MIT researcher explains AI image generators: https://
bit.ly/3E47BYO
AI
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MIT Researcher Explains How AI Image Generators Work
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AI Definition Debate: Cognilytica Explores Artificial Intelligence Meaning
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In this @Cognilytica #AIToday AI Glossary Series #podcast 'Artificial Intelligence' hosts @rschmelzer & @kath0134 share how there still is no commonly accepted definition for #artificialintelligence and Cognilytica’s definition for #AI. Full episode: https://
cognilytica.com/2022/11/04/ai-
today-podcast-ai-glossary-series-artificial-intelligence/?utm_source=dlvr.it&utm_medium=twitter
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Private Equity Takeovers: Higher Prices, Lower Service Quality
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By taking firms private, funds can do all sorts of changes without having to tell anyone much about it. The result is often higher prices & lower services, as private equity funds try to maximize profit. It is just very unusual to see the process play out so publicly.
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Bay Area Robotics Symposium 2022 Video Now Available Online
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is now available from Friday's Bay Area Robotics Symposium (#BARS2022) with over 300 attendees, 20 faculty talks (6 mins each), 50 poster spotlights (1 min each). Major thanks to Mark Mueller of @UCBerkeley and @DorsaSadigh @Stanford for organizing: https://
youtu.be/rQDx_QSnoOw?t=
4810
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Twitter Acquisition: Cost Cutting and Organizational Realignment Strategy
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This is a useful thread to think about changes at Twitter. Some of these changes – massive cost cutting & layoffs, aligning of the goals of the company with the goals of the new owner – are common when firms are bought out. But private equity does it quietly, so we don’t see it.
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Best Books Learning Machine Learning Zero Hero
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The Best Books To Learn #MachineLearning From Zero To Hero http://
bit.ly/3cxlTDo #AI #DeepLearning #NeuralNetworks #TensorFlow #DataScience #Python #javascript #iot #Rstats #linux #ReactJS #serverless #BigData #Analytics #ML #100DaysofCode #womenwhocode #DigitalTransformation -
Large Language Models Demonstrate Self-Improvement Capabilities
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Large Language Models Can Self-Improve Huang et al.: https://
arxiv.org/abs/2210.11610 #ArtificialIntelligence #DeepLearning #MachineLearning -
The Importance of Explainable AI for User Adoption
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Le problème que je regrette, c'est qu'on arrivera pas à embarquer la masse avec des plateformes pensé par des devs. Les algo de reco c'est ouf. Il faut bien s'en servir et pas juste les jeter à la poubelle mais développer des approches d'XAI par exemple. https://
en.wikipedia.org/wiki/Explainab
le_artificial_intelligence
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Addressing data privacy and algorithmic issues in AI
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Mais on fait quoi ? Est ce que je suis en train de cracher sur des intiatives open source et faire l'apologie des plateformes tech, NON. J'alerte constamment sur la viligance de vos données et sur les dérives des algos d'IA, comme dans cette vidéo
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The impact of AI recommendation algorithms on user experience
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Tout le monde critique les algorithmes des plateformes, et notamment les algo de recommandation soupçonnait de manipuler les utilisateurs. Oui mais voilà quand on supprime tous les algos d'IA ,et qu'on laisse le choix aux users. Ca créé une UX horrible. Comment ca ? Exemple