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Comment by johansch | Hacker News Reader

This is pure and utter bullshit. Their core market is by far gaming, as this PDF (that I found via NVidia IR) shows:

http://files.shareholder.com/downloads/AMDA-1XAJD4/341168899...

Also: The level of their gross profit margin indicates that they are in fact a monopolist:

http://marketrealist.com/2016/11/driving-nvidias-profit-marg...

(These are not the financials of company operating in a healthy, 20-year old industry - they are the financials of a company that after operates without meaningful opposition in a 20 year old business.)

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Nvidia isn't a monopolist. They have two big competitors in AMD and Intel.

Intel ship about 2/3 of the graphics chips for laptops and desktops. Nvidia have more than half of the remainder. That isn't a monopoly.

In the discrete GPU space AMD are also there and ship almost half as many unit as Nvidia. That's no monopoly.

The graphics systems for the current consoles are shipped by AMD aren't they?

Nvidia is a profitable company. Calling them a monopolist because they are profitable is unwarranted.

* Edited to fix grammar.

AMD ships primarily low and mid range cards, NVIDIA has an effective "monopoly" in the enthusiast market share which has the highest profit margins by far.

That said AMD hasn't managed to ship a 350-400$+ card that's worth spending money on compared to the competition since probably the 7950...

That's a ridiculous definition of a monopoly. Using that methodology, you can claim any company has a monopoly that happens to have the best performing thing at the time.

Nobody is claiming Tesla has a monopoly on electric cars because they make the best. And nobody should claim Nvidia has a monopoly on GPUs since they are on top.

I didn't claim they had a monopoly, I said they had an "effective monopoly" in only one, albit very critical market segment, in which they ship over 75% of the hardware.

Regarding the effective monopoly on high end, this will change next month with release of Vega card.

I wouldn't hold my breath, the 1080 TI is coming out and NVIDIA would just drop the price on the 1080, they've done pretty much exactly the same thing with the Fury.

And AMD will have again a very expensive card to manufacture GDDR5/5x vs HBM2 with high power consumption based on the fact that the RX480 draws nearly as much power as a 1080 atm, and HBM2 isn't exactly power efficient (unlike HBM1 vs GDDR5), HBM2 is nice but the power requirement currently increase with the density, and it leaks voltage pretty badly with 4 stacks...

OK, by revenue, sure. But calling it "pure and utter bullshit" is probably going a little far, don't you think? (Where is the line item for "AI"? Datacenter and Auto? Not to mention many "gaming" cards are more than sufficient for "AI" if you don't need 64bit FP.) Intel has been hammering at the GPU screw for more than a decade and by all rights, they still haven't figured out how to use a screwdriver (to use Huang's characterization of Intel's approach).

Nvidia, meanwhile, has built a massively parallel beast that's still decent at gaming. But make no mistake; their engineering priorities are set on general parallel computation. Gaming performance is in many ways a similar problem, and thus benefits, but it would be a mistake to think games still come first for their engineers.

Not quite the right conclusion.

Many of Nvidia's "gaming" cards (e.g., higher-end GTX cards) are in fact used NOT for gaming but for deep learning by numerous AI researchers, developers, and startups with small budgets who buy them through retail channels.

That's indeed possible. But really, if you were to guesstimate the ratio of GPU usage between these items sold to consumers that end up being used by:

a) AI/startups

b) gamers

what would you guess?

My guess is somewhere between 1:50 and and 1:500.

The difference is that AI/startup users may buy hundreds of GPUs at once.

I think he is already including that in his 1:50 or 1:500 ratio.

Indeed.

Revenue growth is far more interesting to tech investors than revenue over the last few years. Deep learning has a massive potential for revenue growth and total revenue will likely eclipse gaming within the next 10 years.

Imagine a world where every car has semi-autonomous technology, the average security camera is doing object detection, localization, more sophisticated language translation, smart drones, etc. The potential for deep learning is undeniable and Nvidia (currently) is leading this race.

Except that you mainly need the massive compute for the training, not the commodity execution of the network!

Any idea what kind of compute a self-driving car(with a trained network) will need ?

Depends massively on what the software is doing, there is still no standardisation on what a self-driving car means.

Nvidia is pushing PX2 but I have a feeling they are too expensive for most cars - don't know the exact price but "a few thousand dollars" was quoted for the Teslas that use them. Some specs - http://wccftech.com/nvidia-drive-px2-pascal-gtc-2016/

At the same time Qualcomm is pushing their much less performant chips for self-driving cars, but at a much lower price point (hundreds of dollars)

Something pretty close to this: http://www.nvidia.com/object/drive-px.html (I believe they are currently recommending the 4 GPU version shown on at the bottom of that page under "DRIVE PX 2 FOR FULLY AUTONOMOUS DRIVING")

The key here isn't that this isn't a full power desktop GPU, but it will run inference on a CUDA-compatible kernel.

That give NVidia a complete end-to-end modelling, training and driving platform. No one else has that.

Surely you don't expect cameras and drones to have massive, loud, heavy, power draining, $650 dollar graphics cards in them?

It seems if they are used in development the sales don't scale anywhere near directly with the number of units sold.

Maybe I'm missing something?

Not now, but in the future. Nobody thought we could fit desktop-class graphics cards into slim laptops, but that's a reality today. Though drones will probably go for custom chips.

http://www.nvidia.com/object/drive-px.html

Their data centre revenue is 20% of their gaming revenue. That's a significant business.

Exactly, and there are ample rooms to grow. Compared to Gaming.

I see datacenter revenue estimated to go from 7% to 15% in 2 years. If deep learning continues to grow datacenter revenue will likely exceed gaming revenue. Depending upon competition and long term growth gaming revenue could become just a footnote.

I think they also count Titans as a gaming item, and server vendors dont offer them. So all the people doing DL with Titans probably are in the gaming category.

Or any number crunching application?

What is with their gaming and datacenter revenue being expected to grow 60% in Q3 FY17?

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