, 2021



Image Credits: Volkswagen Group

Volkswagen Commercial Vehicles, a standalone VW brand responsible for the development and sales of light commercial vehicles, and Argo AI, an autonomous driving technology company, unveiled the first version of the ID Buzz AD (Autonomous Driving) on Sunday.

The two companies shared plans to test and commercially scale the jointly developed, fully-electric self-driving van over the next four years at the VW night event ahead of the 2021 IAA Mobility Event in Munich. Testing of the prototype, one of the first five planned test vehicles, has already begun and will continue at Argo’s development center in Neufahrn, near Munich, as well as at Argo’s nine hectare closed course near the Munich airport, which tests for a variety of traffic situations unique to European driving conditions, and Argo’s test track in the United States.

“Building on our five years of development and learnings from our operations in large, complex U.S. cities, we are excited to soon begin testing on the streets of Munich in preparation for the launch of the self-driving commercial ridepooling service with MOIA,” said Bryan Salesky, founder and CEO of Argo AI, in a statement.

In 2025, MOIA, a subsidiary of the VW Group that works with cities and local public transport providers on mobility solutions, will be commercially launching the ID Buzz in Hamburg as part of a self-driving ride-pool system. The ride-pool service is designed to leverage the power of autonomous systems to relieve inner-city congestion.

At the event, Volkswagen Commercial Vehicles, which has developed a separate businesses unit devoted to autonomous driving and acquired a stake in Argo AI, demonstrated how ride-pooling via a self-driving system can help with managing traffic flows.

“An environment recognition system from six lidar, eleven radar and fourteen cameras, distributed over the entire vehicle, can capture much more than any human driver can from his seat,” said Christian Senger, head of autonomous driving at Volkswagen Commercial Vehicles, said at the event.

VW first revealed the ID Buzz as a concept vehicle back in 2017, a futuristic take on the classic microbus that invokes nostalgia as a family camper van. The final product looks a bit different than the iconic campers, now containing all of the bells and whistles of autonomy, such as Argo’s proprietary sensor Argo Lidar, which sits on top of the Buzz’s roof. According to Argo AI, its lidar can detect objects from a distance of more than 1,300 feet, or 400 meters. Four years ago, Argo acquired lidar company Princeton Lightwave, which has allowed the company to produce this new, highly accurate sensor with patented Geiger-mode technology that can detect a single photon, the smallest of light particles, so that it can capture, detect and precisely represent objects with low reflectivity like black vehicles.

Argo AI’s entire system consists of sensors and software that give the computer a 360 degree awareness of the vehicle’s environment, allowing it to “predict the actions of pedestrians, bicyclists and vehicles, and direct the engine, braking and steering systems so that the vehicle moves safely and naturally, like an experienced driver,” according to a statement from VW.

This isn’t the first time Argo’s tech will be used to transport humans where they need to go. In July, Argo and Ford announced plans to launch at least 1,000 self-driving vehicles on Lyft’s ride-hailing network over the next five years in cities like Miami and Austin. In the same month, the California Public Utilities Commission issued Argo a Drivered AV pilot permit so it could start testing on public California roads. Argo AI recently also received a $7.5 billion valuation, nearly two years after the VW Group finalized its $2.6 billion investment in the company.

techcrunch.com

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From: Frank Sully9/6/2021 2:23:18 AM
2 Recommendations   of 2185
 
The Rise Of AI In The Transportation And Logistics Industry



Cindy Gordon
Contributor AI
CEO, Innovation Leader Passionate about Modernizing via AI

What a ride it has been in the Transportation and Logistics (T&L)sector regarding the B2C eCommerce growth boom world-wide, much of this driven by the global retail sales growth during COVID-19.

This accelerated growth and now with global trade rapidly rebounding, the timing is right for the transportation and logistics industry to advance smarter digital transformations.



Transportation and Logistics Industry - AI Digital[+]GETTY

According to McKinsey, this industry must be completely digital to secure its future – but what will it take?

The future although seems rosy, is complex and challenging due to rapid industry consolidations, new technology acceleration, ever constant regulatory changes such as GDBR, and of course, Brexit impacting European markets.

The World Trade Organization (WTO) has been most vocal reinforcing the importance of the T&L Industry to take heed on the importance of customer experiences – how courier drivers ship, route and deliver parcels and products with agile speed has become the new normal. Service speed from Amazon has shifted customer expectations on timeliness on B2B to be as resilient as their B2C personal experiences demanding instant quotations, real time tracking on orders, and personalize messaging on express services.

We have always known the omni-channel logistics for transparent, personalized, efficient and speedy delivery options would forever change the network infrastructure dynamics of the transportation and logistics industry. We are even starting to see crowd-sourced delivery brands and internet last mile service providers, such as Cargomatic, Flexport flexing their muscle on traditional business models.

Unfortunately, many logistic companies are held back by outdated IT infrastructures, fleet management and warehousing systems that are impacting their ability to innovate and digitally transform fast enough to differentiate better and achieve greater were never designed to interconnect, and data that is widely distributed between systems specialized to support only individual operations, such as fleet management, warehousing, and port or marine operations.

Today’s T&L challenge is to escape the limitations of legacy systems, gain a more holistic perspective, and unlock new value from the networks and complex relationships that characterize this sector.

Smart infrastructure driven by new vehicle technology and autonomous driverless truck and drone ships will change how cargo moves. As the Internet of Things (IoT) continues to connect everything from courier drivers wearing smart uniforms and smart watches to driving smart vehicles, on smart roads with intelligent signage where every container, pallet, package are all AI and IoT sensor connected, these new capabilities are changing how decisions are made, what routes to take, how fleets are managed where packages, products and cargo flow.

AI allows T&L companies to process more easily historical trends to forecast and manage inventory, and address variable demands across supply chain operations. Historical data from past operations can help AI algorithms conduct primary operations automatically, reducing human error in the supply chain, and even predict revenue forecasts or operating margins – being able to see foreward vs looking in the rear view mirror with sophisticated AI driven predictive models is in short the only future for T&L companies that want to modernize and successfully evolve.

