Apple Is Working on a Dedicated Chip to Power AI on Devices
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Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#2Is this a real IC/processor for arbitrary software or an abstraction of an underlying GPU/DSP?
Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#3> . The chip, known internally as the Apple Neural Engine, Is this a real IC/processor for arbitrary software or an abstraction of an underlying GPU/DSP?
> Exynos 8895 features VPU (Vision Processing Unit) which is designed for machine vision technology. This technology improves the recognition of an item or its movements by analyzing the visual information coming through the camera. Furthermore, it enables advanced features such as corner detection that is frequently used in motion detection, image registration, video tracking and object recognition.
http://www.samsung.com/semiconductor/minisite/Exynos/w/solut...
> New Vision Processing Unit (VPU) paired to the Image Signal Processors (ISP) that provides a dedicated processing platform for numerous camera features, freeing up the CPU and GPU and saving power.
https://www.mediatek.com/products/smartphones/mediatek-helio...
I was also hoping that with Google's high-efficiency for the TPU, they would make a version for mobile as well, at least for their Pixel phones. I guess they still might, but the fact that the TPU2 does both training and inference makes me think they won't do that anytime soon anymore.
The biggest reasons why I like this "mobile AI chips" trend is that they can give you back some privacy, if the data can be analyzed locally without going to the vendors' servers, and I think they will also boost the capabilities of computational photography. No more spying toys for kids, etc.
Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#4Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#5Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#6> . The chip, known internally as the Apple Neural Engine, Is this a real IC/processor for arbitrary software or an abstraction of an underlying GPU/DSP?
Most likely some kind of dedicated deep learning accelerator. This is coming with or without Apple: > Exynos 8895 features VPU (Vision Processing Unit) which is designed for machine vision technology. This technology improves the recognition of an item or its movements by analyzing the visual information coming through the camera. Furthermore, it enables advanced features such as corner detection that is frequently u…
Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#7Earlier quoted context omitted.
Most likely some kind of dedicated deep learning accelerator. This is coming with or without Apple: > Exynos 8895 features VPU (Vision Processing Unit) which is designed for machine vision technology. This technology improves the recognition of an item or its movements by analyzing the visual information coming through the camera. Furthermore, it enables advanced features such as corner detection that is frequently u…
What does the instruction set look like on that? Is there another example out of this type of chip?
Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#8Earlier quoted context omitted.
Most likely some kind of dedicated deep learning accelerator. This is coming with or without Apple: > Exynos 8895 features VPU (Vision Processing Unit) which is designed for machine vision technology. This technology improves the recognition of an item or its movements by analyzing the visual information coming through the camera. Furthermore, it enables advanced features such as corner detection that is frequently u…
What does the instruction set look like on that? Is there another example out of this type of chip?
Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#9Why not use a gpu. A lot of AI stuff is linear algebra: Multiply accumulate etc.
Re: Apple Is Working on a Dedicated Chip to Power AI on Devices
#10Why not use a gpu. A lot of AI stuff is linear algebra: Multiply accumulate etc.
I am 100% positive that they considered that before starting to work on this ASIC. Some possible reasons: GPUs are insufficiently specialized, or use too much energy on the subset of work that Apple wants to enable with this chip. GPUs are too large. GPUs are busy doing other things, etc.