For the longest time they have encouraged people to use Geforce cards for doing machine learning. Now they are changing the licensing and making it not okay for data centers is not gonna sit well with people. Especially with the carveout for Bitcoin miners. The number of customers who are impacted like the article points out will be mainly universities. This is bad move overall and isn't gonna gain them any good will with the community. Like seriously how many companies are out there are putting out Geforce cards into data centers? The big data centers from cloud computing platforms all use Tesla cards.
The exemption makes it even more ridiculous, not only do they want to restrict where you can use the software but they also want to have a say in what kind of applications you can use their software for.
This besides the fact that Bitcoin on GPUs is fairly dead, it's almost entirely done on ASICs now.
If you read the license agreement it states that the term applies to 'blockchain processing', not to bitcoin specifically.
There are a number of "alt-coins" (blockchain-based cryptocurrencies other than bitcoin) designed to be "ASIC-resistant" e.g. by using the Lyra2REv2 algorithm.*
This is notably the case of Monero and Monacoin, two popular cryptos in Japan. Generally, the Japanese and Koreans are very enthusiastic about cryptocurrencies in general.
Cryptocurrency GPU-mining on Tesla cards would be outright unprofitable.
These facts may contribute to Nvidia's decision not to displease Japanese GPU miners specifically.
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* This is to avoid big ASIC farms as is the case of bitcoin (apparently, more than 70% of bitcoin's hash rate comes from China, most notably from a specific valley where electricity is dirt cheap). One purpose of ASIC-resistance is to maintain a high-enough degree of decentralization in mining, which increases security for the network/blockchain.
$20,000 btc can make mining on gpu's potentially profitable again, more so as the price goes up. If the price holds the 6 months or a year it takes to mine one is another matter entirely :)
Here's a figure on the scale-out you can get on the DeepLearning11 server (cost $15k) - it's about 60-80% of the performance of a DGX-1 for 1/10th of the price (for deep ConvNets and image classification, at least).
I think this is because they want people to use Titan V workstations. They know that the Titan V will cannibalize Tesla sales of they let people put them in data centers. It's still a shady move, but it makes sense.