Agility and the ability to innovate to use AI effectively and efficiently is unfortunately often hampered when IT architectures are bogged down in legacy investments and ability to apply agile AI solutions in the cloud to inform decision making to help create more memorable customer experiences, and help companies differentiate requires thinking outside the box more.

Leveraging Salesforce’s customer success platform can help companies transform digitally and improve scaling needs. However one of the big issues that constantly plagues CRM systems is often their inability to drive the discipline to use the powerful new tools. So many companies are finding new pathways to optimize and close the adoption gaps to ensure investments are maximized with value-based outcomes.



Purolator RB03 09 24 09 New Purolator electric[+]TORONTO STAR VIA GETTY IMAGES

T&L market leaders like Purolator are now powering unique predictive and prescriptive AI sales business models to increase their company’s win rates and accelerate top-line revenue growth. Purolator’s sales operational leaders have learned that AI requires a transparent ability to easily track data completeness and monitor sales predictions for accuracy. AI without complete and quality data is a recipe for failure. AI methods like prescriptive analytics offers Purolator sales professionals real-time coaching. Like Uber guides its passengers to the right destination with more precision in timely navigation, next generation AI sales guidance systems also will have an uncanny ability to provide real-time relevant sales coaching to help both the seller and the customer to have a more valuable experience. Purolator’s, Jeffrey Green, Senior VP Sales and Customer Experience, has a strong background in advanced analytics and mathematics and equally a strong technology leadership heritage which are key skill attributes to lead a complex digital customer experience transformation. Under his visionary customer experience management leadership, with strong support from his colleagues: CIO, Ricardo Costa, CMO, Ramsey Mansour, and CFO, Roselyn Samtelben, this team is trail-blazing with AI innovations across the enterprise.

Digital Transformation is not easy and although the technology solutions can easily be found in the market, it takes tremendous leadership, communication and talent management to up-skill T&I industries – and of course investment capital and sustainability – or simply “ the art of the long view,” with a strong dose of patience to manage the ebbs and flows of resistance and renewal.

What is a constant in the T&L industry is leaders will need to build an agile digital culture and business model that consistently values innovation and understands the value of data to drive improved decision making. Unlocking data relevancy to provide strategic insights will be an ongoing leadership priority as T&L companies continue to drive forward their digital transformation initiatives.

It is an exciting time for the T&L industry as all companies in this sector race to advance their digital transformation efforts, leveraging advanced analytics to see what is hard to see.

I am reminded of Tom Peter’s famous quote when he said: “Leaders win through logistics. Vision, sure. Strategy, yes. But when you go to war, you need to have both toilet paper and bullets at the right place at the right time. In other words, you must win through superior logistics.”

The race is on for superior and much smarter logistics. Is your organization ready?

Follow me on Twitter or LinkedIn. Check out my website or some of my other work here.


Cindy Gordon

Dr. Cindy Gordon is a CEO, a thought leader, author, keynote speaker, board director, and advisor to companies and governments striving to modernize their business

forbes.com

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From: Glenn Petersen9/6/2021 5:08:50 AM
1 Recommendation   of 2185
 
Workers fear robots and automation from Covid are here to stay. But they create jobs.

Calls for steps like 'robot taxes' to level the playing field between humans and AI will only hurt the economy — and workers.

Sept. 6, 2021, 3:30 AM CDT
By James Pethokoukis, economic policy analyst at the American Enterprise Institute
MSNBC.com

Before the pandemic, headline-grabbing advances in artificial intelligence and robotics — such as gaming champ AlphaGo becoming the first computer program to beat a human professional player at the board game Go, and those cool/scary videos of gymnastic machines from Boston Dynamics jogging and jumping and tumbling — led to numerous stories and books about robots taking all the jobs. That, even as unemployment was falling to its lowest levels since the 1960s.
Wait until the government tries to define “robot” for tax purposes and a legion of corporate lobbyists charge into battle, gumming up the works for the robot producers and would-be customers.
Now unemployment is a lot higher, and a much-mentioned post-pandemic economic trend is the continuation of greater workplace automation that began during the outbreak to protect people from Covid-19. The economics team at Wall Street bank Goldman Sachs are highlighting the shift to ecommerce and the “digitization of the workplace” — including cost and time savings from remote work and virtual meetings — as keys to higher productivity and economic growth over the next few years. Meanwhile, labor shortages and surging demand have businesses looking at how to employ technology of all sorts to replace needed workers.

Supermarkets are installing more self-checkout kiosks, with some even experimenting with computer-vision capabilities that would eliminate the need for cashiers. Even older technology, such as QR codes, are being employed at places like restaurants, so diners can order from their tables by scanning those pixelated square barcodes rather than consulting a server. The Financial Times reported recently on a jewelry store owner who revamped her set-up so that window shoppers can use smartphones to purchase items by scanning those little square codes. She used to pay a part-time sales person, but not anymore.

Not to be outdone, Elon Musk announced plans in August to build a Tesla bot. The multibillionaire demonstrated the concept of a 5-foot-8-inch, 125-pound automaton at the automaker's recent AI day. For now, the Tesla bot only exists in a slide deck. But Musk said the chips and sensors currently employed for the autopilot driver-assist feature in Tesla cars would help jump-start the project, code-named Optimus (a likely nod to Optimus Prime from the “Transformers” film franchise).

Musk didn’t give a target date when consumers will be able to purchase it, and he acknowledged that the Tesla Bot “probably won’t work.” Even so, the announcement has already figured prominently in dire pronouncements about looming technological unemployment. “The commercial application of the planned robot is absolutely to replace human jobs — the ones that Musk himself finds ‘boring,’” Guardian columnist Van Badham writes. “Like ones working in factories, and supermarkets.”

