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" ... Even the heralded use of Machine Learning (ML) does not make-or-break the answer to the parking question. If you collected a ton of data about car parking and fed that data into a Machine Learning or Deep Learning (DL) algorithm, presumably the computationally pattern matching would identify the two types of parking, though deciding which is the better would not be especially part of the pattern identification. ... "
" ... In fact, by outsourcing the most computationally expensive aspect of its advertising business to users’ devices, the company could actually massive increase the richness of its mining activities while reducing its total hardware needs. ... "
" ... It's focused heavily on artificial intelligence, which represents the most computationally intensive workloads in the data center. Most companies think of NVIDIA's GPUs as a go-to computing resource for training AI models using large datasets. And the company achieved great success in that market. Companies like Walmart have sworn by Nvidia's GPUs. ... "
" ... There are advantages to this approach. You can apply inheritance more readily, and computationally, it becomes easier to determine the metaphorical similarity between two different entities or attributes (you can even argue that in this particular way of thinking, you don't really need attributes at all). ... "
" ... This solution is built on four well-founded assumptions. Each is a puzzle in an of itself that is computationally expensive to solve. By combining Symmetric external Diffie-Hellman (SXDH) on pairing groups, Learning with Errors (LWE), Learning Parity with Noise (LPN) over large fields, and the existence of a Boolean Pseudo-Random Generator (PRG) that is simple to compute, the team developed iO that is based on the difficulty of computational problems with a long history of study, based on complexity, coding, and number theory. ... "