Row 91001

Row ID: 91001 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 91001 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I have seen ML being deployed on M1/2 MBPs for cpu based training on space dynamics (which uses TBs of numerical) data. It is efficient since the NPUs can be leveraged or so I heard (I steer away from Apple as much as I can and I love Linux for such things honestly). However, if you are interested in CUDA based DL, a dedicated Desktop (if money ain’t a concern) will be long lasting and useful than Laptop. You can use the desktop as a server for you to access via a remote access app on a laptop so you don’t overburden the cooling solution on your laptops (which are expensive).

FieldValue
text I have seen ML being deployed on M1/2 MBPs for cpu based training on space dynamics (which uses TBs of numerical) data. It is efficient since the NPUs can be leveraged or so I heard (I steer away from Apple as much as I can and I love Linux for such things honestly). However, if you are interested in CUDA based DL, a dedicated Desktop (if money ain’t a concern) will be long lasting and useful than Laptop. You can use the desktop as a server for you to access via a remote access app on a laptop s…
label r/deeplearning
dataType comment
communityName r/deeplearning
datetime 2024-05-25
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Raw Record

{
  "text": "I have seen ML being deployed on M1/2 MBPs for cpu based training on space dynamics (which uses TBs of numerical) data. It is efficient since the NPUs can be leveraged or so I heard (I steer away from Apple as much as I can and I love Linux for such things honestly). However, if you are interested in CUDA based DL, a dedicated Desktop (if money ain’t a concern) will be long lasting and useful than Laptop. You can use the desktop as a server for you to access via a remote access app on a laptop so you don’t overburden the cooling solution on your laptops (which are expensive).",
  "label": "r/deeplearning",
  "dataType": "comment",
  "communityName": "r/deeplearning",
  "datetime": "2024-05-25",
  "username_encoded": "Z0FBQUFBQm5Lak1yM0VjMWpBc1JycGdSWDl5YWVzUXFIZ1FVeElZTVY0RWJicG44c1RIV29kSFFSNXRfQ3c2aUtyMkN4TWpVOHBkQ0N0cXBQZFo2YUlQRGFXNV9qeW5hdy1FTkFBQTVaZWFWdEpQT0NYX2FGeU09",
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}
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