Probabilistic Machine Learning. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
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COMPUTING
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Probabilistic Machine Learning: Techniques and Tools Guide
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What is Data Science: Big Data Analytics and Machine Learning
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What's Data Science? #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
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Smart Cities and AI: Big Data Analytics Integration
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#SmartCities and Artificial Intelligence. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
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Probabilistic Machine Learning: Tools and Technologies Overview
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Probabilistic Machine Learning! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode
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Holodeck Technology Becomes Sharper and More Advanced
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The Holodeck is getting sharper. https://t.co/Qt2ZjibifV
— Robert Scoble (@Scobleizer) 2 avril 2026The Holodeck is getting sharper.
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Block Launches Mesh-LLM, a Decentralized Peer-to-Peer AI System
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Block just open-sourced mesh-llm, a peer-to-peer system that lets anyone pool spare GPU compute to run large open-source AI models without relying on any cloud provider. If a model fits on your machine, it runs locally at full speed. If it doesn't, the system automatically splits it across multiple machines on the network. Dense models get split by layers. Mixture-of-experts models like DeepSeek and Qwen3 get split by experts. Zero configuration required. Discovery happens over Nostr. Nodes find each other through relays, score by region and VRAM, and self-organize. No central server coordinates anything. Weights are read from local files, never sent over the network. Dead nodes get replaced in 60 seconds. It exposes a standard OpenAI-compatible API on localhost, meaning any existing AI tool can plug in without modification. Block is building infrastructure for AI that doesn't route through OpenAI, Google, or Anthropic. Frontier-class open models running across a mesh of commodity hardware, discovered via Nostr, with no cloud dependency. That's the direction AI needs to go. [Translated from EN to English]
→ View original post on X — @whiteafrican, 2026-04-02 23:14 UTC
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Local AI Models Running on Laptop Hardware
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More evidence of move to local models.
— Robert Scoble (@Scobleizer) 2 avril 2026
This one running on the claw. On a laptop. https://t.co/oEGqhlQ9JQMore evidence of move to local models. This one running on the claw. On a laptop.
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Atomic Bot enables local OpenClaw AI
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Atomic Bot now makes it easier to run OpenClaw fully locally on your machine, using API keys or tokens, with no cloud in the loop.
— 🚨 AI News | TestingCatalog (@testingcatalog) 2 avril 2026
Pick a local model, and your personal AI assistant runs entirely on your own hardware.
Available now on macOS and Windows 👀 https://t.co/uzKuaOBhsO pic.twitter.com/RuVKLfrKtOAtomic Bot now makes it easier to run OpenClaw fully locally on your machine, using API keys or tokens, with no cloud in the loop. Pick a local model, and your personal AI assistant runs entirely on your own hardware. Available now on macOS and Windows
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Cloud Role and Advanced AI Models Infrastructure Future
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Cloud still has a role. We'll want real time data about the world (like is your favorite restaurant open right now) and the high end will want the best possible models to do advanced stuff (coding, simulations, etc). But NVIDIA was running its very advanced world model-based
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Chip Design Requires Predicting the Future Four Years Ahead
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The AI market moves fast, but chips take years to build. In his @TEDTalks, @RodrigoLiang shares why chip design is part science, part vision, part predicting the future 4 years from now.
— SambaNova (@SambaNovaAI) 2 avril 2026
Watch his full talk 👇
https://t.co/19qDsfiHlk pic.twitter.com/qOQSpLdFjiThe AI market moves fast, but chips take years to build. In his @TEDTalks, @RodrigoLiang shares why chip design is part science, part vision, part predicting the future 4 years from now. Watch his full talk 👇 bit.ly/41G3vAO
→ View original post on X — @sambanovaai, 2026-04-02 21:05 UTC