#9
New, unifying concepts may be derived empirically by linking data patterns that #generalize to the interaction between experimental components (#TaskDemands).

New theories can emerge and be tested through #Multitask studies unconstrained by existing taxonomies.

#NASA May Pay $1 Billion to Destroy the #InternationalSpaceStation. Here’s Why : Sci Am

Here’s How Two #Teenagers Found a New Proof of the #Pythagorean Theorem : Medium

Do #MachineLearning Models #Memorize or #Generalize? : Google

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"Human beings... are far too prone to generalize from one instance. The technical word for this, interestingly enough, is superstition." — Francis Crick — — — #FrancisCrick #quote #quotes #humans #people #superstition #beliefs #generalize #generalities

@ncrav

While not expressing disagreement or agreement with the #study's #conclusions, the #experiment design included some features that make it difficult to #generalize from.

For example, they eliminated those homeless with a history of #substance #abuse. That by itself makes the #headline claims a bit suspect, or at least not clearly #supported by evidence.

#StudyDesign #analysis #PR

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series

Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad Javad Darvishi Bayazi et al.

Action editor: Antoni Chan.

https://openreview.net/forum?id=mvftzofTYQ

#generalization #generalize #datasets

WOODS: Benchmarks for Out-of-Distribution Generalization in Time...

Deep learning models often fail to generalize well under distribution shifts. Understanding and overcoming these failures have led to a new research field on Out-of-Distribution (OOD)...

OpenReview

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series

https://openreview.net/forum?id=mvftzofTYQ

#generalization #generalize #datasets

WOODS: Benchmarks for Out-of-Distribution Generalization in Time...

Deep learning models often fail to generalize well under distribution shifts. Understanding and overcoming these failures have led to a new research field on Out-of-Distribution (OOD)...

OpenReview

I would argue the named entity recognition (#NER) is the simplest, best defined #NLP task with a current, practical application. One might think that NER is a solved problem. However, the best existing NER models still fail to #generalize well to named entities (names) that were not in their training data (despite decades of work).

I don't know what #sentience is, but I'm, on principle, not willing to grant #personhood to something that can't identify names it has never seen before.