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Oral Assessments Graduate 2020-01-09 4 113 S01 computing where a:ll the computations taken place within
Oral Assessments Graduate 2020-01-09 4 114 S01 the memory↘ so we ↑can do some computations within the
Oral Assessments Graduate 2020-01-09 4 115 S01 memory no need to transfer the data to processor and uh
Oral Assessments Graduate 2020-01-09 4 116 S01 send it back to the memory↘
Oral Assessments Graduate 2020-01-09 4 117 UNK (0.4)
Oral Assessments Graduate 2020-01-09 4 118 S01 so (.) this is where euromorphic computing is↘
Oral Assessments Graduate 2020-01-09 4 119 UNK (0.7)
Oral Assessments Graduate 2020-01-09 4 120 S01 so neuromorphic computing with two d material we give a-
Oral Assessments Graduate 2020-01-09 4 121 S01 ⌈i- it's like kind of like s- (.) it gives more power
Oral Assessments Graduate 2020-01-09 4 122 T02 ⌊mm mm
Oral Assessments Graduate 2020-01-09 4 123 S01 efficient ⌈devices↘
Oral Assessments Graduate 2020-01-09 4 124 T02 ⌊mm hm
Oral Assessments Graduate 2020-01-09 4 125 UNK (1.0)
Oral Assessments Graduate 2020-01-09 4 126 T02 i have a question→ are there different types of uh
Oral Assessments Graduate 2020-01-09 4 127 T02 material they are being um (1.0) researched and how
Oral Assessments Graduate 2020-01-09 4 128 T02 this could be used↗
Oral Assessments Graduate 2020-01-09 4 129 S01 ☉yea☉h↘ so the th- so silicone so there are researchers
Oral Assessments Graduate 2020-01-09 4 130 S01 who are working on the same silicone itself like they
Oral Assessments Graduate 2020-01-09 4 131 S01 are making trying to uh making it like mo:re uh power
Oral Assessments Graduate 2020-01-09 4 132 S01 efficient devices like that by reducing the- (.) so