you need priors and baselines to be statistically literate. i expected json mode to be <half of fn calling, esp since fn calling is more than twice as old.
MACHINE LEARNING
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Real-life Dr. Octopus suit showcased by gigadgets
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Real-life Dr. Octopus suit
— Ronald van Loon (@Ronald_vanLoon) 3 avril 2024
by @gigadgets_#Robotics #AI #MachineLearning #Tech #Technology #Innovation
cc: @pbalakrishnarao @karpathy @chr1sa pic.twitter.com/MtFhJYAbpDReal-life Dr. Octopus suit by @gigadgets_ #Robotics #AI #MachineLearning #Tech #Technology #Innovation cc: @pbalakrishnarao @karpathy @chr1sa
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What is Business Intelligence: Machine Learning and Data Science
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What is #Business Intelligence?
by @DataScienceDojo #MachineLearning #AI #BigData #Analytics #DataAnalytics #DataScience cc: @ravikikan @yvesmulkers @kuriharan -
Autonomous Road Marking Robot Technology Innovation
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#Autonomous Road marking #Robot
— Ronald van Loon (@Ronald_vanLoon) 3 avril 2024
via @FrRonconi#AI #ArtificialIntelligence #Robotics #Tech #Technology #Innovation
cc: @karpathy @ravikikan @patrickgunz_ch pic.twitter.com/gsCB71ZTCm#Autonomous Road marking #Robot
via @FrRonconi #AI #ArtificialIntelligence #Robotics #Tech #Technology #Innovation cc: @karpathy @ravikikan @patrickgunz_ch -
Passage Retrieval with Generative Models for Question Answering
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Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
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Data Storytelling for Successful Brand Building Strategy
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#Data storytelling for successful brand building
by Bilal Awan @DataScienceDojo Read more: https://
buff.ly/3GkgzRL #DataScience #BigData #MachineLearning #ArtificialIntelligence cc: @terenceleungsf @yvesmulkers @pascal_bornet -
Unified Decoder Models Gaining Adoption in Modern AI Systems
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yeah, you're right; i think some people are doing everything in one big decoder model these days though
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Are Encoder-Decoder Models Like T5 and BART Still Relevant?
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is anyone still using encoder-decoder models (T5, BART, etc.)? if so — for what?
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HELM Project Multi-Axis LLM Evaluation Research Discussion
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With our research talk webinar with Dyah Adila on Friday, let's look back at a recent visit we had with Yifan Mai, lead maintainer of the HELM project at Stanford’s CRFM. Mai talked with our researchers about multi-axis LLM evaluation. Read more here:
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Human Annotation Still Essential for Machine Learning Model Improvement
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Did you really think there were no humans in the loop? Quoting from the article — “The primary role of our Machine Learning data associates is to annotate video images, which is necessary for continuously improving the underlying machine learning model powering,” said an