More generally a few remarkable strategies people use during their training:
1) skim text because they already know it
2) ignore text because it's clearly noise (e.g. they won't memorize SHA256 hashes. LLMs will.)
3) revisit parts that are learnable but not yet learned
MACHINE LEARNING
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Training Strategies: Skimming, Filtering Noise, and Revisiting Content
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Examples vs. Presentations: Spaced Repetition in LLM Training
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Is it the number of examples that matters or the number of presentations to the model during training? E.g. humans used spaced repetition to memorize facts but there are no equivalents of similar techniques in LLMs where the typical training regime is uniform random.
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AI and Machine Learning Combat $300B Annual Insurance Fraud
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Insurance fraud in the US is a $300 billion per year problem. Learn how @Quantiphi and NVIDIA are using #AI and #machinelearning for document digitization to identify risks, prevent fraud, and accelerate claims processing. Register today: https://
nvda.ws/3GkfXwO -
Galática’s fastai notebook plan exploration attempt
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Looks like http://
galatica.org had a good plan for a fastai notebook, although I can't get it to go further than producing this intro! 😀 -
MLOps Maturity Model: Maximizing Your Data Science ROI
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Where does your company fit on this #MLOps Maturity Model? And what could that mean for your ROI on datascience investments? Check out @JoshPoduska
's blog to find out: -
Robot Dog Walks on Stools Using Onboard Vision
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New work from @berkeley_ai and @CMU_Robotics on visual locomotion enables a robot dog walking on tall bar stools in @ashishkr9311's living room — entirely from onboard cameras and compute. Trained in simulation and deployed directly in the real world!https://t.co/kBEpOCsRob https://t.co/wVIeiMgfd2
— Berkeley AI Research (@berkeley_ai) 15 novembre 2022New work from @berkeley_ai and @CMU_Robotics on visual locomotion enables a robot dog walking on tall bar stools in @ashishkr9311
's living room — entirely from onboard cameras and compute. Trained in simulation and deployed directly in the real world! http://
vision-locomotion.github.io -
Classical Mechanics as MAP Approximation of Quantum Mechanics
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Classical mechanics is the MAP approximation of quantum mechanics.
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Machine Learning Optimization for U.S. Treasury Yield Curves
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Last chance to register! Find out how to use #machinelearning to optimize yield curve estimation of U.S. Treasuries. Hear from Markus Pelger, Assistant Professor of Management Science & Engineering at @Stanford
, on November 16 at 9 AM PT: https://
nvda.ws/3O6JUCq -
SAP Build Democratizes App Development for Citizen Developers
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Latest #news on #SAPBuild Catalyze #innovation in #appdev to support #citizen & professional #developers Let's democratize capacity to co-create! 'anyone can be a builder' @JuerMueller #SAPTechEd #code #Python #Analytics #data #ML @Shi4Tech @ipfconline1 @moingshaikh #AI https://
x.com/SAPTechEd/stat
/SAPTechEd/status/1592503986879270912
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Brain Dynamics Inspire Flexible Machine Learning Models
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Solving Brain Dynamics Gives Rise to Flexible Machine Learning Models https://
syncedreview.com/2022/11/15/sol
ving-brain-dynamics-gives-rise-to-flexible-machine-learning-models/
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