Large Language Models Can Self-Improve Huang et al.: https://
arxiv.org/abs/2210.11610 #ArtificialIntelligence #DeepLearning #MachineLearning
RESEARCH
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Large Language Models Demonstrate Self-Improvement Capabilities
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Academic Review Process Rigor and Accountability Critique
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I learned more about the potential of overlap from your tweets than this metareview. That shows how lazy the metareview is. If the AC's gonna wield significant power to overturn three reviewers, they have to do more work than this. Read the paper and point out the exact overlap
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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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Mastering Atari Games with Limited Data: Deep Learning
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Mastering Atari Games with Limited Data Ye et al.: https://
arxiv.org/abs/2111.00210 #MachineLearning #DeepLearning #ArtificialIntelligence -
What Will Artificial Intelligence Do To Us?
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What Will #ArtificialIntelligence Do To Us? https://
currentaffairs.org/2022/11/what-w
ill-artificial-intelligence-do-to-us
… @curaffairs #AI #DeepLearning #Robots #BigData #Analytics #MachineLearning #100DaysofCode #IoT #serverless #womenwhocode #Rstats #Python #DigitalTransformation #TensorFlow #DataScience -
Parallel Experiments Challenge in Multilingual Machine Learning Project
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I also think there was a will to experiments on too many aspects at the same time and in parallel in BS: try a new organisation, a multilingual model with low-ressources languages, a new way of building a dataset (crowd sourcing of sources), attempts to train in fp16, etc etc
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Large AI Teams: BigScience Lessons on Project Organization
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yes, agree on the exhaustion feeling. BigScience was an experiment in trying to involve as many/diverse people as possible but a take-away is that too large teams can be counter-productive. Smaller projects like T0/ethics/RAIL were more successful inside BS than larger Bloom imo