But the dystopian story of tech-created unemployment fears is a lot older than those QR codes, first developed in Japan back in the 1990s. And over the long run, that story has always been wrong, as economists are quick to remind us. Although more and better machines destroy some jobs, they also create new ones — whether by increasing sales through lower prices (if you sell more stuff, you need more workers to make the stuff) or allowing workers to do new and more complex tasks. A 2020 study from Stanford University’s Institute for Human-Centered AI looked at the impact of AI and robotics on the manufacturing, retail banking and nursing home sectors. Researcher Yong Suk Lee found that although the technology initially replaced human workers, they eventually ended up creating jobs down the road. Econ 101 wins again.

Still, economists’ data and entrepreneurs’ assurances are unlikely to prevent more fearmongering about smart machines replacing humans, especially with headlines continuing to show advances in AI and robotics. Expect more calls for policymakers to consider steps like “robot taxes” so humans would have a more even playing field with technology. Microsoft co-founder Bill Gates, hardly a Luddite, floated the idea in 2017, as have public officials like New York City Mayor Bill de Blasio.

A tax on corporate robot purchases would discourage companies from buying them — and when companies buy them anyway, the resulting tax revenue could be used to help displaced workers through retraining programs or even direct compensation. But this assumes workers should fear competition from robots, and that you can define what a robot is in the first place. You could make the case, after all, that even a simple spreadsheet is a robot of sorts.

Wait until the government tries to define “robot” for tax purposes and a legion of corporate lobbyists charge into battle, gumming up the works for the robot producers and would-be customers. We already got a taste of that last summer when the Senate Commerce Committee rejected attempts to lift regulations to allow for the deployment of thousands of driverless cars after unions and attorneys campaigned against the proposal, according to Reuters. Autonomous vehicles probably look like robots to taxi and truck drivers.

In the new Brookings Institution analysis “ Tax not the robots,” Robert Seamans correctly calls the notion of implementing robot taxes “a misguided idea that would have negative consequences for firms, their workers, and ultimately the economy.” In a review of the relevant economic literature, he notes there’s no evidence that robots are overall directly substituting for human labor. “Indeed, robots may actually be complementing labor, resulting in increases in employment,” he adds. Again, this is just as economists have predicted.

Of course, past and current labor market performance is no guarantee of future results, and robots could pose more of a danger to jobs and workers than they have until now. But we don’t want to slow down tech progress and the ways it makes workers more productive, since becoming more productive is how workers make more money over the long run. The new Institute of Labor Economics analysis “How Do Workers Adjust When Firms Adopt New Technologies?” finds evidence of “improved employment stability, higher wage growth, and increased cumulative earnings in response to digital technology adoption.”

We need more robots, not fewer. And given years of weak productivity growth in the United States, we need more of them ASAP. So rather than pre-emptively slowing down tech progress through robot taxes and regulation, let’s start by helping workers adjust. Which starts with technology.

Beyond making employees more productive by giving them more robots and AI, Seamans thinks technology can help workers survive and thrive. For example, he points out that data-driven tools can help match the skills of workers in one occupation with the skills needed in higher-paying careers. A brick mason and a welder actually have pretty similar skills, but the latter pays 75 percent more in Florida, so databases that discover, track and publicize the information could help masons find more lucrative jobs. He also favors limits or even bans on noncompete agreements to help labor market mobility. Policies to help workers navigate a world of greater automation and disruption are where governments should turn to, not policies that attempt to stifle change.

We can do lots of things to prevent robots from taking all the jobs, and instead help them help us create more. Though if they want to replace us for all those Zoom calls, that’s probably OK.

Workers fear robots and automation from Covid are here to stay. But they create jobs. (nbcnews.com)

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To: Glenn Petersen who wrote (1167)9/6/2021 10:39:17 AM
From: Savant
   of 2185
 
Desperation for employees...reminds me of the late 90's, when some companies were hiring while prospects were still incarcerated..

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To: Savant who wrote (1171)9/6/2021 12:04:06 PM
From: Glenn Petersen
   of 2185
 
A period when the widespread adoption of computers was fueling an increase in worker productivity and economic growth. Hopefully, history will repeat itself.

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From: Frank Sully9/6/2021 12:34:46 PM
   of 2185
 
How does Baidu's CEO Robin Li travel to work? Using Baidu's Robotaxi service of course!

Two minute video


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From: Frank Sully9/6/2021 6:28:57 PM
1 Recommendation   of 2185
 
The Amazing Robots Exploring Space Exploring the cosmos is hard work. These are the robots helping astronauts and engineers in space.



By Loukia Papadopoulos
Sep 06, 2021

Rover, Perseverance, Curiosity. If these names sound familiar, it's because they are among the most extraordinary robots currently exploring space. And while they might be the most famous, they are not the only robots helping astronauts and engineers discover the cosmos. Robots are present everywhere in space, from the International Space Station to out and about on planets and moons, and they bring together the best of science, technology and engineering. What do these robots do? A variety of tasks ranging from cleaning handrails, picking up objects, and flipping switches to collaborating to build structures in space.

Some of these advanced robots are even designed to handle hostile environments such as the ones found on the Moon and on Mars, and they can crawl, walk, scale cliffs, and sketch out the rough terrain found in all types of surroundings.

Indeed, it seems there's little these agile robots cannot do. In this video, we bring you footage of them live and in action. We also answer some of the most common questions about them: What are these robots called? Who developed them? Where are they now? What will they be doing on future missions?






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From: Frank Sully9/7/2021 12:42:07 AM
1 Recommendation   of 2185
 
Nvidia: AI Leadership Key To Continuous Double-Digit Stock Price Growth

Sep. 06, 2021 7:50 PM ET NVIDIA Corporation (NVDA) 15 Comments10 Likes

Khaveen Investments

Summary
  • The company’s share price has surged 42% along with its revenues at 54%, we aimed to determine if the share price has reached its peak or if there is more.
  • It is advancing its AI leadership to capture growth opportunities in the booming cloud market fueled by the rising volume of data.
  • We determine that pricing increase rather than shipment growth was the key to its PC GPU sales, and its pricing power was due to its performance improvements with every new.
  • Despite the company’s Arm acquisition still pending regulatory approval, it has gone ahead in advancing its product development with Arm’s architecture, with its new BlueField DPU and Nvidia Grace.



