This is like the anime hero/villain (depending on your perspective) equivalent of fighting at half power.
627 karma · joined October 11, 2013
This is like the anime hero/villain (depending on your perspective) equivalent of fighting at half power.
They never even looked at First Sale Doctrine which is a possible defense in this type of dispute.
If you translate this too books then the book itself is the tangible medium. Scans are infringing copies and only valid for personal use.
[1] https://en.wikipedia.org/wiki/Capitol_Records,_LLC_v._ReDigi...
[1] https://www.kernel.org/doc/Documentation/vm/soft-dirty.txt
Now the Moore's is basically at its end and x86 is partially stagnating, at least from Intel, other platforms like ARM are gaining traction and it seems like a good time to revisit VLIW.
I think another key factor is that most applications now run on top of platforms/frameworks rather than at the native level. This means you only need to port Linux, the JVM, node, python, and a few others and you captured a pretty large potential audience. Compare this to the mid 00's when moving to Itanium meant porting all you native apps.
Companies have tried to create Just In Time (JIT) media services that return digital items to a pool when you are not actively using them. This essentially creates micro loans with a time span of minutes to hours.
I can't remember the name of the company that was attempting this but they were shutdown due to a copyright lawsuit.
EDIT: They actually mention the company in the FAQ. ReDigi lost their lawsuit [1].
[1] http://www.ca2.uscourts.gov/decisions/isysquery/68b0f5b0-959...
[1] https://www.newsweek.com/h-1b-visa-row-foreign-workers-make-...
1. The runtime api (libcudart.so)
2. The driver api (libcuda.so).
The driver api is very close to the opencl api and is very low level. Most people use the CUDA runtime api which is vastly more convenient. The main difficulty with OpenCl and the driver api is that you have to manually load GPU code onto the device which then returns a handle. You generally have to load the code onto every device which means multiple handles for the same function. This makes executing kernel quiet a lot of work. The runtime api does this all automatically which make programming with CUDA quiet easy since launching a kernel is basically a function call. The CUDA rutime also automatically handles context creation which is another time saver.
When I first learned OpenCL I was shocked at how difficult is was to simply write a simple vector add program since there was all this additional code loading, creating contexts, etc. The setup / boiler plate was greater than the actually code itself.
It basically boils down to convenience in my opinion. Couple this with the fact the NVIDIA generally has the most powerful and energy efficient cards and it's no surprise they took the market.
[1] https://en.wikipedia.org/wiki/Energy_East
ADDENDUM: The amount of rail accidents in Canada is shockingly high. Multiple per day [2].
[2] http://www.bst-tsb.gc.ca/eng/stats/rail/2018/sser-ssro-2018....
> In 2000, the first long-acting synthetic insulin was approved by the U.S. Food and Drug Administration.
Looks like it will still be at least another year before a viable generic enters the market.