Even today’s best #deeplearning vision systems can fail when pose/lighting/background vary. Our work on ImageNetX is one of the first large scale efforts to pinpoint mistake types of in AI computer vision systems. Explore the dataset
MACHINE LEARNING
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DataRobot Named Leader in IDC MLOps Platforms Assessment
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Managing, monitoring, and governing #AI at scale is challenging, but the right #ML platform makes operations possible. See why DataRobot was recognized as a Leader in the IDC MarketScape: Worldwide MLOps Platforms 2022 Vendor Assessment. https://
bit.ly/3jgioad -
Artificial Curiosity and Creativity: Schmidhuber’s Foundational Work Since 1990
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Artificial Curiosity & Creativity Since 1990-91 Jürgen Schmidhuber : https://
people.idsia.ch/~juergen/artif
icial-curiosity-since-1990.html
… #Artificialintelligence #DeepLearning #MachineLearning -
AI Moat Challenge: Learning and Building in Open Tech Landscape
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Discussion with my friend: my friend: What's the point of learning this AI stuff or even building AI stuff if there's no moat anyway? It's all open tech and even if you learn and make something it'll just get outcompeted/copied by someone else later?
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Barriers to Enterprise Adoption of Advanced ML Models
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Tons. 1) the brilliant researchers working on these models don’t know how to run an ML business 2) cost 3) performance, guardrails, safety 4) infosec/org/legal approval for use in-house 5) power concentration/small talent pool of folks that know this tech
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Data Science Tools Mastered in 2022 and Learning Goals
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What new #data science or engineering tool did you master in 2022? And which tool do you want to master in 2023?
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Humans misjudge k-shot examples: they locate, not teach
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Humans have poor intuition re: the information content of k-shot examples. We often think we're teaching the model a task when really we're just locating it.
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Invalid reasoning yields 80-90% of chain-of-thought gains
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Building on @sewon__min et al.'s find that multiple-choice examples with random answers barely harm performance, @BoshiWang2 et al. find you can achieve 80-90% the gains of chain-of-thought using only examples with invalid reasoning.
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Neobank Love Affair That Wasn’t: AI and Blockchain
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The Neobank Love Affair That Wasn’t https://
bit.ly/3OZXcB0
#neobank #blockchain #AI #digital #MachineLearning #DataScience @Khulood_Almani @FrRonconi @amalmerzouk @CurieuxExplorer @Analytics_699 @EmmanuellaMend1 -
From Boxing Ring to Data Science: Tiffany Perkins-Munn’s JPMorgan Journey
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From the ring to The Street, Tiffany Perkins-Munn has always employed data to guide her #career success. Learn about her journey from TITLE Boxing Club to @jpmorgan in our latest blog post from the Data Science Innovator's Playbook. https://
domino.buzz/3WpqLOW #MLOps #datascience