Manage complexity in Kubernetes with AI and machine learning
#AI #AIio #BigData #ML #NLU #Futureofwork @ahier @guzmand
@DavidBrin @denisegarth @dez_blanchfield @diioannid @DioFavatas @gerald_bader http://
ow.ly/mqQA30sw8BG
MACHINE LEARNING
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Managing Kubernetes Complexity with AI and Machine Learning
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ML Tools Must Support Collaboration Across Diverse Teams
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"Do my #ML tools support collaborating w/ diverse people (from #datascientist to #engineer to #analyst) to understand a model's behavior? This is table stakes." – Predibase CEO @w4nderlus7
— Predibase by Rubrik (@predibase) 17 juillet 2023
Great talk w/ @robstersayspodcast on How #AI Happens podcast. Full link in comments. pic.twitter.com/zocJjyuO0d"Do my #ML tools support collaborating w/ diverse people (from #datascientist to #engineer to #analyst) to understand a model's behavior? This is table stakes." – Predibase CEO @w4nderlus7 Great talk w/ @robstersayspodcast on How #AI Happens podcast. Full link in comments.
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FlashAttention-2: Faster Attention with Better Parallelism
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FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning paper: https://
tridao.me/publications/f
lash2/flash2.pdf
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github: https://
github.com/Dao-AILab/flas
h-attention
… Scaling Transformers to longer sequence lengths has been a major problem in the last several years, promising to improve performance -
MIT’s AI Predicts Molecular Properties With Minimal Data
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ML models need to be trained on millions of labeled molecular structures to predict its properties. By contrast, MIT’s AI only needs a small amount of data, outperforming other ML approaches & potentially speeding up drug discovery: http://
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Process Mining and RPA Integration for Organizational Efficiency
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Automatically capture all activity across your organization, identify and diagnose the cause of bottlenecks, and calculate granular ROI — all thanks to integrating a value-rich Process Mining solution with Robotic Process Automation (RPA). Learn more: https://
ibm.co/3rw9JVe -
Causalvis: Visualizations for Causal Inference Tool
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Causalvis: Visualizations for Causal Inference https://
bit.ly/43req0S #MachineLearning #AI #DataScience #DeepLearning -
Master Matrix Calculus for Deep Learning
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If you want to understand the matrix calculus you need for Deep Learning, here is where you need to go: https://
explained.ai/matrix-calculu
s/index.html
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Domino Named CRN Tech Innovator for Fourth Consecutive Year
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We're honored to be named a @CRN Tech Innovator four years in a row. Thank you to our customers and partners for allowing us to help them build game-changing #AI quickly, responsibly and cost effectively. https://
domino.buzz/3NYPwiv #datascience #MLOps -
Perceiver IO: Unified Neural Network for Multiple Modalities
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"Life would be drastically simpler if a single neural network architecture could handle a wide variety of both input modalities and output tasks." – Perceiver IO
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C4 Dataset Context Length Limitations Impact LLM Benchmarking
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The C4 dataset has nothing in it longer than 4096, which means that it’s not pushing at longer context lengths. This can have some interesting implications when benchmarking LLMs trained at different sizes. pic.twitter.com/pLqVk4hCN6
— Replit ⠕ (@Replit) 17 juillet 2023The C4 dataset has nothing in it longer than 4096, which means that it’s not pushing at longer context lengths. This can have some interesting implications when benchmarking LLMs trained at different sizes.