David Becker/Getty Images News

Since our previous analysis on Nvidia Corp ( NVDA), the company’s full-year revenues have increased by 53% in 2020 which has exceeded our expectationsof 43% growth with higher GPU sales across PC and data center markets. As such, the company’s stock price also surges well past our previous price target of $578.39. In this analysis, we determine if its impressive growth can continue and justify a higher valuation for the company.

The main segments of the company contributing to its high growth were the Data center & Gaming segment representing 40.2% and 46.5% of its total revenues respectively. We identified Nvidia’s AI leadership as a key advantage fuelling the growth across its data center segment capitalizing on rising data creation from AI, HPC and IoT applications with its AI leadership through its innovative products catered towards the booming cloud market. Besides data centers, gaming continues to be a key driver with its continuous performance improvements backed by new releases of next-generation GPU models contributing to rising pricing power to maintain ASP growth.

Finally, we followed up on the Arm acquisition which is slated by management to conclude by early 2022. Through the acquisition of Arm, it not only earns incremental licensing revenue but also the ability to further leverage its CPU capabilities to develop and expand its range of Arm-based products including upcoming CPUs launches and the latest DPU SoCs. As the company is in the progress of obtaining regulatory clearance, we analysed the effect of the acquisition on the market competitiveness of the CPU markets.



Source: Nvidia

AI Leadership ensures High Growth Across Key Data Centre Segment

The increasing volumes of data created will fuel data center growth over the next decade. An important aspect of this will be machine-to-machine and Artificial Intelligence ('AI') technologies that enable massive volumes of data to be processed with ease and speed. AI data processing is made possible by a system of linked supercomputers that are used to process complex workloads by running millions of simulations and financial models to generate predictions from massive volumes of data by identifying a pattern and then replicating that pattern identification across other data. As can be imagined, AI computing would require massive computing infrastructure.

Driven by the advent of AI, HPC, IoT and edge computing, data creation is projected to grow at a rate of around23% in the next 5 years. This would require greater cloud infrastructure to handle the increase in data. To determine the growth in cloud infrastructure revenues, we identified the factor of correlation of cloud infrastructure revenues to data volume growth over the past 10 years. The factor identified of 1.65x was applied to data volume growth projections to estimate the cloud infrastructure market growth rate to the year 2025.



Source: Statista, Khaveen Investments

Volume of Data Worldwide

2016

2017

2018

2019

2020

2021F

2022F

2023F

2024F

2025F

Cloud Infrastructure Market Revenues ($ bln)

32

46.5

69

96

129.5

178.9

246.3

342.9

470.6

650.6

Cloud Infrastructure Market Revenue Growth % ('a')

52%

45%

48%

39%

35%

38%

38%

39%

37%

38%

Data Volume (ZB)

18

26

33

41

64.2

79

97

120

147

181

Data Volume Growth % ('b')

16%

44%

27%

24%

57%

23%

23%

24%

23%

23%

Cloud Infrastructure Revenue Growth/Data Volume Growth Factor ('c')

3.25

1.02

1.80

1.61

0.62

1.65

1.65

1.65

1.65

1.65

*A =C x B

Source: Statista, Khaveen Investments

As mentioned, Artificial Intelligence ('AI') will play a crucial role in synthesizing and storing these waves of data. The race of AI computing technology is being led by semiconductor companies that create the chips that enable technology across all segments of the market. As such, innovations in AI have been especially expeditious in the semiconductor industry with several companies such as Nvidia, Intel and AMD developing significant AI capabilities in their chip systems.

We view Nvidia in particular, as not just an AI leader of the semiconductor industry, but as the AI leader of the world. Nvidia aims to develop AI solutions for every industry and is already well on the way there. It is the leader in autonomous vehicles, with its AI-enabled Advanced Driver Assistance Systems (ADAS) being developed for global automakers, having already secured $8 bln in automotive design wins. Notwithstanding, Nvidia’s automotive segment only represents 3.2% of its revenues. Nvidia’s key data center segment that represents 40.2% of its revenues, is where the company’s AI leadership is really seen. The company recently announced that its AI-powered DGX server has been adopted by the top 10 Aerospace companies, 6 of the top 10 US banks, and 8 out of the 10 top global telcos.



Source: Statista

As data volume and workload grow, it gets more difficult to transmit the data. To tackle this, enterprises are expected to bring applications and storage closer to themselves rather than transporting resources to a central location. As a result, large enterprises are more likely to build on-site data storage centers which require the use of an on-site fully built server system. This is where Nvidia’s latest DGX server comes into play. To put things in perspective, these aren’t the $500 GPU chipsets used in PCs. The GPU-enabled DGX servers are provided on a subscription model, with a single one costing a massive $4.3 million a year. As to the capability of DGX, its initial design was reported to have one of the world’s fastest AI workload speeds by the National Energy Research Scientific Computer Center (NERSC). Given both the first mover and technological advantage that Nvidia has, we see the company in a prime position to capture the on-premises server market in addition to the cloud server market. As such we expect the company’s data segment revenue as a percentage of total cloud capex to continue increasing at 3%. This was derived through our calculations by first estimating the total capex by the top 4 cloud providers (Amazon ( AMZN), Microsoft ( MSFT), Google ( GOOG), Alibaba ( BABA)) and adjusted by its market share as the total cloud capex.

