Nvidia

Chips Ride Atop the Leader Board, Part 1

volume xvii issue 2

Semiconductor manufacturing is the most complex industrial feat we take on as a species - worldwide.  Modern microprocessors are incredibly complex housing more than a billion transistors, each about .02% the width of a human hair.

Semi (chip) manufacturing seemed until a few years ago, to have matured, enjoying plenty of worldwide building capacity despite the investment and technology challenges.  But then the industry suffered brutal price competition for central processing units (CPU's) and memory chips as the business commoditized.

Due to the continuing evolution of the Internet and the ability to merge software with chips, manufacturers again have the ability to create economies of specialization, allowing suppliers to set prices in certain markets.

Look at a company like Intel whose stock price showed a secular bear market pattern - lower highs followed by lower lows - for a decade.  Intel suffered the tech bust in 2000 and it was 2009 until it seemed to turn a corner.  An extended period of low interest rates certainly goosed capital and R&D spending.  Intel both designs and builds chips.  The foundry business is extremely capital intensive.

Now we have a growing list of ‘fabless’ semiconductor companies who design the chips and outsource some or all the manufacturing to the foundries.  I have long held the belief that the day would come when semiconductor companies could cheaply burn applications onto chips, shorten the manufacturing cycle, and better control inventory pushed into the supply chain.  And that's exactly what's happening.

Nvidia (NVDA:NASDAQ) is the Wall Street darling in the space of bit-level processors, up 600% in five years, 200% last year alone.  Remember when Nvidia was the graphics card you bought for your PC with a special chip that made the monitor look great without slowing it down?  Pre Dell, XBox, eBay and Amazon, you bought the card and the games from ComputerLand, Radio Shack or Best Buy, wherever you would go to buy a PC.  You controlled the game from your keyboard, maybe you bought a joy stick.

Guys who worked for me when I ran a help desk at a large financial firm in 1995, figured out how to group-game on the Ethernet behind our firewall.  Our workstations were video enabled for bit-mapped graphics.  They thought that I didn't know, but I allowed it and the network administrators never caught on.  Now these chips are capable of heavy duty bit flipping for lots of high performance computing applications.  No longer a chip on an insert-able card, it is called a Graphics Processing Unit (GPU) and can run alongside the CPU as a dual processor to make servers run faster.

Nvidia has transformed from a special-purpose semiconductor company for games and graphics, to one that can build general-purpose processors, like a CPU.  NVDA would rather call their solutions a platform, offering a suite of chip-enabled applications.  The marketing slant is in their pubic presentations and financial reports.

The thing that has really changed our company, what really defines how our company goes to market today, is really the platform approach, that instead of just building a chip that is industry standard, we created software stacks on top of it to serve vertical markets that we believe will be exciting long term that we can serve. And we find ourselves incredibly well positioned now in gaming, in AI and in self-driving cars.
NVidia CEO Jen-Hsun Huang

Bank of America Merrill Lynch (BoAML) published a Semiconductor Playbook in January and it is convincing that NVDA has leadership - as in top of the heap - with these chip applications:  PC gaming (still 60% of NVDA revenue with an 18% CAGR), Artificial Intelligence (deep learning), AI for self-driving and co-piloted cars, and a budding Virtual Reality (VR) business.

Beyond the predictable cash flow from the gaming business, if just one of these new businesses blooms and NVDA sticks to a fabless model, they win.  Regardless of competition that validates their markets, they are first to the dance with a meaningful customer base and financial commitment, and negligible CapEx.

Artificial Intelligence is the biggest wager in bit-level computing per Goldman Sachs, who sees the current addressable market at $5B - $10B in annual sales.  Compare these estimates to total annual sales in the semiconductor industry at $350B.  That is a lot of headroom.  As of the third calendar quarter 2016, Goldman Sachs estimates there are about 1500 AI startups worldwide, nearly all running the applications in the cloud.  AWS, Azure, and IBM Cloud are favorites to house co-processors with burned-in apps, designed to easily scale along with CPUs in data centers.  Startups fuel the bleeding edge innovation, venture capital, private equity investment and M&A pipeline.

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