Nope, and more Nope ..
"900TB in 4U (225TB/U storage density – better than the SFA200NV/400NV) and, with the four supported 4U x 90 bay expansion cabs, 4.5PB in a rack. That's better storage density compared to flash and it's cheaper."
AF700 is 4U an can hold 24 30TB drives .. raw capacity is 720 TB, then add say four of the 24 drive expansion shelves at 2U each ... with an average raw density of 360 TB/RU .. and you've got 12RU with 720 + 4* 360 and you've got a petabyte of raw storage in 12RU
Now take off some capacity for RAID etc which is probably going to be more or less the same for DDN and ONTAP, and then add on the 4.7:1 average savings from dedupe, compression, and clones and you're looking at about 4 Petabtytes of storage in 12 RU vs 4.5 in a whole rack.
Flash WINS !!!
Also ... deep learning performance is rarely about raw storage throughput .. you can choke the GPUs in a DGX-1 with less than 2 gigabytes per second of throughput, and thats with a _lightweight_ learning model, the really deep stuff rarely goes much above 500MB/sec for 8 of the biggest baddest GPU cards... HPC workflows and architectures != Deep Learning, so sorry DDN, fast'n'cheap isn't really going to be nearly as compelling in AI as it was in HPC.