Cloud Providers Capex ($ mln)

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Amazon

3,785

3,444

4,893

5,387

7,804

11,955

13,427

16,861

40,140

45,427

Microsoft

2,355

2,305

4,257

5,485

5,944

8,343

8,129

11,632

13,925

15,441

Google

3,438

3,273

7,358

11,014

9,950

10,212

13,184

25,139

23,548

22,281

Alibaba

403

768

1,243

1,680

1,598

3,129

5,287

4,596

Total (Top 4)

9,578

9,022

16,911

22,654

24,941

32,190

36,338

56,761

82,900

87,745

Source: Nvidia, Amazon, Microsoft, Google, Alibaba, Khaveen Investments

We then estimated the total cloud capex growth rate by basing it on the forecasted growth in the cloud infrastructure revenues on a 10-year average factor of 0.68x. With the growth in cloud capex, we computed Nvidia’s share of capex spending which has been growing at 3% on average in the past 7 years. Nvidia’s AI-powered GPU accelerators are deployed in more than 97% of all AI-accelerator hardware used by the top 4 cloud providers (Amazon, Google, Microsoft, and Alibaba). These top 4 cloud providers alone control 67%. Applying our estimated share of capex, we forecasted its total data center revenues growing at around 30%.



Source: Nvidia, Amazon, Microsoft, Google, Alibaba, Statista, Khaveen Investments

Continuous Performance Excellence Leads to Continuous Pricing Premium

Nvidia’s Gaming segment revenue growth has averaged a stellar 27% in the past 7 years. The main contributor is rising ASPs which averaged 27% whereas shipments growth was flat. Although Nvidia accounts for 81% of the discrete GPU market share and steadily rising, its market share in the overall GPU market has declined slightly against AMD ( AMD) and Intel ( INTC) who also manufactures integrated GPUs but is planning to develop its Alchemist product while Nvidia only produces discrete chips.



Source: Statista, JPR, Khaveen Investments

Based on its stagnant share of the overall GPU market, this implies that demand for the integrated GPU market continues to remain strong. PC shipments grew at -0.8% within the same period. Whereas GPU unit shipments were lower than the PC shipment growth with an average of -2%. One of the attributable factors is the rising GPU costs relative to stagnant PC prices. In the past 5 years, Nvidia’s average ASP as a percentage of PC ASP has risen from 19% to 38%, making it harder for PC makers to cater to the mid-range and entry-level markets which presence remains stable. As costs continue to increase and Intel seeks to capitalize on its refreshed Intel Iris Xe integrated chips, we see Nvidia’s share of overall GPUs to decline and PC shipments CAGR of 3% through 2025.

Gaming PC Share of Market Revenues

2016

2020

High End

43%

47%

Mid-Range

35%

34%

Entry Level

22%

19%

Source: JPR

However, every year, Nvidia releases a new product lineup offering better performance against the previous models. From GPUCheck, we obtained the average benchmark score of all GPU models released for each year to obtain an average score and the average performance increase at 22% per year. Then, the average performance increase is compared to the increase in Nvidia’s ASPs for each year to derive the ASP growth to performance growth factor average of 1.1x. This implies that Nvidia’s GPU performance increase can sustain its ASP growth at a factor of 1.1x. We believe this to be fair, given the company’s solid track record of continuous product development. Its next generation of GPUs with the Ampere Next architecture is expected to be launched next year with the anticipated RTX 4000 series a successor to its current lineup. One of the major significant upgrades anticipated is the switch towards TSMC’s (NYSE: TSM) N5 process allowing even more GPU cores and transistors than the current Ampere GPUs manufactured on TSMC’s N7 and Samsung ( OTC:SSNLF) 8N process. Even longer-term, the company’s roadmaps indicate continued innovation with the following generation of ‘Ampere Next Next’ expected in 2024 which could utilize TSMC’s N3 process.



Source: Statista, GPU Checker, Khaveen Investments

Year

Average Score

Average Score Increase ('a')

ASP Increase ('b')

ASP/Score Increase Factor ('c')

2025F

452.5

22%

24%

1.10

2024F

372.2

22%

24%

1.10

2023F

306.1

22%

24%

1.10

2022F

251.7

22%

24%

1.10

2021F

207.0

22%

24%

1.10

2020

170.3

57%

22%

0.38

2019

108.2

-32%

7%

-0.23

2018

158.0

39%

27%

0.70

2017

114

37%

25%

0.69

2016

83.4

18%

45%

2.51

2015

70.6

10%

26%

2.52

2014

64

Average

22%

1.10

*B = A x C

Source: Nvidia, Statista, JPR, GPU Checker

All in all, the main driver of gaming revenues is rising prices from continuous product development rather than unit shipments. Nonetheless, the robust demand on GPU shipments seen based on data from JPR indicates a major tailwind in 2021 and forecasted a growth rate of 36% based on the average GPU shipments growth rates of Q1 and Q2. Though we expect growth to normalize, and we based our shipment growth assumption beyond 2021 on a 3.5% CAGR through 2025. Also, accounting for Nvidia’s market share in GPUs, we derived its total unit shipment as well as ASP growth to forecast its total gaming revenue growth.



Source: Nvidia, Statista, JPR

Annualized Nvidia

2016

2017

2018

2019

2020

2021F

2022F

2023F

2024F

2025F

Shipments ('a')

34.76

37.67

33.58

27.68

31.95

43.45

44.97

46.55

48.18

49.86

Shipments Growth %

-1%

8%

-11%

-18%

15%

36.0%

3.5%

3.5%

3.5%

3.5%

ASPs ('b')

116.8

146.4

186.1

199.4

242.8

300.4

371.5

459.5

568.3

702.8

ASP Growth %

45%

25%

27%

7%

22%

24%

24%

24%

24%

24%

Gaming Revenues ($ mln) ('c')

4,060

5,513

6,250

5,518

7,759

13,051

16,707

21,386

27,377

35,045

Gaming Revenues Growth %

44.1%

35.8%

13.4%

-11.7%

40.6%

68.2%

28.0%

28.0%

28.0%

28.0%

*C = A x B

Source: Nvidia, Statista, JPR, WCCF Tech

Growth From Arm Regardless of Acquisition Approval

Already a leading developer of GPUs, Nvidia is using its advantage in AI to produce a range of new products. It is acquiring Arm to leverage its CPU capabilities across key industries as seen with the expansion of its Certified Systems with BlueField DPU SoCs featuring 22 bln transistors and incorporating 16 Arm-based CPUs along with a 400 gigabits-per-second networking chip. The combination of both company’s capabilities with CPU from Arm and Mellanox networking solution for an advanced chip enhanced by is AI Enterprise software suite in partnership with VMware ( VMW) vSphere creating a new market for Nvidia. The company has already received strong support from customersincluding Dell Technologies ( DELL), Inspur ( OTC:INPRF), Lenovo ( OTCPK:LNVGY) and Supermicro integrating its DPUs into their systems. Besides that, cloud service providers such as Baidu are using its DPUs to accelerate workloads. Additionally, it is also planning to enter the data center CPU market with Nvidia Grace against incumbents Intel and AMD.

