Quotes About CPU

All of these technologies that we are putting together... our memory technology, our CPU, our graphics architecture, our GPUs - all that is being applied to where the data is. You can almost predict where Intel will be in the future. It will be where data resides.

Power, of course, is very important, but really, there's a bundle of technologies you have to have to make sure they're highly integrated, so you have to have modem, you have to have connectivity, you have to have GPS, you have to have graphics, you have to have CPU.

If you look back over the history of computing, it started as mainframes or terminals. As PCs or work stations became prevalent, computing moved to the edge, and we had applications that took advantage of edge computing and the CPU and processing power at the edge. Cloud computing brought things back to the center.

Doing processing locally has its advantages. For instance, the cost of an endpoint CPU and memory is a 1000x cheaper than the cost of CPU and memory in the server. And in many places around the world, connectivity and transmission costs are sometimes far more expensive than the device.

It is difficult to make good scalable use of a CPU like you can of a graphics card. You certainly don't want 'better or worse' physics or AI in your game

Conceptually, we believe that embedded mining will ultimately establish bitcoin as a fundamental system resource on par with CPU, bandwidth, hard drive space, and RAM.

The speed at which modern CPUs perform computations still blows my mind daily.

Since the 1980s, Intel has specialized in a type of chip called a CPU, a central processing unit, of which a microprocessor in a PC is one example. These are the chips that serve as the "brain" in a computer or data center. They are general-purpose workhorses, equally capable of opening a web browser or running Microsoft Excel. They can conduct many different types of calculations, which makes them versatile, but they do these calculations serially, one after another.

Where a CPU would feed an algorithm many pieces of data, one after the other, a GPU could process multiple pieces of data simultaneously. To learn to recognize images of cats, a CPU would process pixel after pixel, while a GPU could "look" at many pixels at once. So the time needed to train a computer to recognize cats decreased dramatically.

possible to run any AI algorithm on a general-purpose CPU, but the scale of computation required for AI makes using CPUs prohibitively

To learn to recognize images of cats, a CPU would process pixel after pixel, while a GPU could "look" at many pixels at once. So the time needed to train a computer to recognize cats decreased dramatically.

To me, it's always a joy to create music no matter what it takes to actually get there. The real evils are always whatever stops you from doing that - like if your CPU is spiking and you have to sit there and bounce all your MIDI to audio. Now that's annoying!

Turing proved, mathematically, that if you choose the right set of rules for the CPU and give it an indefinitely long tape to work with, it can perform any definable set of operations in the universe. It would be one of many equivalent machines now called Universal Turing Machines.

A CPU is just a collection of logic gates.

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