Red Lion, Recognized by UK-Based Developer of #IoT! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding
AI
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Best Books to Read 2023: Data Science and AI
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Best #Books to Read! for 2023 – by @bookauthority
! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
lnkd.in/gxjbN9FP -
MIT Offers 35 Free Machine Learning and AI Courses Online
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MIT: 35 Best Courses in Machine Learning! @MIT Explore a world of knowledge with free online courses from MIT on edX, featuring lessons in AI, machine learning, computer science engineering, circuits and electronics, Genetics, data science, statistics and much more. Many
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Top 25 IoT Influencers in Machine Learning and Data Science
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Top 25 #IoT Influencers in Machine Learning! @cbtechinc #BigData #Analytics #DataScience #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #Linux #Programming #Coding #100DaysofCode https://
geni.us/IIoT-Influence
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Discover the full article on alphaxiv.org
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read more:
alphaxiv.org/abs/2603.28765 [Translated from EN to English]→ View original post on X — @askalphaxiv, 2026-04-02 06:54 UTC
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Adaptive Block-Scaled Data Types for Efficient 4-bit LLM Quantization
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“Adaptive Block-Scaled Data Types” A lot of 4-bit LLM quantization assumes every block should use the same number format, this paper argues that’s the wrong abstraction. So they let each 16-value block choose between FP4 and scaled INT4, depending on which gives lower error. This format, IF4 (Int/Float 4), reuses the unused sign bit of the shared FP8 scale factor to store the choice, so it gets adaptivity with no extra storage overhead. This is because at 4 bits, precision is so scarce that matching the format to the local value distribution really matters. The result is lower quantization error and better performance than existing 4-bit block-scaled formats in both training and PTQ.
→ View original post on X — @askalphaxiv, 2026-04-02 06:54 UTC
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Siri’s Investors Reveal AI Innovation Insights
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This video with the investors behind Siri gives you a lot of them:
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Qwen-3.6 Plus Rivals Opus 4.6 in Benchmark Performance
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Holy sh*t: Qwen-3.6 plus comes very close to opus 4.6 evals. About time for Anthropic to drop opus 4.7 or Mythos
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AI Studying Social Behavior Patterns on X Platform
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Yeah, it's fun watching the small signals of socialness or antisocialness (or whatever you call it) here on X. The games people play to try to move up the interest graph rings… I don't know where it's all going, but I have my AI studying everybody, and it's interesting to see
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Social Media Evolving Into Interest-Based Media Platforms
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The quantity of posts being made every day has killed any sense of socialness. We are now moving into an interest media, not a social media. But I keep seeing your posts on my feed, so I guess Grok wants me to read and interact with you. So, there is a little bit of social