That said, the deal is pending regulatory approval and management is expectingto obtain clearance by early 2022. The HHI index is a measure of market competitiveness commonly used by governmental bodies such as the FTC and the Department of Justice in M&A deals. It serves as guidance whether a deal would go through, or antitrust action would be taken depending on the concentration level.

Post-Merger HHI

Change from Premerger HHI

Antitrust Action

HHI < 1000

Not concentrated,

Any

No action likely

1000 < HHI < 1800

Moderately Concentrated,

>100

Moderately Concentrated, Possible Action

1800 < HHI

Highly Concentrated,

>50

Challenge very Likely

Source: OpenTextBC

For the Arm deal, the HHI calculation would be applied on the PC CPU and server market shares only as only Nvidia, AMD and Intel compete within the GPU markets. In Nvidia’s case, the HHI value for both markets would not change as it represents Arm’s share. For example, the PC CPU market HHI is valued at 4,312 in both pre-and post-acquisition.

PC CPU Market Pre-Acquisition

Share

s

s^2

PC CPU Market Post Acquisition

Share

s

s^2

Intel

54%

54

2916

Intel

54%

54

2916

AMD

36%

36

1296

AMD

36%

36

1296

Arm

10%

10

100

Nvidia

10%

10

100

Total

4312

Total

4312

Source: Statista, PCMag

Similarly, the CPU market for servers would derive the same HHI score as the PC CPU market as Nvidia would replace Arm’s share. There is no change to the HHI score of 6,334.

Server CPU Market Share Pre-Acquisition

Share

s

s^2

Server CPU Post Acquisition

Share

s

s^2

Intel

78%

78

6084

Intel

78%

78

6084

AMD

9%

9

81

AMD

9%

9

81

Arm

13%

13

169

Nvidia

13%

13

169

Total

6334

Total

6334

Source: Nextplatform, Itcandor

If we consider Nvidia’s planned entry to the server CPU market with the launch of Nvidia Grace. Even a small increase in share for Nvidia would lead to a reduction in the HHI value by 188. This highlights Intel’s incredibly high market share. Even if the deal does not go through, the market would still become more competitive. Thus, based on the change in HHI values, Nvidia has a rather unique case for the deal going through. It does not compete with Arm directly PC and server CPU markets, it would just take up Arm’s market share and would not lead to any change to the HHI. In fact, it could make the market even more competitive.

  • Regulators are "looking to ensure that their markets are pro-competitive, that this is pro-innovation… and this is good for customers. We can prove that and show that and demonstrate that overwhelmingly, so I have no concerns. - Jen-Hsun Huang, CEO of Nvidia
Server CPU Market Share Pre-Acquisition

Share

s

s^2

Server CPU Post Acquisition

Share

s

s^2

Intel

78%

78

6084

Intel

77%

77

5929

AMD

9%

9

81

AMD

8%

8

64

Arm

13%

13

169

Arm

12%

12

144

-

Nvidia

3%

3

9

Total

6334

Total

6146

Source: Nextplatform, Itcandor, Khaveen Investments

Furthermore, Nvidia’s acquisition comes at a time when M&A activity has risen in the semiconductor market with the average deal value rising by more than 5 times since 2015. Should the deal go through, it would make it the most valuable semicon deal in history at $40 bln. Though, larger deals in the past have broken down due to antitrust. Out of 32 of the largest deals since 2015, only 3 major deals above $1 bln have fallen apart representing a 9.3% rejection rate including KLA ( KLAC) and Lam Research ( LRCX) merger, Qualcomm ( QCOM) acquisition of NXP (NASDAQ: NXPI) and Broadcom’s ( AVGO) acquisition of Qualcomm. On the other hand, smaller deals valued at below $1 bln had fewer issues with antitrust. Of the 98 deals, only 4 deals were stopped by regulators which is a 4% rejection rate. This implies that larger deals attract greater scrutiny, which is negative for Nvidia considering it is the highest valued semicon deal.



Source: Design&Reuse

Acquisition Approval Risk

Initially, the expectation of the Arm acquisition deal to go through is by Q1 2022 but subject to regulatory approval from various governmental bodies. There are several arguments that the deal might be delayed or would ultimately fail to get approval. Based on our previous analysis, we highlighted several headwinds that could arise from regulators across various jurisdictions which include:
  • Tensions between the US and China and to protect Arm China against possible intervention by foreign governments in the future
  • The intention for the UK to protect its local industry and prioritize local jobs, technological expertise and intellectual property
  • European authorities seeking to protect companies’ access to advanced technology and preserve sovereignty and independence
While management stated its confidence that the Arm deal would go through as planned, these headwinds may pose a risk for the company to meet its deadline. In the Q2 2022 earnings briefing, Nvidia acknowledged the headwinds in obtaining regulatory approval which is taking longer than initially thought.

