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Nothing embarrasses me more as a Canadian than how our entrepreneurs beg for government funding Raise from private markets! https://t.co/GVjrSt1IoE

modeling language at @allen_ai

finbarr

Mon Dec 08 14:54:30

Remains the central nodes: For this one you need basically to have explored all the branches to know where to go, and until all this has been build, the gradient sees nothing. It is exactly reasoning: Until you have explored complex options, you cannot know the good one. 5/5

Research Scientist @meta (FAIR), Prof. @Unige_en, co-founder @nc_shape. I like reality.

François Fleuret

Mon Dec 08 14:54:26

Now, when you teach a gpt on that, every node (but the central) in the solution path is obvious to predict. Since it has only two neighbors at most, just check which they are, the one already in the path, and you are done. Gradient descent is super happy. Logits are great. 4/5

Remains the central nodes: For this one you need basically to have explored *all the branches* to know where to go, and until all this has been build, the gradient sees nothing. It is exactly reasoning: Until you have explored complex options, you cannot know the good one. 5/5

François Fleuret

Mon Dec 08 14:54:25

Had a chat at neurips with @_vaishnavh about the failure of next-token prediction + teacher forcing, and he has this wonderful minimal synthetic problem that IMO encompasses all the problem with / reason for "reasoning" 1/5

A sequence will be generated by first building a "star graph" with a central node and several "paths" extending from there. So the central node has as many neighbors as there are branches, the branche extremities have a single neighbor, and all other node has two. 2/5

François Fleuret

Mon Dec 08 14:54:23

why settle for just liking fancy things when you can also like everything else this world has to offer at the same time

curious guy creating things @ https://t.co/HXWladhJaA - up and coming wife guy

jack friks

Mon Dec 08 14:52:38

i would like to take this time to thank @marclou for making shipfast on an older version of next which means almost all my projects were marked safe from this vector of attack we are lucky guys

curious guy creating things @ https://t.co/HXWladhJaA - up and coming wife guy

jack friks

Mon Dec 08 14:48:21

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Newest first — browse tweet threads

探索

Newest first — browse tweet threads

Nothing embarrasses me more as a Canadian than how our entrepreneurs beg for government funding Raise from private markets! https://t.co/GVjrSt1IoE

Remains the central nodes: For this one you need basically to have explored all the branches to know where to go, and until all this has been build, the gradient sees nothing. It is exactly reasoning: Until you have explored complex options, you cannot know the good one. 5/5

Now, when you teach a gpt on that, every node (but the central) in the solution path is obvious to predict. Since it has only two neighbors at most, just check which they are, the one already in the path, and you are done. Gradient descent is super happy. Logits are great. 4/5

Had a chat at neurips with @_vaishnavh about the failure of next-token prediction + teacher forcing, and he has this wonderful minimal synthetic problem that IMO encompasses all the problem with / reason for "reasoning" 1/5

why settle for just liking fancy things when you can also like everything else this world has to offer at the same time

i would like to take this time to thank @marclou for making shipfast on an older version of next which means almost all my projects were marked safe from this vector of attack we are lucky guys