Global AI News Aggregator
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20 Most Important AI Concepts Explained! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #Books #100DaysofCode geni.us/20-Concepts-Xplained
→ View original post on X — @gp_pulipaka, 2026-04-07 14:26 UTC
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Building a Self Improving Agentic RAG! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #Books #100DaysofCode geni.us/Building-Improving-R…
→ View original post on X — @gp_pulipaka, 2026-04-07 14:26 UTC
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Harvard Opens More Free Online Courses in AI, Data Science! #BigData #Analytics #AI #MachineLearning #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/Harvard-Courses-AI
→ View original post on X — @gp_pulipaka, 2026-04-07 14:26 UTC
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A Practical Guide to Reinforcement Learning from Human Feedback! Review of the Book! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #Books #100DaysofCode geni.us/Practical-Guide-RL geni.us/Review-of-Book
→ View original post on X — @gp_pulipaka, 2026-04-07 14:26 UTC
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Agentic Maritime Anomaly Analysis with Generative AI! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/Agentic-Maritime
→ View original post on X — @gp_pulipaka, 2026-04-07 14:26 UTC
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Ready to see what’s next in data, AI, and innovation? 👀
— SAS Software (@SASsoftware) 7 avril 2026
Experience it all at #SASInnovate April 27-30, where big ideas turn into real impact and the future gets a little more exciting.
See you there ✨ https://t.co/B03NE0gZ14 pic.twitter.com/pMcXTzgG2d
Ready to see what’s next in data, AI, and innovation? Experience it all at #SASInnovate April 27-30, where big ideas turn into real impact and the future gets a little more exciting. See you there http://
2.sas.com/6018B6tmHp
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🔥 JUST IN:
— Lukas Ziegler (@lukas_m_ziegler) 7 avril 2026
Open-source robotics dataset from 100% real-world scenarios! 🤯
Chinese robotics company @AGIBOTofficial just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions.
Built entirely from real-world… pic.twitter.com/aADoukKKiO
🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company @AGIBOTofficial just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: agibot-world.com/ ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com
→ View original post on X — @clementdelangue, 2026-04-07 13:30 UTC
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Supply chains generate continuous streams of operational data across production and compliance processes. AI links these signals along the product journey, enabling traceability and faster response when disruptions, regulatory checks, or trust issues appear. Microblog @antgrasso
→ View original post on X — @antgrasso, 2026-04-07 13:02 UTC
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🚨 Over 1 billion rows of psychiatric genetics data. Now on Hugging Face. ADHD. Depression. Schizophrenia. Bipolar. PTSD. OCD. Autism. Anxiety. Tourette. Eating disorders. 12 disorder groups. 52 publications. Every GWAS summary statistic from the Psychiatric Genomics Consortium. Before: wget, gunzip, 20 minutes debugging separators, repeat 50 times. Now: one line of Python.
→ View original post on X — @clementdelangue, 2026-04-07 13:00 UTC
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#DataScience Trends by @Python_Dv #AI #GenerativeAI #BigData
→ View original post on X — @ronald_vanloon, 2026-04-07 11:20 UTC