I’m showing my age here, but much like we had math coprocessors running beside the 286 and 386 gen CPUs to take on floating point operations; then graphics cards offloaded geometry-based math operations to GPU’s - are we looking at AI-style die or chips to specifically work on AI functions?
Excuse my oversimplification, this isn’t my field of expertise!
They already have dedicated hardware they call the neural engine, and use for coreML, ARKit, some of the magic they do to turn terrible sensors and lenses into passable images, etc. There’s a lot of processing that already happens on your device. Being able to search your images by subject might be something Google does too, but Apple does it locally.
So my guess is they’ll just adjust the architecture of the neural engine to accommodate any new requirements, rather than adding a “new core”. But it’s kind of all semantics. There will be new hardware components and intercommunication at a low level.
Well, your not too off. Like ASICs are made for mining cryptocurrency. Specialized processing designed for specific computations. This indeed make it’s efficiency greater than a general purpose CPU.
Awesome, thanks for the insight.
I’m showing my age here, but much like we had math coprocessors running beside the 286 and 386 gen CPUs to take on floating point operations; then graphics cards offloaded geometry-based math operations to GPU’s - are we looking at AI-style die or chips to specifically work on AI functions?
Excuse my oversimplification, this isn’t my field of expertise!
They already have dedicated hardware they call the neural engine, and use for coreML, ARKit, some of the magic they do to turn terrible sensors and lenses into passable images, etc. There’s a lot of processing that already happens on your device. Being able to search your images by subject might be something Google does too, but Apple does it locally.
So my guess is they’ll just adjust the architecture of the neural engine to accommodate any new requirements, rather than adding a “new core”. But it’s kind of all semantics. There will be new hardware components and intercommunication at a low level.
Apple added (a while back) what they call a “Neural Engine,” which is hardware dedicated to efficient execution of ML workloads.
https://en.m.wikipedia.org/wiki/Apple_A11
They have been refining it ever since. I would not be surprised if they made advancements in both the hardware and software used for local GAI.
And Google did the same with the Tensor Processor Unit in the Pixels.
Well, your not too off. Like ASICs are made for mining cryptocurrency. Specialized processing designed for specific computations. This indeed make it’s efficiency greater than a general purpose CPU.
Yes!
not a dedicated chip per se, the trend is to build it directly into the SoC (mobile devices) or the dedicated GPU