One more double-clicking on why the study, research, policy outreach and multi-stakeholder partnership for human-centered AI is so critical. And why @StanfordHAI was established four years ago to innovate, forecast and help guide this technology. N/
RESEARCH
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Human-Centered AI: Tanner Lecture on Values and Perspective
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I had the honor to deliver the Tanner Lecture @Yale on Oct 2022. With all the excitement and concerns of #AI nowadays, it’s so important to focus on the human-centered approach to AI. Talk link: What We See and What We Value: AI with a Human Perspective https://
youtu.be/aWwNXRS3wBE 1/ -
History of Machine Learning Algorithms
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The history of #MachineLearning #Algorithms
by @avi_gopani @Analyticsindiam Read more: https://
buff.ly/3wuNak3 #AI #BigData #MachineLearning #ArtificialIntelligence #ML #MI #Digital #DataScience cc: @terenceleungsf @ronald_vanloon @richardsocher -
Memory Efficient Neural Networks: Activation Storage Optimization
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This is useful for memory efficient NNs because with careful architecture choice, you don't have to store the activations of every layer. You can store the last layer and work your way backwards. The example indicates that the operation composes, so you can make deep networks 5/n
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Reversible Vision Transformers: Memory-Efficient Deep Learning Architecture
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I learned about this trick from this paper "Reversible Vision Transformers" by @Karttikeya_m et al (
https://
arxiv.org/abs/2302.04869). Not an expert here, but I think the reversible transformation is derived from previous work on NICE (
https://
arxiv.org/abs/1410.8516). 6/6 -
Mathematical Puzzle for Memory-Efficient Neural Networks
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Cute puzzle, courtesy @Karttikeya_m
. Has applications to memory-efficient neural network architectures. Suppose F and G are arbitrary known functions (not necessarily invertible). You are given output O. Can you reconstruct input I? Hint in next tweet. 1/n -
Creating a Text Sentiment Classifier with Hugging Face
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Now, here is the most important part of getting the pre-trained model either from Hugging Face or Open AI. Let's create a text sentiment classifier using Hugging Face. For that get the model from HF and apply the Sentiment Analysis to the review Table
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Artificial Intelligence defeats eight world champions at bridge
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#ArtificialIntelligence beats eight world champions at bridge
by @lfspinney @guardian Learn more: https://
buff.ly/3iLiZxe #AI #BigData #MachineLearning #ML #MI #Digital #DataScience #DL cc: @ronald_vanloon @yvesmulkers @marketbuildr -
Computer Vision Applications in Nuclear Medicine and AI
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The Scope Of #ComputerVision In Nuclear Medicine
by @joshinav @BBNTimes_en Go to: https://
buff.ly/3MYOLVi #AI #BigData #MachineLearning #ArtificialIntelligence #ML #MI #HealthTech cc: @aghiathchbib @yvesmulkers @kuriharan -
ML Automates Neck Injury Assessment with Objective Metrics
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Researchers at Reykjavik University and startup NeckCare have teamed up to simplify and automate neck injury assessments with objective metrics. #DataScience #MachineLearning #InjuryAssessment http://
spr.ly/60123Wj3i