Zero-shot forecasting of chaotic systems https://
bit.ly/3XMvnBe
New foundation models are showing promise for zero-shot learning in chaotic systems that reveals they can compete with custom models, capturing long-term behaviors #AI #MachineLearning #DeepLearning #LLMs
MACHINE LEARNING
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Foundation Models Master Zero-Shot Learning in Chaotic Systems
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Artificial Intelligence Transforming Human Resources and Workforce
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How Artificial Intelligence is Transforming Human Resources and the Workforce
#AI #AIio #BigData #ML #NLU #Futureofwork @ahier @guzmand
@DavidBrin @denisegarth @dez_blanchfield @diioannid @DioFavatas @gerald_bader -
New Robot Imitation Learning Approach Presentation at CORL
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Looking fwd to Justin and Chung-Min presenting this exciting new approach to robot imitation learning @corl_conf https://t.co/Y4D0OwhCBM
— Ken Goldberg (@Ken_Goldberg) 2 octobre 2024Looking fwd to Justin and Chung-Min presenting this exciting new approach to robot imitation learning @corl_conf
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Training Machine Learning Models on 10k H100 GPUs
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"How to train a model on 10k H100 GPUs?"
has now been immortalized on my blog: https://
soumith.ch/blog/2024-10-0
2-training-10k-scale.md.html
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Targeting checkpointing improvements planned for machine learning
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it's on our list of things to do (more targeting checkpointing, not FSDP). I wrote up a plan / doc early last year about it.
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Data Engineers Critical for GenAI Success and Code Development
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The best #GenAI models will not succeed without good data. That’s why data engineers are even more critical today. This guide shares practical guidance on using AI tools for faster code dev, implementing data governance & more. Read here
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ChainBuddy: AI Agent System for Generating LLM Pipelines
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ChainBuddy: An AI Agent System for Generating LLM Pipelines https://
bit.ly/3ZSq8Tf
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Training Models at Scale: 10K+ H100 Infrastructure Guide
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quick mini-post I wrote for @francoisfleuret broadly summarizing the things one needs to do to train models on 10k+ H100s.
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Face Detection Study Reduces False Positives for Autonomous Systems
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The study could potentially help face detection systems by reducing false positives, which might impact self-driving cars, human-computer interaction, & robotics. The dataset & models could also help areas like product design.