{"id":16796,"date":"2024-09-01T09:56:10","date_gmt":"2024-09-01T09:56:10","guid":{"rendered":"\/?p=16796"},"modified":"2024-09-01T10:11:49","modified_gmt":"2024-09-01T10:11:49","slug":"many-ai-companies-are-cheating-everyone-by-not-doing-a-good-job-of-remembering-essential-details","status":"publish","type":"post","link":"\/?p=16796","title":{"rendered":"Many “AI” companies are cheating everyone by not doing a good job of remembering essential details"},"content":{"rendered":"

Roger Grosse @RogerGrosse\u00a0 Amortized variational inference is neither amortized nor variational nor inference. x.com\/jpillowtime\/st\u2026
\nJonathan Pillow @jpillowtime Amortize means to “to pay off a debt with regular payments”<\/p>\n

But in amortized inference you pay a big up-front cost to train an inference network, then inference is cheap per datapoint. Isn’t that the opposite of amortization?<\/p>\n

Shouldn’t we call it Big Down Payment inference?
\nReplying to @RogerGrosse<\/p>\n

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The inferences now are “cheap” in the sense of “not worth much”, “not reliable”, “not storing the original data and context and environmental clues”. It tries to “snapshot” a reality that is intrinsically infinite and eternal – constantly changing, but within human ability to survive. What we have now is sham, a scheme, where the costs of hidden and inaccessible knowledge – that could be shared – is forced onto users, buyers, and future generations.<\/span><\/div>\n<\/div>\n<\/div>\n
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Filed as (Many AI companies are cheating everyone by not doing a good job of remembering essential details)<\/span><\/div>\n<\/div>\n<\/div>\n
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Richard Collins, The Internet Foundation<\/span><\/div>\n<\/div>\n<\/div>\n
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CC: <\/span>@jpillowtime<\/span><\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Roger Grosse @RogerGrosse\u00a0 Amortized variational inference is neither amortized nor variational nor inference. x.com\/jpillowtime\/st\u2026 Jonathan Pillow @jpillowtime Amortize means to “to pay off a debt with regular payments” But in amortized inference you pay a big up-front cost to train an inference network, then inference is cheap per datapoint. Isn’t that the opposite of amortization?
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