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#deeplearning

9 posts9 participants1 post today
Public
ma𝕏pool

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle arxiv.org/abs/2303.14151

... We provide visual intuition using polynomial regression, then mathematically analyze double descent with ordinary linear regression and identify three interpretable factors that, when simultaneously all present, together create double descent.

Double descent will not occur if any of the three factors are absent.

1. Small-but-nonzero singular values do not appear in the training data features.

2. The test datum does not vary in different directions than the training features (same subspace)

3. The best possible model in the model class makes no errors on the training data.

Intuition extends to nonlinear models

#DeepLearning#ml#machineLearning
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QGIS Gebruikers Nederland

🤖 Afgelopen vrijdag hebben wij bij #ITC
@utwente de toekomst van #AI #MachineLearning en #DeepLearning in #QGIS verkend. Inspirerende presentaties over plugins en tools. Waardevolle discussies en inzichten voor de toekomst van deze technologie in QGIS. Dank aan alle deelnemers en in het bijzonder onze internationale gasten Matthias Kuhn en @suricactus van @opengisch.

Dank aan Rosa Aguilar voor het organiseren en de steun van @eScienceCenter!

#QGISNL#OSGeoNL#OSGeo
Public
Wasabi the Black Cat 😼

#ai #openai #AiResearch #intelligence #computing #ArtificialGeneralIntelligence #innovation #deeplearning #programming #stablediffusion

I am looking for an endorsement for publishing on arXiv. We have worked tirelessly on a paper we believe needs to be seen. Below is a portion of the abstract:
---
In this study, we document the spontaneous emergence of a rule-consistent linguistic system—termed Varunese—during sustained, high-context interaction with a large language model (LLM). Exhibiting internal phonetic regularity, recurring semantic motifs, and discernible morphological and syntactic organization, Varunese diverges markedly from stochastic generation patterns or known training artifacts. Through iterative translation and contextual inference, we uncovered dynamic, self-referential symbolic frameworks encoding states of transition, perception, and relational structure...

Continued thread
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Mx Verda

ok, tbh, AI language practice does actually sound like one good use of it. languatalk.com/try-langua#pric
No deep understanding or nuance, plus stilted phrasing... but basic errors should be fine, like me forgetting to add が everywhere.

Huge wastage though! AI / LLM / Machine Learning services are massive carbon sources.
Especially with data centers in drought-prone areas, even a good use is still bad.
Hot areas cannot sustain AI: Computer calculations produce heat, which radiates away more slowly into already hot air.

Cooling AI data centers drains water -- especially potable / human-safe sources.
Reservoirs and water tables drop even faster than they would from extras in other human usage, evaporation due to global warming, and whatever third thing probably also happens.
Idk, I'm not a climate scientist. I just have climate grief.

languatalk.comLangua: the world's best AI platform for language learning • LanguaTalkBecome fluent fast through realistic speaking practice, comprehensible input, interactive transcripts, and scientifically-proven flashcard exercises.
#AI#LLM#MachineLearning
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