Human sensory-motor processing seems to operate at 10 bits/second. It takes 1/3 of a second before our brain registers how heavy an object we are lifting actually is, replacing the less accurate judgement we had previously made just by looking at the object.
MACHINE LEARNING
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Comprehensive Guide to Machine Learning: Free Resource
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Free Book: A Comprehensive Guide to #MachineLearning http://
bit.ly/2AAidka #AI #NeuralNetworks #TensorFlow #Algorithms #Programming #Python #ML #100DaysOfCode #javascript #linux #cloud #serverless #BigData #Analytics #womenwhocode #devcommunity #DataScience #DeepLearning -
Building AI Projects with Hugging Face Spaces
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Would be so cool to build a http://
hf.co/spaces with it! -
GPT-3 Tokenization Challenges and Model Limitations
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+1 for this approach. GPT-3’s tokenization is a big gotcha. Model doesn’t see text as sequences of characters unless you add spacing/hyphens. It can’t even reliably tell you the last letter of a word without first rewriting it that way. Similar for counting length:
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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 -
Tech Convergence: AI, ML, IoT Integration in Retail Digital Signage
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Connect The Dots! How #tech convergence #AI #ML & #IoT is enabled by #SystemsIntegrators – Examples #Digitalsignage in #Retail & more! See @Think_BlueStar @intel via @insightdottech https://
insight.tech/retail/sis-dep
loy-interactive-digital-signage-with-ease?utm_source=twitter&utm_medium=organic&utm_campaign=2022-tdc-eaves
… #software #ITInfluencer #hardware #IntelPartner #IoT @dinisguarda -
Career Paths: Data Science vs Machine Learning Engineering
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If you want to become a full-stack data scientist then start from data science and to become MLE you can go with ML as well
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Team structure and ethical considerations in AI dataset creation
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I would say: smaller teams of full time people in a single org, simpler performance goals, more paid compute, no specific goals on ethical sourcing or social impact of the dataset creation process
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AI Evolution Reshapes Modern Advertising Industry Landscape
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How Artificial Intelligence has Evolved in the Advertising Industry https://
analyticsinsight.net/how-artificial
-intelligence-has-evolved-in-the-advertising-industry/
… #ArtificialIntelligence #AI #Advertising #MachineLearning #DataScience #innovation #IoT #DigitalMarketing #100DaysOfCode #technology #programming #DigitalTransformation