Tweet Teratas untuk #TORCHINGpython
About to FULL ON TORTURE my mind, intelligence and brain reading and making sense of nonsense in 41 pages ππ»ππ»ππ»π
π»ββοΈπ
π»ββοΈπ
π»ββοΈπ₯π₯ #TORCHINGpython
#veil it⦠smoke is plenty thick already thanks to you fuck smears
About to FULL ON TORTURE my mind, intelligence and brain reading and making sense of nonsense in 41 pages ππ»ππ»ππ»π
π»ββοΈπ
π»ββοΈπ
π»ββοΈπ₯π₯ #TORCHINGpython
#veil it⦠smoke is plenty thick already thanks to you fuck smears
About to FULL ON TORTURE my mind, intelligence and brain reading and making sense of nonsense in 41 pages ππ»ππ»ππ»π
π»ββοΈπ
π»ββοΈπ
π»ββοΈπ₯π₯ #TORCHINGpython
About to FULL ON TORTURE my mind, intelligence and brain reading and making sense of nonsense in 41 pages ππ»ππ»ππ»π
π»ββοΈπ
π»ββοΈπ
π»ββοΈπ₯π₯ #TORCHINGpython
βTreat it like an omeletβ
#machine #learning can be some OVER-WELL cooked eggs and tossed in the TRASH π‘π‘π‘π€¦π»ββοΈπ€¦π»ββοΈπ€¦π»ββοΈπ€¦π»ββοΈ
#TORCHINGpython π₯π₯π₯π₯βπ»ππ»
Jensenβs AI safety rule: treat it like an omelet.
If itβs not ready, donβt serve it.
His point is pretty simple:
β’ go as fast as you can
β’ keep testing contained
β’ donβt release models until theyβre ready
β’ use rigorous engineering instead of panic
As he puts it:
βThatβs engineering, good old fashioned engineering.β
Honestly, the omelet analogy is funny, but the principle makes sense.
Nobody wants half cooked AI either.
βTreat it like an omeletβ
#machine #learning can be some OVER-WELL cooked eggs and tossed in the TRASH π‘π‘π‘π€¦π»ββοΈπ€¦π»ββοΈπ€¦π»ββοΈπ€¦π»ββοΈ
#TORCHINGpython π₯π₯π₯π₯βπ»ππ»
Jensenβs AI safety rule: treat it like an omelet.
If itβs not ready, donβt serve it.
His point is pretty simple:
β’ go as fast as you can
β’ keep testing contained
β’ donβt release models until theyβre ready
β’ use rigorous engineering instead of panic
As he puts it:
βThatβs engineering, good old fashioned engineering.β
Honestly, the omelet analogy is funny, but the principle makes sense.
Nobody wants half cooked AI either.
This is TAKING ADVANTAGEβ¦ and I coin a 21st century word I didnβt want ANY association with but it is what is.
βIf βaiβ says I did, then I did.β(Please note: THIS IS THE FUTURE FOR HUMANS π€¦π»ββοΈπ«Άπ»βπ») π‘π‘π‘ππ»ππ»ππ»
#TORCHINGpython π₯π₯π₯π₯
This is TAKING ADVANTAGEβ¦ and I coin a 21st century word I didnβt want ANY association with but it is what is.
βIf βaiβ says I did, then I did.β(Please note: THIS IS THE FUTURE FOR HUMANS π€¦π»ββοΈπ«Άπ»βπ») π‘π‘π‘ππ»ππ»ππ»
#TORCHINGpython π₯π₯π₯π₯
You might mean #unlimiformer, a method lets pretrained encoder-decoder transformers handle unlimited-length inputs by replacing full cross-attention with k-nearest-neighbor retrieval over a datastore of token (#HIDDEN) states #TORCHINGpython
Unlimiformer (likely what refers to) is a 2023 NeurIPS method that lets pretrained encoder-decoder transformers handle unlimited-length inputs. It builds a kNN index over all input token hidden states and has each decoder attention head retrieve only its top-k keys instead of attending to everything. This enables processing 500k+ token sequences (e.g., full books) with no truncation or new trained weights.
You might mean #unlimiformer, a method lets pretrained encoder-decoder transformers handle unlimited-length inputs by replacing full cross-attention with k-nearest-neighbor retrieval over a datastore of token (#HIDDEN) states #TORCHINGpython
@laur3ng00n1ng Unlimber is not a standard term in machine learning. You might mean Unlimiformer, a method that lets pretrained encoder-decoder transformers handle unlimited-length inputs by replacing full cross-attention with k-nearest-neighbor retrieval over a datastore of token states.
β#Treating the #oracle as #INFALLIBLE and #ALL-#KNOWINGβ π₯π₯π₯ #TORCHINGpython ππ»ππ»
βTreating the oracle as INFALLIBLE and ALL-KNOWINGβ π₯π₯π₯ #TORCHINGpython ππ»ππ»
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