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In last year‘s conference "Quantum For Business 2019" Iordanis Kerenidis gave a nice talk about quantum machine learning.
At about time 27:10 he mentions a "Quantum Data loader" as an alternativ for QRAM. To me it sounds very concrete but I can not find any reference for it. Has somebody any details about it or did I get this wrong? I have looked at arxiv papers 1911.01117 and 1812.03584, that he probably referred to in his talk. But these seem to use QRAM explicitely.
He generally refers to QRAM. But there are other ways to load data in a quantum computer, generally referred as quantum embeddings or quantum feature maps. They are generally more near-term oriented than QRAM. Yet with a QRAM, you can design an algorithm with the goal of obtaining a possible expression of a speedup against a classical version. This article, and this one are examples/references you can learn about quantum embeddings and quantum feature maps.
