Raghavan asked if the time is ripe for dedicated machine learning technology and not surprisingly decided it was. Up until now machine learning has been done in software – algorithms running on general purpose uniprocessors – supported more recently by software running on multicore processors and GPUs and DSPs.
However, the idea of moving data up to the cloud to be processed is clearly unsustainable given the expected explosion of data that is coming, Raghavan said.
There is a desire, even a necessity, to move beyond data to information, knowledge and wisdom. And that will require more processing done at the source of data measurement to minimize the communication burden, he argued.
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