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Just as an iff statement is stronger than an if statement, a claim about all nonn-cromulent objects is stronger than a claim about all non-cromulent objects.
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The abbreviation "iff" = "if and only if" is common and extremely useful. Occasionally you see "whenn" = "when and only when." John Conway proposed "onne" = "one and only one." "Nonn" doesn't extend this pattern. But it DOES look like a mathematical shorthand akin to "iff."
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People often say "non" in these settings but "nonn" is what they really mean. It's tempting to also coin innfinite and irrrational. However, I think nonn-finite and nonn-rational are safer!
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How about "nonn" as shorthand for "not necessarily"? "Let F be any nonn-convex function" "The bounded region defined by these nonn-linear constraints" "The trouble is the nonn-decomposable path score" "REINFORCE works in nonn-Markov environments" "WFSAs are nonn-determinizable"
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(People keep suggesting that blue states use the Texas device to pass unconstitutional gun control laws. But tit-for-tat constitutional violations are playing with fire. The law above makes the point neatly, via a right everyone holds dear, yet affects no one … ALMOST no one.
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Hey you states! Can someone quick pass a law? Make it illegal to express any positive opinion of any Supreme Court decision or Justice. State can't enforce, but anyone else can sue violators for $10K + costs. How long till SCOTUS strikes down this heinous abrogation of 1A rights?
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Summer 2022 NLP/ML internships at Microsoft Semantic Machines! Fun with creating the most powerful, natural, and helpful human-AI interactions. We had a great time hosting a very talented collection of interns last summer, working on diverse challenges. http://aka.ms/smjobs pic.twitter.com/HOFvJJuko8
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Jason Eisner Retweeted
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@adveisner at@TeachingNLP (paraphrased): "early works on ML/Stat-based NLP were basically people doing their homework in public, learning a new topic and finding some trivial application for it. this is how we got so many methods into our toolbox"Thanks. Twitter will use this to make your timeline better. UndoUndo -
Jason Eisner Retweeted
But, our question for the overall
#nlproc community is whether there are good existing models about how to enable sharing of assignments and teaching materials in a sustainable way? please offer some pointers!#NAACL2021#ACL2021NLP#EMNLP2021Show this threadThanks. Twitter will use this to make your timeline better. UndoUndo -
"Learning how to ask: Querying LMs with mixtures of soft prompts" https://www.cs.jhu.edu/~jason/papers/#qin-eisner-2021 … In the
#NAACL2021 Best Paper session, an entertaining short presentation from@hiaoxui of@jhuclsp. Today (Wed) at 12:30 PDT (session is 11:40-1:10 PDT).pic.twitter.com/IthBXopugN
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Experimenting to find a language model prompt that works for your NLP task? Why not automate that? Prompts are made of word EMBEDDINGS ... so just tune those vectors by SGD. Even random init works fine. Bonus: Continuous "soft prompts" are more expressive than discrete ones.pic.twitter.com/QZweQFRwRQ
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Careful analysis here, featuring the complexity class P/poly: "Limitations of Autoregressive Models and Their Alternatives" https://arxiv.org/abs/2010.11939
#NAACL2021 talk by@kitsing_l, Session 14D (Wed 09 Jun 2021 5PM PDT)pic.twitter.com/QEsSmIkD5k
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It may be EASY to determine whether x is grammatical, yet IMPOSSIBLE to do so by testing p(x) > 0, for ANY p that is modeled autoregressively.
(The required autoregressive factors are uncomputable: halting problem!)Show this threadThanks. Twitter will use this to make your timeline better. UndoUndo -
If your LM needs to reflect a speaker's reasoning or planning, you need a more powerful family of language models where next-word prediction isn't cheap by design, but requires lookahead or other marginalization.pic.twitter.com/X21GNetlAy
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Everyone's using big autoregressive language models. But ... they predict the next word with a polysized circuit (computation graph). So they can't accurately model settings where that prediction is NP-hard.
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The Roads All Taken I shall be drawing this (Figure B) Somewhere pages and pages hence: Two paths diverged in a graph, and we Went nondeterministically; And then we assessed the difference.
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Here's a version of the ad for even more senior people. Microsoft is committed to building a diverse workforce: we strongly encourage women and URMs to apply for both positions. https://careers.microsoft.com/us/en/job/1029300/Principal-Researcher-Semantic-Machines-NLP-ML …
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The Semantic Machines group @ Microsoft is looking to hire a few more extremely talented NLP/ML researchers. I can say firsthand it's an incredible team to work with! Wanna redesign dialogue systems to truly help human users via truly natural conversation? https://careers.microsoft.com/us/en/job/1026908/Senior-Researcher-Semantic-Machines-NLP-ML …
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At least anyone can verify from the Ethereum blockchain that I do own *this* NFT: https://opensea.io/assets/0x8c5acf6dbd24c66e6fd44d4a4c3d7a2d955aaad2/18396660817237219395031867244880941621250554421087481293517036944217445198134 … https://etherscan.io/verifySig/2437 (thanks to
@bax1337 via@matthew_d_green for help on that) (and apologies that I didn't realize the environmental cost of Ethereum 1.0 transactions)Show this threadThanks. Twitter will use this to make your timeline better. UndoUndo
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