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Comment by matt4711 | Hacker News Reader

I thought the NVIDIA drivers for the more fancy cards (TITAN etc) are the same as for the gforce cards. Wouldn't this restriction apply to those cards as well? Doesn't make much sense to me...

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They can't price-differentiate FP64 compute out, since ML uses FP32 or even FP16. They tried discriminating FP16 performance but frameworks switched to using FP32 units and downconverting to FP16 after. They can't kill FP32 performance since that's used for gaming. They tried killing the virtualization, they tried differentiating based on clustering, they tried every reasonable technical procedure. So now they're falling back to legal means, to defend an artificial price distinction that has no reflection in card features that anyone cares about.

In the future, Teslas will have Tensor Cores and GeForces won't, so deep learning will be much faster (but also much more expensive, so it kind of cancels out) on Tesla cards.

Yeah, doesn't it seem a little weird that they seem to want to enforce the distinction between gaming and industrial cards, but they also went ahead and included tensor cores in that new Titan card?

Did they not think that through and have an 'oh shit' moment when they saw all the news articles or something? Or is this a 'the first hit is free' sort of deal where they want people to learn about using the product on a startup budget, without giving up the ability to squeeze if someone has a good idea and wants to scale?

Titan V is so expensive that it's not cannibalizing anything. Once the GeForce 1180 comes out... they'll make it just slow/expensive enough that it still doesn't cannibalize anything.

They did take the "GeForce" label off of the new Titan. And the 1180 might not have any tensor cores at all.

Are you sure that they won't do it? Did they mention it somehow?

AFAIU, tensor cores are just super efficient matrix operations, and they might super useful in gaming applications, for example, physics engines.

They have just released the new Titan V, which has Tensor Cores I believe. That would indicate that they do want to include them in non workstation/dedicated ML cards, no?

Except that they dropped the GeForce branding from the Titan V, and appear to be targeting the card for compute at developers/researchers [0].

[0] https://nvidianews.nvidia.com/news/nvidia-titan-v-transforms...

The Titan V is a compute card, the same way the Titan XP and Titan Xs were. Differing factors between them and the xx80[Ti] of the corresponding generation were memory bandwidth and capacity - gaming performance was nearly identical to the geforce. Titans are entry-level compute.

That is probably the point.

They want to sell two fungible products while enforcing a pricing hurdle so that certain types of customers have to pay much more for the same performance.

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