NPU vs. CPU vs. GPU vs. TPU: AI Hardware Compared

[@marcialabrahantes3369]

TPUs are a branded chip from Google - Tensor processing unit - used as an "efficient+proprietary" chip to train with TensorFlow, Google's AI algo. I doubt they're anywhere outside of G Datacenters and they'll likely won't be relevant in a few years. With that, I think the script is GPT v2.0 quality - please update your LLM source, y'all

[@EyeonTech]

Thanks for stopping by and sharing your input! However, we do not use AI to write our scripts or do our research. Feel free to visit our website that has more information than we can fit into 3 minutes! www.techtarget.com/whatis/feature/GPUs-vs-TPUs-vs-NPUs-Comparing-AI-hardware-options

[@JuanCarlosGiraldo-r2z]

I loved your video. However, I think there is a misunderstanding about what a TPU is. I don't think it's fair to say that the use of a TPU is relegated to watches, coffee makers, and other such devices. A TPU is a bit misunderstood in this regard. Unlike GPUs that are used on a daily basis in the gaming community, TPUs have a very specialized use in the data centers of Google and large companies like Amazon and Meta. A TPU is a device that processes data to perform matrix multiplication operations in a very efficient manner through processing elements or PE that are packed into hundreds of thousands on a single chip. It is based on a technology from 1978 called systolic arrays. Today, thanks to advances in electronics and the proliferation of purpose-built integrated circuits or ASICs, it is possible to build these systems to accelerate intensive vector, matrix, and tensor calculations in general. I would have said that while an NPU is used for inference, in contrast due to computational demand TPUs are used for training neural networks.