We are working through the regulatory process, although some Arm licensees have expressed concerns and objected to the transaction, and discussions with regulators are taking longer than initially thought - Nvidia CFO Colette Kress

A breakdown of the agreement could lead to the company incurring fees related to the failure of the acquisition. A couple of months ago, the deal faced several risks of being delayed as seen with the European regulator’s reluctance to consider the case until after the summer holidays to gather more information. Nvidia is reported to notify the European Commission in early September as the EU is set to launch a formal probe into the deal. Also, the US FTC has been seeking to gather more information while Big Techs including Google, Microsoft, and Qualcomm complained about limiting competition. Whereas in China, the company applied with Chinese authorities but appears to be facing tensions with the axed CEO of Arm China which is challenging the company for unfair dismissal.

It is believed that the agreement allows both companies to extend the deal to Q3 2022 but either party could walk away beyond that. That said, even the deal fails to go through, we believe that the company may be able to realize synergies anyway given its strong product development in the pipeline.

Valuation

The company has had an average revenue growth rate of 29.01% in the past 5 years with average gross and net margins of 61.05% and 28.4% respectively. The strength of its earnings and margins is its increasing margin as a result of lower COGS as a percentage of revenues which declined by 3.9% on average in the past 10 years. In comparison to other chipmakers, Nvidia’s gross margins are higher than the industry average of 47.2% and net margins of 13.2% which highlights its superior pricing power which saw ASPs rising by 25% on average in the past 6 years due to its dominance over the discrete GPU market.



Source: Nvidia, Khaveen Investments

In terms of cash flows, the company’s 5-year average FCF margin is 15.14% and has steadily increased as it grows its operating cash flows. Its margins appear to be volatile due to its investments in marketable securities with an inflow of $6.6 bln in 2019 and an outflow of $10 bln in 2020. However, excluding this, it has very high levels of cash generation with an adjusted average FCF margin of 29.1%. Thus, it is not only saving up for larger acquisitions in the future, but it indicates its solid profitability and earning power which would make it highly valuable even when growth slows down.



Source: Nvidia, Khaveen Investments

Moreover, the company has a strong balance sheet with a debt-to-equity ratio of 0.7x in 2020 with a high EBITDA interest coverage of 114x in the past 5 years indicating its solid ability to repay its debts. In comparison with other chipmaker competitors, its debt-to-equity is significantly lower than the average of 1.35x which highlights its advantage as a fabless chipmaker with a lean balance sheet.

We valued the company based on a P/S valuation due to its superb revenue growth as a rapidly growing company. To determine the appropriate P/S multiple to use, we calculated the average P/S ratio of the chipmakers according to their 5-year CAGR.

Average Chipmaker Revenue CAGR (5Yrs)

PS Ratio

35%+

25.07

30%-35%

22.03

25%-30%

20.00

20%-25%

15.95

15% -20%

11.73

10%-15%

7.52

0%-10%

6.76

Source: SeekingAlpha, Khaveen Investments

Firstly, we forecasted its revenues through 2025 without including Arm based on Nvidia growth in gaming and data center as discussed above. The automotive revenues are projected based on a 22% CAGR derived from its $8 bln automotive pipeline assuming it realizes it by 2025. The professional visualization segment is based on the workstation market CAGR of 9.8% from 2022 through 2025 while the OEM revenues are based on annualized results in 2021.

Nvidia Revenue Forecast Without Arm ($ mln)

2020

2021F

2022F

2023F

2024F

2025F

Gaming

7,759

13,051

16,707

21,386

27,377

35,045

Professional Visualization

1,053

1,782

1,957

2,148

2,359

2,590

Data Center

6,696

9,649

11,727

14,410

17,452

21,298

Automotive

536

654

798

973

1,187

1,449

OEM and Other

631

1,472

1,472

1,472

1,472

1,472

Total

16,675

26,608

32,660

40,390

49,847

61,853

Growth %

53%

59.6%

22.7%

23.7%

23.4%

24.1%

Source: Nvidia, Khaveen Investments

In addition, we previously computed the potential synergies from Arm should the deal go through as planned in 2022. Furthermore, Arm’s revenues are also included in the forecast.

Synergies ($ mln)

2022F

2023F

2024F

2025F

Gaming

742

1,993

4,018

6,327

Professional Visualization

90

205

351

489

Data Center

459

1,406

3,230

5,694

Automotive

25

69

140

207

Total Synergies

1,316

3,673

7,739

12,717

Arm Revenues

2,145

2,280

2,423

2,576

Source: Nvidia, Khaveen Investments

Bear Case

The bear case valuation assumes a 25% probability of the deal going through should the company face challenges from antitrust regulators. Also, the bear case assumes 80% of synergies and Arm revenues would be realized.

Bear Case

2021F

2022F

2023F

2024F

2025F

Nvidia revenues ($ mln)

26,608

33,995

42,265

52,607

65,685

Growth %

59.6%

27.8%

24.3%

24.5%

24.9%

P/S Ratio

25.07

20.00

15.95

15.95

15.95

Valuation ($ mln)

667,068

680,022

674,119

839,081

1,047,673

Number of shares outstanding ('mln')

2,490

2,490

2,490

2,490

2,490

Target Share Price

$267.90

$273.10

$270.73

$336.98

$420.75

Current Share Price

$223.96

$223.96

$223.96

$223.96

$223.96

Upside

19.6%

21.9%

20.9%

50.5%

87.9%

Source: Khaveen Investments

Base Case

Whereas the base case assumes a 50% probability on the basis of its continued progress to complete the deal but also the possible delays due to regulators requiring more information. Also, we assume 100% of synergies to be realised through the acquisition.

Base Case

2021F

2022F

2023F

2024F

2025F

Nvidia revenues ($ mln)

26,608

34,927

43,937

55,534

70,144

Growth %

59.6%

31.3%

25.8%

26.4%

26.3%

P/S Ratio

25.07

22.03

20.00

20.00

20.00

Valuation ($ mln)

667,068

769,432

878,877

1,110,874

1,403,114

Number of shares outstanding ('mln')

2,490

2,490

2,490

2,490

2,490

Target Share Price

$267.90

$309.01

$352.96

$446.13

$563.50

Current Share Price

$223.96

$223.96

$223.96

$223.96

$223.96

Upside

19.6%

38.0%

57.6%

99.2%

151.6%

Source: Khaveen Investments

Bull Case

Finally, the bull case assumes a 100% probability as we believe the acquisition would not lead to greater market concentration but rather a more competitive one as its case for the deal to go through. Also, we assume 120% of synergies to be realised through the acquisition.

