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Course Level Date Clip# Line Interlocutor Content
Oral Assessments Graduate 2020-01-09 4 93 S01 where there's no width→ which is has which is like a
Oral Assessments Graduate 2020-01-09 4 94 S01 sheet of paper↘
Oral Assessments Graduate 2020-01-09 4 95 T02 mm
Oral Assessments Graduate 2020-01-09 4 96 S01 so which has only length and breadth
Oral Assessments Graduate 2020-01-09 4 97 T02 mm
Oral Assessments Graduate 2020-01-09 4 98 S01 so uh (0.6) without like fabricating chips with the
Oral Assessments Graduate 2020-01-09 4 99 S01 two d materials would be like uh more uh p- uh
Oral Assessments Graduate 2020-01-09 4 100 S01 power efficient °thing°→ the other thing which i'm
Oral Assessments Graduate 2020-01-09 4 101 S01 working on is neuromorphic computing→ which is like
Oral Assessments Graduate 2020-01-09 4 102 S01 these uh devices have uh uh memory and processors
Oral Assessments Graduate 2020-01-09 4 103 S01 separately↘
Oral Assessments Graduate 2020-01-09 4 104 UNK (0.4)
Oral Assessments Graduate 2020-01-09 4 105 S01 so whenever we need to (.) do a computation let's say
Oral Assessments Graduate 2020-01-09 4 106 S01 like we need to add three plus four↘ we need to take
Oral Assessments Graduate 2020-01-09 4 107 S01 three from memory→ four from memory→ and send it back to
Oral Assessments Graduate 2020-01-09 4 108 S01 the processor→ and do the computation three plus four is
Oral Assessments Graduate 2020-01-09 4 109 S01 seven↘ and it's stored back again to the memory↘
Oral Assessments Graduate 2020-01-09 4 110 S01 so this is where uh uh like uh ⁎uh⁎ (0.5) data is taken
Oral Assessments Graduate 2020-01-09 4 111 S01 from memory→ processed and stored back↘ but in neuromorphic
Oral Assessments Graduate 2020-01-09 4 112 S01 computing like what our brain does is like we have in memory