Row 48284

Row ID: 48284 | Dataset Entry | Axioma AXP Content Repository

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I think the logic here is that neural nets have actually been working reasonably well all this time, going back to the 50s, but compute sucked. Now that compute is getting truly beefy we're seeing neural nets and other ML really start to take off. If I recall correctly Ilya said neural nets were pretty bad until it crossed a threshold and then suddenly got better and then kept improving with more and more compute.

Yes, there were a few innovations in training models but I don't think those innovations are so groundbreaking that they are driving the improvements, primarily. I think the primary driver is that compute is exploding. There have always been creative and brilliant people in ML but they were hobbled by the fact that they only had a few 100 or 1000s of nodes to play with...now they have billions upon billions and, on assumes, soon enough it will be trillions or 10s of trillions, and so on.

FieldValue
text I think the logic here is that neural nets have actually been working reasonably well all this time, going back to the 50s, but compute sucked. Now that compute is getting truly beefy we're seeing neural nets and other ML really start to take off. If I recall correctly Ilya said neural nets were pretty bad until it crossed a threshold and then suddenly got better and then kept improving with more and more compute. Yes, there were a few innovations in training models but I don't think those inno…
label r/openai
dataType comment
communityName r/OpenAI
datetime 2024-05-22
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Raw Record

{
  "text": "I think the logic here is that neural nets have actually been working reasonably well all this time, going back to the 50s, but compute sucked. Now that compute is getting truly beefy we're seeing neural nets and other ML really start to take off. If I recall correctly Ilya said neural nets were pretty bad until it crossed a threshold and then suddenly got better and then kept improving with more and more compute.\n\nYes, there were a few innovations in training models but I don't think those innovations are so groundbreaking that they are driving the improvements, primarily. I think the primary driver is that compute is exploding. There have always been creative and brilliant people in ML but they were hobbled by the fact that they only had a few 100 or 1000s of nodes to play with...now they have billions upon billions and, on assumes, soon enough it will be trillions or 10s of trillions, and so on.",
  "label": "r/openai",
  "dataType": "comment",
  "communityName": "r/OpenAI",
  "datetime": "2024-05-22",
  "username_encoded": "Z0FBQUFBQm5Lak1SZjc5VWdnZ2lGSEx5N1RVd1NiWFRrRkRSWWtEeHNNZkF1aTZ3bHh1SGlrYkwtbG51STFLTkdpNWQxaXRiRDE0QThwaWJGa0dLX1draEVoOUlaT2ozVFE9PQ==",
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}
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