Artificial Intelligence of Things AIoT book → “Hands-On AI for IoT” — Expert Machine Learning & Deep Learning techniques for developing smarter IoT systems [2nd Ed.]: http://
amzn.to/3YAu6hS 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Leverage the power of Python libraries such as TensorFlow
MACHINE LEARNING
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Book announcement: Hands-On AI for IoT 2nd Edition with TensorFlow
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Mastering NLP book: from ML foundations to LLM agents and RAG pipelines
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“Mastering NLP From Foundations to Agents” by Lior Gazit and Meysam Ghaffari, from @PacktPublishing @PacktDataML http://
amzn.to/4nJrLw4 Learn this:
•Engineer NLP systems from ML foundations to LLM architectures
•Implement RAG pipelines, routing layers, and agent -
Mastering PyTorch book covering deep learning from CNNs to LLMs
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"Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond" – http://
amzn.to/40IFEQR via @PacktDataML —————
#AI #ML #MachineLearning #DataScience #DataScientist -
PRISM: New AI Sequence Model Breaks Speed-Expressivity Trade-off
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Can AI sequence models be both expressive and blazingly fast? Researchers from Tencent, Beihang University, and Peking University present PRISM—a new sequence model that breaks the speed-expressivity trade-off. Instead of running slow, step-by-step iterations (like
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Metaprompting: ET article written a couple months back
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Metaprompting – wrote an ET article on this a couple of months back.
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AI Models Compete to Write Rubik’s Cube Solver
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Use Case 5: Rubik’s Cube Solver
— Sakana AI (@SakanaAILabs) 23 juin 2026
Can an AI write complex algorithmic solvers from scratch?
We tasked Fugu Ultra and three frontier models with writing a Rubik’s Cube solver in pure Python from a single prompt. No off-the-shelf solving libraries were allowed. We then ran the… pic.twitter.com/7xYsZrbV4UUse Case 5: Rubik’s Cube Solver Can an AI write complex algorithmic solvers from scratch? We tasked Fugu Ultra and three frontier models with writing a Rubik’s Cube solver in pure Python from a single prompt. No off-the-shelf solving libraries were allowed. We then ran the
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Grok learns from conversation, thanks entrepreneurs
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What grok learned from this conversation: https://
x.com/i/grok/share/a
1f30061cd7d4ba98d6fc22f17c6bf7b
… Thanks for inviting me to meet so many interesting entrepreneurs. -
Three models know my dog’s name
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Three of the models correctly know my dog's name! https://intheweights.com/p/cleo
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Superintelligent machines may well need us after all
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Superintelligent machines may well need us after all
by @newscientist Learn more: https://
bit.ly/4eQPAzg #ArtificialIntelligence #MachineLearning #ML -
VLM³ proves vision-language models are native 3D learners
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What if standard vision-language models already understand 3D—without complex architecture changes or special losses? Meta and Princeton University present VLM³, showing that VLMs are native 3D learners. Their recipe: unify camera focal lengths, use text-based pixel references,