2nd Edition — now at http://
amzn.to/45Y3LyI v/ @PacktDataML Graph Machine Learning — Latest advancements in Graph Data to build robust #MachineLearning algorithms 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Master new graph ML techniques through updated examples using PyTorch Geometric and
MACHINE LEARNING
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Graph Machine Learning 2nd Edition with PyTorch Geometric Advancements
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Mastering PyTorch: Create and Deploy Deep Learning Models
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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 #GenAI
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Kirk Borne Offers Over 4600 Free Resources for X Subscribers
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I continue adding more 𝐅𝐑𝐄𝐄 resources for my @X Subscribers to access: 𝗼𝘃𝗲𝗿 𝟰𝟲𝟬𝟬 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗮𝗿𝗲 𝗻𝗼𝘄 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲. Subscribe for only US$6/month #MachineLearning #ML #AI #DataScience #Python #Mathematics #Statistics #SQL #GenAI #AgenticAI
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Attention Residuals: Novel Architecture for Transformer Models
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Attention Residuals Paper: https://
github.com/MoonshotAI/Att
ention-Residuals/blob/master/Attention_Residuals.pdf
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Code: https://
github.com/MoonshotAI/Att
ention-Residuals
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Attention Residuals: Smart Learned Aggregation in Neural Networks
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Huge! @Kimi_Moonshot presents Attention Residuals (AttnRes)! This new technique replaces fixed accumulation in standard residual connections with smart, learned attention over preceding layer outputs, letting models dynamically aggregate information. Their 'Block AttnRes'
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ELLIS Board: Florence d’Alché-Buc on AI and Data
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👋 Meet the ELLIS Board This episode features Florence d’Alché-Buc, Professor at @telecomparis 🇫🇷 and ELLIS Board Member. She shares her views on data vs. algorithms, causality, foundation models, and how AI systems should be evaluated. Watch the video: piped.video/kgLCpIUEwiY
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Pokémon Go’s 30 Billion Images Secretly Built Massive AI Dataset
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143 millions de personnes pensaient chasser des Pokémon.
— VISION IA (@vision_ia) 16 mars 2026
En réalité, elles construisaient l'un des plus grands datasets visuels du monde réel de l'histoire de l'IA.
Niantic vient de révéler que les photos et scans AR collectés via Pokémon Go représentent plus de 30 milliards… https://t.co/lEauNwHvpE143 million people thought they were hunting Pokémon.
In reality, they were building one of the largest real-world visual datasets in the history of AI.
Niantic just revealed that the photos and AR scans collected via Pokémon Go represent more than 30 billion images.
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Deformable Part Models: Flexible Object Detection Breakthrough
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📌 The Rise of Deformable Part Models in Object Detection
— Satya Mallick (@LearnOpenCV) 16 mars 2026
Imagine trying to detect a person walking 👣. Their arms move, legs bend, head turns – rigid detectors couldn’t handle this flexibility. In 2008, researchers introduced Deformable Part Models (DPM), a breakthrough that… pic.twitter.com/6diFdj9a2gThe Rise of Deformable Part Models in Object Detection Imagine trying to detect a person walking . Their arms move, legs bend, head turns – rigid detectors couldn’t handle this flexibility. In 2008, researchers introduced Deformable Part Models (DPM), a breakthrough that
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StitchCUDA: AI Framework Automatically Optimizes GPU ML Programs
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What if AI could automatically write and optimize entire GPU programs for your ML workloads? Researchers from the University of Minnesota-Twin Cities introduce StitchCUDA. This multi-agent framework features a Planner, Coder, and Verifier. The Coder uses innovative rubric-based
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SGD as ResNet: Rethinking Attention Architecture Fundamentals
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SGD is a ResNet too (the blocks of it are fwd+bwd), the residual stream is the weights so… We're not taking the Attention is All You Need part literally enough? 😀