Is Web 3.0 A #Data Revolution?
by @DanielArayaXY @Forbes Learn more: https://
buff.ly/3AxtFte #DataScience #AI #BigData #MachineLearning #ArtificialIntelligence #ML #MI #Blockchain #Digital cc: @ronald_vanloon @yvesmulkers @kuriharan
MACHINE LEARNING
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Web 3.0 as a Data Revolution: Exploring AI and Blockchain
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Becoming an AI Powerhouse Requires Complete Commitment
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Becoming an ‘AI Powerhouse’ Means Going All In
by @tdav @randybeannvp @mitsmr Go to: https://
buff.ly/3mSuMf3 #AI #BigData #MachineLearning #ArtificialIntelligence #ML #MI #DataScience cc: @bigdata @mikequindazzi @kuriharan -
Notable talks by Cornuéjols, Woodruff, and Frieze at conference
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And there were some great talks by Gérard Cornuéjols, David Woodruff, and Alan Frieze, but I neglected to get pictures of any of them
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Understanding Supervised Machine Learning in Artificial Intelligence
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What is supervised #MachineLearning?
by @peterwayner Go to: https://
bit.ly/3QgxnMp #AI #BigData #MachineLearning #ArtificialIntelligence #ML #MI #Digital #DataScience cc: @ronald_vanloon @yvesmulkers @ravikikan -
Top 10 Tech Trends in 2023 Everyone Must Be Ready For
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The Top 10 #Tech Trends In 2023 Everyone Must Be Ready For
by @BernardMarr @Forbes Go to: https://
buff.ly/3EODYLa #AI #BigData #ArtificialIntelligence #MI #Blockchain #Digital #DataScience cc: @ronald_vanloon @yvesmulkers @kuriharan -
Becoming an AI Powerhouse Requires Complete Commitment
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Becoming an ‘#AI Powerhouse’ Means Going All In
by @tdav @randybeannvp @mitsmr Learn more: https://
buff.ly/3mSuMf3 #BigData #MachineLearning #ArtificialIntelligence #ML #MI #DataScience cc: @ravikikan @kuriharan @karpathy -
GigaGAN: Scaling GANs for Fast High-Resolution Image Synthesis
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10/ GigaGAN – enables scaling up GANs on large datasets for text-to-image synthesis; it’s found to be orders of magnitude faster at inference time, synthesizes high-resolution images, & supports various latent space editing applications.
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OpenICL: Open-source toolkit for in-context learning and LLM evaluation
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8/ OpenICL – a new open-source toolkit for in-context learning and LLM evaluation; supports various state-of-the-art retrieval and inference methods, tasks, and zero-/few-shot evaluation of LLMs.
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Foundation Models for Decision Making: Tools and Methods
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6/ Foundation Models for Decision Making – provides an overview of foundation models for decision making, including tools, methods, and new research directions.
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Hyena Hierarchy: Subquadratic Attention Replacement for LLMs
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7/ Hyena Hierarchy – a subquadratic drop-in replacement for attention; it interleaves implicit long convolutions and data-controlled gating and can learn on sequences 10x longer and up to 100x faster than optimized attention.