Challenges and Applications of Large Language Models A comprehensive review of the problems that remain unsolved in LLMs arena. The paper also provides a broad overview of application areas of LLMs and highlights some common application architectures across domains. This is
MACHINE LEARNING
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General Ability vs Situational Competence in AI Systems
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There's a big difference between possessing a *general* ability vs being able to show the appearance of competence in specific situations. AI has always excelled at the latter, but the value is in the former.
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Modern Columnar Data Format for ML and LLMs in Rust
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Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. https://
bit.ly/3NwSGek #AI #MachineLearning #DeepLearning #LLMs #DataScience -
The Path To Empathetic Software Automation
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The Path To Empathetic Software Automation
#AI #AIio #BigData #ML #NLU #Futureofwork @TunstallAsc @StrategyFintech @TamaraMcCleary @TerenceLeungSF @psb_dc @thomaspower @vinod1975 @ylecun http://
ow.ly/nyls30swkQj -
Learning Real World Machine Learning Recommended Resource
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Awesome! Recommended to anyone interested in learning how real world ML works!
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MIT Dataset Enables Precise Semantic Image Captions for Accessibility
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Training ML models w/MIT’s new dataset empowers them to create precise, semantically dense captions, while illustrating data trends & intricate patterns. It could help improve accessibility for those w/visual disabilities: https://
bit.ly/3D6VwQZ -
Likelihood Versus Probability: Key Differences in Data Science
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What is the Difference Between Likelihood and Probability?: Likelihood and probability are interrelated and often confused terms finding common usage in data science and business. Both probabilities are associated with probabilities but differ in… https://
analyticsvidhya.com/blog/2023/06/l
ikelihood-vs-probability/?utm_source=dlvr.it&utm_medium=twitter
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Self-Attention Mechanism in Large Language Models Explained
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Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch https://
bit.ly/3YL821l #AI #DeepLearning #MachineLearning #DataScience -
Why DeepMind Never Released AlphaGo to the Public
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I wonder this is the reason why DeepMind has never released AlphaGo (or any of its variants), and has never let the general public play against it. So that no one will be able to find holes in it, and show that, just like other AIs, AlphaGo can easily be defeated or jail broken.
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Data Science and ML Learning Resources Thread
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End of this thread! If you are looking to learn more about
Data Science
ML/DL/AI
Analytics
Math & Statistics
Resources
MLOps Then, Don't forget to follow me at @avikumart_ for upcoming posts