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Show AI Ratings for: Market Intelligence Special Report: NVIDIA, Giacomo Bonavera, London, June 14h 2019 is the leading research, advise and market intelligence provider for financial institutions in the area of Artificial Intelligence. As an independent authority classifies the AI market and constantly monitors 11.000+ companies in the field of Artificial Intelligence. issues Market Intelligence Special Reports to different topics about the AI industry.

NVIDIA (NASDAQ: NVDA) share price slumped to half the value from its last year highs. While the top executives try to give reasons for the depression, we look deeper and find the real reasons that caused revenues to crash in the recent quarters.

NVIDIA reported revenue declines of 31% from a year ago for the first quarter ended April 28, 2019, to $2.22 billion compared with $3.21 billion from a year ago and $2.21 billion in the previous quarter.

Founder & CEO of NVIDIA, Jensen Huang had this to say, “NVIDIA is back on an upward trajectory, we’ve returned to growth in gaming, with nearly 100 new GeForce Max-Q laptops shipping. And NVIDIA RTX has gained broad industry support, making ray tracing the standard for next-generation gaming.

“Despite the near-term pause in demand from hyperscale customers, the application of AI continues to accelerate. AI adoption is accelerating in the world’s largest industries, moving beyond the cloud to the edge where AI processing has to be instantaneous. We’re excited about our pending acquisition of Mellanox, which will help us drive data center architecture for high performance computing and AI from the cloud to the edge,” he said.

Let us unpack that by looking at the revenue by reportable segments of NVIDIA:

GPU Business. GPU business revenue decreased by 27% in the first quarter of fiscal year 2020 compared to the first quarter of fiscal year 2019, which reflects declines in gaming GPU and data center revenue, as well as the absence of $ 289 million of revenue from cryptocurrency mining processors.

GeForce GPU product sales for gaming decreased 28%. Data center revenue, including Tesla (not to be confused with the electric car manufacturer), GRID and DGX, decreased 10%, primarily reflecting a slowdown in certain hyperscale and enterprise customer purchases, partially offset by growth in inference sales.

Revenue from Quadro GPUs for professional visualization increased 6% due primarily to higher sales across desktop and mobile workstation products. The PC OEM revenue decreased by 78% primarily driven by the absence of cryptocurrency mining processor sales.

Tegra Processor Business. Tegra Processor business revenue decreased by 55% for the first quarter of fiscal year 2020 compared to the first quarter of fiscal year 2019 . This was driven by a decline in shipments of SOC modules for gaming platforms, which was only partially offset by an increase of 14% in automotive revenue, primarily from growth in AI cockpit modules.

There is quite a big gap between saying “NVIDIA is back on an upward trajectory” and “the application of AI continues to accelerate” when revenues in all reportable segments plunged between a quarter and three quarters.

To say “we’ve returned to growth in gaming, with nearly 100 new GeForce Max-Q laptop shipping” must mean they returned to growth from a very low base because a laptop with the best GeForce Max-Q graphics chip in it retails on Amazon for between $1800 and $2900. If that was the bullwhip Kevin Cassidy of Stifel was referring to in a written report that “Nvidia likely cleared out channel inventories in the quarter for its graphics processing units for gaming”, then the slack in the logistical pipeline couldn’t have been too big. But let’s not forget, Kevin Cassidy reiterated a ‘Hold’ rating on Nvidia last year which must mean he was holding some of the stock in his portfolio.

To see the problems that Nvidia’s stock plunge since early October is causing for its shareholders, look no further than Softbank.

Softbank has drawn headlines during the past year for its ambitious Vision Fund, a massive $100 billion fund engineered by CEO Masayoshi Son. The fund has invested in a number of tech companies—including Nvidia, WeWork, Uber and Slack. The idea behind it was to get in early on companies that will be reshaping technology for the next 100 years.

According to Bloomberg, Softbank is considering selling off some or even all of its stake in Nvidia early next year—more than 98 years short of its 100-year vision. Softbank reported that the valuation of its Vision Fund in the September quarter had increased by ¥504 billion ($4.5 billion) year over year, with much of that increase due to its investment in chipmaker Nvidia. Since Oct. 1, however, Nvidia has lost 50% of its value, potentially delivering a blow to the Vision Fund that its biggest investors, notably sovereign funds in the Middle East, may not welcome.

All of the top AI ETFs including BOTZ, ROBO, ROBT, IRBO and UBOT have weightings in NVIDIA and all of those ETFs have slumped. So can it be said that the AI ETFs that financial market investors are using as benchmarks are a true reflection of the AI market?


VCs invested more than $1.5B in chip startups in 2017, nearly doubling the investments made two years ago. There are at least 45 startup chip companies focused on NLP, speech recognition, and self-driving cars. Silicon Valley startup Cerebras and UK’s Graphcore are quietly working on bots that can carry on conversations and systems that can automatically generate video and virtual reality images. Not only do these newcomers have strong backing by leading VCs, but they have also been on an active hiring spree, cherry picking key executives from many of the older and established chipmakers. Cerebras has hired dozens of engineers from Intel, notably bringing in its CTO from Intel’s Datacenter group. Graphcore was founded by semiconductor veterans who have founded multiple startups in the past, including Icera, a mobile chip company, which was sold to Nvidia in 2011 for $376M. Another promising startup, SambaNova, which was funded by Google Ventures and co-founded by an Oracle veteran and professors from Stanford, is working on solutions to integrate hardware and software to maximize the performance and efficiency of AI chips.

With such a crowd of innovators focused on a single target, new innovations are expected to continue to accelerate at a rapid clip. Perhaps the biggest differentiator on deck at the moment is the development of key software that is tightly incorporated into single solution sets. So far, Nvidia appears to have the clear advantage, and its equally weighted software and hardware development teams reflect the importance of software integration in the next generation AI chip sets. But with each new advancement comes the opportunity for new leaders of the pack, and the specialization of AI chips for different segments is already evolving faster than most analysts had expected. As each of these companies fights for its share of this $35B chip market opportunity, watch for accelerating M&A activity—and more opportunities for investors in every area of the space., September 9th 2019, Alexander G. Welzl

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Competence in Artificial Intelligence

Rigourous systematic.

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