Bull Case

2021F

2022F

2023F

2024F

2025F

Nvidia revenues ($ mln)

26,608

36,384

47,078

61,558

79,690

Growth %

59.6%

36.7%

29.4%

30.8%

29.5%

P/S Ratio

25.07

25.07

20.00

22.03

20.00

Valuation ($ mln)

667,068

912,153

941,714

1,356,113

1,594,068

Number of shares outstanding ('mln')

2,490

2,490

2,490

2,490

2,490

Target Share Price

$267.90

$366.33

$378.20

$544.62

$640.19

Current Share Price

$223.96

$223.96

$223.96

$223.96

$223.96

Upside

19.6%

63.6%

68.9%

143.2%

185.8%

Source: Khaveen Investments



Source: Khaveen Investments

Our 1-year average price target for the bear, base and bull case is $270.50, $288.45, $317.11 with an upside of 20.8%, 28.8% and 41.6% respectively.

1-year Average Price Target

Target Price

Current Price

Upside

Bear Case

$270.50

$223.96

20.8%

Base Case

$288.45

$223.96

28.8%

Bull Case

$317.11

$223.96

41.6%

Source: Khaveen Investments

Verdict

To sum it up, the company’s growth prospects are supported by its solid innovative capabilities leading to its AI leadership and GPU performance excellence. Highlighting the advancement of its AI strategy around the data center markets, we believe it can capitalize on the booming cloud growth and increasing capex share to benefit its data center revenues. Additionally, despite the flattish shipment growth, we believe it can continue to grow its gaming revenues highlighting its consistent performance improvement with its next-gen Ampere Next based models. As it advances its AI strategy, it is looking to leverage Arm’s incredible CPU IP across its latest product R&D for the data center for future launches. Compared to our previous analysis, we applied a quantitative P/S multiple to reflect its superb growth outlook as one of the highest in the industry. Based on our valuation model using a P/S multiple, its projected revenue growth rate of 59.6% in 2021 driven by strong growth momentum across gaming and data center segments provides an upside opportunity of 28.8% as its stock price has already increased by 71% year to date. Overall, we rate the company as a Buy with a target price of $288.45.

seekingalpha.com

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From: Frank Sully9/7/2021 8:46:18 AM
   of 2185
 
Birentech launches new GPU line aimed at powering metaverses

Chinese smart chip startup Birentech announced on Sep 6 that it is launching a new GPU product line.

Detail: Co-founder Guofang (Golf) Jiao said Birentech's new GPU will support industries such as gaming, AR, VR, emulation and video, with a focus on the buzzing "metaverse" use cases, such as helping users develop "digital twins". Jiao said that the company aims to fuse hardware with AI software technology in the future.

“Birentech is closer to Chinese markets. Our GPU products will be optimized to accustom to local applications,” said Jiao.

Context: The first batch of 7nm GPU, another product from Birentech is expected to tape out later this year, competing against Nvidia’s next generation Tensor Core GPU.

The RTX A2000 GPU, recently introduced by Nvidia, will help power the Santa Clara-based company's Omniverse, a simulation and collaboration platform, to a wide range of mainstream computers.

AI hardware companies like Birentech and Nvidia have been banking on metaverse, a trendy technology that can be more simply understood as virtual, immersive environments in which users can interact with each other and the world using avatars, or digital twins. Epic Games' popular Fortnite is one prime example of metaverse, in which the company has not only provided regular gaming features, but also developed several non-gaming related interactive use cases, such as one immersive trailer screening event for the sci-fi movie Star Wars: The Rise of Skywalker.

en.pingwest.com

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From: Glenn Petersen9/7/2021 6:17:04 PM
   of 2185
 
UiPath stock falls following earnings beat, outlook hike

Last Updated: Sept. 7, 2021 at 4:25 p.m. ET
First Published: Sept. 7, 2021 at 4:21 p.m. ET
By Wallace Witkowski Follow
MarketWatch



UiPath reported second-quarter earnings Tuesday. UIPATH
--------------------------------------

UiPath Inc. shares fell in the extended session Tuesday even as the “software robots” provider topped Wall Street estimates and raised its outlook for the year.

UiPath PATH, -1.44% shares dropped 6% after hours, following a 1.4% decline in the regular session to close at $62.46. Following UiPath’s first earnings report as a public company about three months ago, shares fell the next day.

The company reported a second-quarter loss of $100 million, or 19 cents a share, versus net income of $5 million in the year-ago period. Adjusted earnings, which exclude stock-based compensation expenses and other items, were a penny a share, compared with 3 cents a share in the year-ago period.

Revenue rose to $195.5 million from $139.4 million in the year-ago quarter. The company’s annualized renewal run rate, or ARR, rose 60% to $726.5 million from a year ago. ARR is a metric often used by software-as-a-service companies to show how much revenue the company can expect based on subscriptions.

Analysts surveyed by FactSet had forecast a loss of 5 cents a share on revenue of $184.3 million and an ARR of $703.8 million, based on UiPath’s forecast revenue of $180 million to $185 million and ARR of $702 million to $704 million for the second quarter.

UiPath forecast revenue of $207 million to $209 million and ARR of $796 million to $798 million for the third quarter, while analysts expect revenue of $205.8 million and ARR of $776.8 million.

For the year, UiPath expects ARR between $876 million and $881 million, up from a previous forecast of $850 million to $855 million. Analysts estimate $854.8 million.

UiPath’s stock made its debut on the New York Stock Exchange back in April. As of Tuesday’s close, shares are about 12% above their IPO price of $56 a share.

UiPath stock falls following earnings beat, outlook hike - MarketWatch

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