Leveraging AI For Personalized User Experiences In The Dating Industry
#AI #AIio #BigData #ML #NLU #Futureofwork @DeepLearn007 @albertogaruccio @alvinfoo @andi_staub @andy_lucerne @antgrasso @BernardMarr @enricomolinari http://
ow.ly/waNg30sIPGF
MACHINE LEARNING
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AI-Driven Personalization Transforms Modern Dating Experiences
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Time-Series Databases Drive IIoT Predictive Maintenance Success
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From Data to Action
Time-series databases are the backbone of successful #IIoT data strategies. Learn how they impact #PredictiveMaintenance: https://
buff.ly/3BIiukp #sponsored #influxdata_iiot #InfluxDB #Data @IIoT_World @lucianilie15 @IoT_Consultant via @fogoros -
Python and ML/AI Engineering Tutorials Daily
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That's a wrap, if you're interested in: – Python – ML/AI Engineering Find me →
@akshay_pachaar
Everyday, I share tutorials on above topics! -
Data Science Africa: From Android phones to pan-African movement
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Day 3 of #12DaysOfChristmas for The Atomic Human @dsa_org From a $100 Android phone to the origins of a pan-African data science movement. When people come together and share purpose, things emerge organically. https://
the-atomic-human.ai/initiatives/da
ta-science-africa-i/
… #AtomicHuman -
Mathematics Role in Machine Learning and Deep Learning Research
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Shape, Symmetries, and Structure: The Changing Role of Mathematics in Machine Learning Research https://
bit.ly/3Z32DVn #AI #MachineLearning #DeepLearning #LLMs #DataScience -
DeepSeek-V3 achieves superior performance with 11x less compute than Llama
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> E.g. Llama 3 405B used 30.8M GPU-hours, while DeepSeek-V3 looks to be a stronger model at only 2.8M GPU-hours (~11X less compute). Super interesting! And DeepSeek was trained in H800’s which are probably also a tad (or noticeably?) slower than Meta’s H100’s.
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Leveraging AI to Build Trust With High-Consideration Prospects
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How To Leverage AI To Build Trust With High-Consideration Prospects
#AI #AIio #BigData #ML #NLU #Futureofwork @oluskayacan @richardkimphd @MariaFariello @johnpearcenews5 @ResurgentAV @rohanmuralee @globaliqx http://
ow.ly/xX2V30sIPGA -
Human Information Processing: Receiving vs Transmitting Capacity Limits
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Thanks Felix … I do think the "The Atomic Human" deals with this … I guess the point is that while we can receive a lot of information … we're constrained in how much we transmit — by their calculations … about 10 bits per second by mine about 30 …
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RoPE and GQA Implementation in GPT to Llama Conversion Guide
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Glad to hear that you've been enjoying it! Regarding RoPE and GQA, I've added some bonus material here a few months back where I implement it from scratch in the GPT -> Llama conversion guide: https://
github.com/rasbt/LLMs-fro
m-scratch/tree/main/ch05/07_gpt_to_llama
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I was planning to add more, but unfortunately I am currently -
Dense vs Mixture of Experts: Technical Insights and Public Sources
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Very interesting, are there any more intuition on dense vs MoE? Also hate to be that guy.. but is there a public source for this (to test okay if not)