Micron vs Invidia by the numbers

Numbers as shown on Seeking Alpha

                MU   vs  NVDA
EV            55.7 B vs 122.5 B
Trail P.E       7.21 vs 53.45
P:Cashflow       4.9 vs 44.2
Rev           23.2 B vs 9 B
Rev Growth     77.9% vs 46.2%
EV/Sales        2.40 vs 13.64
Net Income     7.6 B vs 2.6 B
EPS             6.35 vs 4.03

I don't get it.  Comparing Apples to Pizza? Can someone help me understand?


I think it might be an apples to pizza comparison. My read is (more or less)…
Micron is a chip producer, which people read as “boring”, “commodity”.

Nvidia is a component producer, and ‘the’ important player in big growth industries, Gaming and AI.

AI encompasses pretty much everything thats interesting in Tech at the moment, automated vehicles, inference, neural networks, ML etc, which people read as “big growth areas”.

It might help to think about a concrete example, an autonomous vehicle. You’ve got to have a car-brain, which understands how to navigate the real world, lots of complex rules, huge amounts of research and programming and training, all built on top of the ‘brain’. So the brain is pretty critical and in particular, the tool sets required to train the brain.

So if you’re the manager on that project, you’re probably going to choose the company thats focussed on that particular problem, and can arguably demonstrate the worlds best tool, but more importantly, the ‘best’ framework (CUDA).

Now, if you need some more memory, you can switch out suppliers with basically no thought. Micron? Ok. Samsung? Sure! etc. Switching out the brain however… that becomes very very difficult. And as far as I can tell… theres no real alternative.

CUDA seems (and I don’t work in the field) the default framework for AI work. Its well supported, well liked and as far as I can tell, unique (in its depth and support). And importantly… proprietary. If you’re working in this field, you’re most likely working on CUDA/Nvidia.

So Nvidia is seen as the default build platform for the fastest growing (and arguably most important) tech trend for the foreseeable future.

In my view, its less about the fundamentals than about the huge amount of momentum that Nvidia has in its AI division. In order for another company to succeed in that space, they would have to convince all the developers and researchers currently learning/using CUDA to switch to their alternative. And… what incentive could they give? Cheaper? No-one cares. Less power consumption? Maybe. Easier? See “no silver bullet” [https://en.wikipedia.org/wiki/No_Silver_Bullet]

Long NVDA (for reasons above), less long Micron (because chips will swamp the world)


Greg did a good job.

As DavidG would say, Multiple Possible Futures .

Micron make memory, not many options there. China just announced it wants to become a world leader in fiber optic components. That’s not hard, they will succeed. Stocks like LITE and OCLR dropped on the news. What if they want to become a top 5 memory producer.

On the other and NVDA has amny options:
Gaming - sounds boring, but eSports is growing at the amatuer and professional level
CrypoCurrency Mining - For intense crypto like Bitcoin, the GPUs are a goto chip for mining and processing transactions. AMD is a competor, but I think NVDA is winnig.
Machine Learning - it is a small part of revenue, but growing. We will see more of this and AI going forward and NVDA is the leader
AI the more generic umbrella over machine learning. Again, the nvda chips are the leaders in a growing market. A seemingly unlimited markets
data centers - this is where a lot of AI and Machine learning takes place, but I think they also used for other data center number crunching purposes. They are much fast and lower power than Intel chips.
Autonomous Vehicles - cars, trucks, busses, trains, metros, personal errand robots, military vehicles, etc. Could be a huge market. You need NVDA up front for learning then onboard for the driving.

Other futures? I don’t know, improved robotic surgery? Holograms for long distance communication? Smarter drones? AI cybersecurity and real-time analysis?

In one of the RBI broadcasts, David played the “would you rather game”, as in would you rather have a technology company run by a brilliant and visionary CEO or a CEO that is a great businessman. The them of the podcast was actually, “you can have both”, and that is what you get with NVDA.

Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.


Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.


Plus, news stories like these all the time…

Nvidia Chief Executive Jensen Huang announced new deals with Volkswagen (VLKAY), Uber, ZF and Baidu (BIDU). In total, Nvidia is now collaborating with more than 320 companies on self-driving car and truck initiatives worldwide, including carmakers, auto parts suppliers and information technology firms.

Nvidia showed off its Xavier autonomous-machine processor, which is capable of deep learning, computer vision and high-performance computing at highly efficient levels, Huang said. The first samples of the processor are being delivered to customers this quarter, he said.

“In the future, every car will be self driving,” Huang said. "There will be 100 million cars built each year, millions of robotaxies and several hundred thousand trucks.

The Nvidia autonomous vehicle announcements show the “unique value of its product road maps, integrated systems, software stacks and software development kits,” B. Riley FBR analyst Craig Ellis said in a note to clients Monday. He reiterated his buy rating and price target of 270.

At the CES event, Nvidia also announced two software development kits for artificial intelligence and augmented reality in vehicles.

Ride-sharing service Uber has selected Nvidia technology for the AI computing system in its fleet of self-driving vehicles, Huang said.

Nvidia’s Huang said the company is involved in some of the hottest technology areas being discussed at CES 2018, which officially opens on Tuesday. Those areas include AI, video games and autonomous vehicles."

But those cars might have some micron memory in them :wink:


Not to mention that it takes a long time and a lot of money ($Billion$$$) to bring a factory on line in the memory business and the price of your product swings based on the balance or in balance of supply and demand. Right now there is a shortage, (and high prices) but two of your competitors are bringing additional factories online, and it may, or may not tip the scales from shortage of your product to oversupply.

And based on the average selling price of the major competitors MU gets the least per chip sold. Hard to say if their product is inferior, or their sales staff. Either way, it points to an issue that needs to be addressed.

You need to figure in all that convertible debt on the books, and what it may do to EPS.

And lastly, Nvidia is a market leader in their area. MU is in third place, and its competitors are substantially bigger, which means they have more R&D money to splash around. R & D that could change the game, not in favor of MU.


Small long in MU, Big long in Nvidia

1 Like