Row 65108

Row ID: 65108 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 65108 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I wrote my masters thesis on the subject and my overall conclusion was that backprop doesn’t happen in the brain because neurons don’t have a direct backwards connection. I also found it unfeasible to approximate the updates that were being propagated in backprop: they are non linear and depend on the values upstream (which the brain wouldn’t have access to since neurons only communicate one way). Having said that, I didn’t dedicate a PhD to this and my research was very limited in scope (it was a learning exercise about deep neural networks).

FieldValue
text I wrote my masters thesis on the subject and my overall conclusion was that backprop doesn’t happen in the brain because neurons don’t have a direct backwards connection. I also found it unfeasible to approximate the updates that were being propagated in backprop: they are non linear and depend on the values upstream (which the brain wouldn’t have access to since neurons only communicate one way). Having said that, I didn’t dedicate a PhD to this and my research was very limited in scope (it wa…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-23
username_encoded Z0FBQUFBQm5Lak1iTVZUR1JJWjREWUxzN3dhN1MzY19wZ2dnMURWUnNqWkhIRXBZVVBIN0N3WFhsQ2RPOExWTmc4OW5DQzhhX3BrU2FDY1NUQ19uQVdLVWFBY2U3VnZZbkE9PQ==
url_encoded Z0FBQUFBQm5Lak9zUE9LTGhvUTlBRGR4UjRRaWxHMFFsOHNqeGtEOGUwZXhhZlctYlNnWHBONEN6aGRsazZtLUNCS193VGpOcU1MRkYxNS1Xd2prdjhPU2lDTU9Va0lxRFdSX1I0cW1pOE8tRG5Sa3J4a2tsZ196WUVfV1RTclpwd1k5b0F6Um1QR3N0Y3ZjSkZkdU1JdDNQNVJIVlBhd2FjZFpMRXZiZHEwdVdJLTJZbHU0UmE5VGRDZ082Q1FEYnBKMWw0ZkdOa1o2NjBwRjNqMC1jSE9oZWxwenBFcGFsdz09

Raw Record

{
  "text": "I wrote my masters thesis on the subject and my overall conclusion was that backprop doesn’t happen in the brain because neurons don’t have a direct backwards connection. I also found it unfeasible to approximate the updates that were being propagated in backprop: they are non linear and depend on the values upstream (which the brain wouldn’t have access to since neurons only communicate one way). \nHaving said that, I didn’t dedicate a PhD to this and my research was very limited in scope (it was a learning exercise about deep neural networks).",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-23",
  "username_encoded": "Z0FBQUFBQm5Lak1iTVZUR1JJWjREWUxzN3dhN1MzY19wZ2dnMURWUnNqWkhIRXBZVVBIN0N3WFhsQ2RPOExWTmc4OW5DQzhhX3BrU2FDY1NUQ19uQVdLVWFBY2U3VnZZbkE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9zUE9LTGhvUTlBRGR4UjRRaWxHMFFsOHNqeGtEOGUwZXhhZlctYlNnWHBONEN6aGRsazZtLUNCS193VGpOcU1MRkYxNS1Xd2prdjhPU2lDTU9Va0lxRFdSX1I0cW1pOE8tRG5Sa3J4a2tsZ196WUVfV1RTclpwd1k5b0F6Um1QR3N0Y3ZjSkZkdU1JdDNQNVJIVlBhd2FjZFpMRXZiZHEwdVdJLTJZbHU0UmE5VGRDZ082Q1FEYnBKMWw0ZkdOa1o2NjBwRjNqMC1jSE9oZWxwenBFcGFsdz09"
}

Entry Information