I was excited when I learned that a new business laptop had a removable battery, a decent graphics card, and 1tb storage standard. I planned to buy it used for a fraction of its current price, 2k usd new, once some doofus got bored of underusing their machine and decided to trade up. Then I saw the AI chip and my desire wavered. You think there will ever be workarounds to make use of this garbage? I really want that removable battery.
A CUDA core is just a vector processor like every GPUs since the late 90s has been made of, but with a different name so it sounds special. It doesn’t just run CUDA, it runs everything else a GPU has traditionally been for, too, and that was stuff people were doing before CUDA was introduced. There are lots of tasks that require the same sequence of operations to be applied to groups of 32 numbers.
An NPU is a much more specialised piece of hardware, and it’s only really neural network training and inference that it can help with. There aren’t many tasks that require one operation to be applied over and over to groups of hundreds of numbers. Most people aren’t finding that they’re spending lots of time waiting for neural network inference or draining their batteries doing neural network inference, so making it go faster and use less power isn’t a good use of their money compared to making their computer better at the things they do actually do.
I was excited when I learned that a new business laptop had a removable battery, a decent graphics card, and 1tb storage standard. I planned to buy it used for a fraction of its current price, 2k usd new, once some doofus got bored of underusing their machine and decided to trade up. Then I saw the AI chip and my desire wavered. You think there will ever be workarounds to make use of this garbage? I really want that removable battery.
That NPU is a math coprocessor. It can be very useful. It’s like a cuda core.
A CUDA core is just a vector processor like every GPUs since the late 90s has been made of, but with a different name so it sounds special. It doesn’t just run CUDA, it runs everything else a GPU has traditionally been for, too, and that was stuff people were doing before CUDA was introduced. There are lots of tasks that require the same sequence of operations to be applied to groups of 32 numbers.
An NPU is a much more specialised piece of hardware, and it’s only really neural network training and inference that it can help with. There aren’t many tasks that require one operation to be applied over and over to groups of hundreds of numbers. Most people aren’t finding that they’re spending lots of time waiting for neural network inference or draining their batteries doing neural network inference, so making it go faster and use less power isn’t a good use of their money compared to making their computer better at the things they do actually do.