How the 4 roles of AI redefine your strategy
#AI #AIio #BigData #ML #NLU #Futureofwork @oluskayacan @richardkimphd @MariaFariello @johnpearcenews5 @ResurgentAV @rohanmuralee @globaliqx
MACHINE LEARNING
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How the 4 roles of AI redefine your strategy
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Learn Data Science and Machine Learning Modeling Online Courses
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Learn from my 2 online #DataScience #MachineLearning Modeling Courses here:
DS 101: https://
aiplus.odsc.com/courses/ds-101
-machine-learning-modelling-in-theory-practice
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DS 102: https://
app.aiplus.training/courses/ds-102
-machine-learning-modelling-in-theory-practice
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#BigData #AI #DataScientists #PredictiveModeling #ML #DataLiteracy #PredictiveAnalytics #IoT #IIoT @_odsc https://
x.com/KirkDBorne/sta
tus/1786085450861412677
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Mistral AI Enters the Conversation
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Mistral has entered the chat https://
bit.ly/3V3eWzB
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
GPU Chips Neural Networks Big Data Foundation Modern AI
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Modern AI was forged from 3 converging elements of computing – GPU chips, Neural Network algorithms, and Big Data. I’m honored to share this recognition with my colleagues and friends @geoffreyhinton @ylecun @Yoshua_Bengio and Jensen Huang @nvidia . #ImageNet would not have been
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LLM struggles with counting and arithmetic despite code workarounds
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Yeah, it’s actually not a hard problem in code — you just iterate over x values from 0 until you find one that works. What makes it remarkable here is just that counting letters and arithmetic are traditionally hard for LLMs and o1 claims to not be using tools/code
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Simpson’s Paradox and Sampling Bias in Data Analysis
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That's sampling bias right there.
Classic Simpson's paradox at play -
Python, Machine Learning, and AI Engineering Tutorials Daily
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If you interested in: – Python – Machine Learning – AI Engineering Find me → @akshay_pachaar Everyday, I share tutorials on above topics! Cheers!
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Understanding Embedding Models: Text to Numerical Representation
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The embedding model Embedding is a meaningful representation of text in form of numbers. The embedding model is responsible for creating embeddings for the document chunks & user queries.
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Major VLM Revolution: Open-Source Models from Google, OpenGVLabs, Qwen, Microsoft
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VLMs are going through quite an open revolution AND on-device friendly sizes: > Google DeepMind w/ PaliGemma2 – 3B, 10B & 28B > OpenGVLabs w/ InternVL 2.5 – 1B, 2B, 4B, 8B, 26B, 38B & 78B > Qwen w/ Qwen 2 VL – 2B, 7B & 72B > Microsoft w/ FlorenceVL – 3B & 8B (Links below)
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Phrase Matching Techniques in Marginalia Search Engine
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Phrase Matching in Marginalia Search https://
bit.ly/4gf76v4 #AI #MachineLearning #DeepLearning #LLMs #DataScience