The system automatically handles protocol conversion, data formatting, and even adds timestamps and quality flags to every data point.
SYSTEMS
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Lakebase Autoscaling Adjusts Compute Resources Dynamically
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Lakebase autoscaling adjusts compute dynamically based on CPU load, memory usage, and working set size, within developer-defined limits. Scaling happens automatically without database restarts, so connections stay open while resources adjust to demand. Paired with scale to zero,
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Will AI Systems Continue to Experience Erratic Behavior?
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are the systems going to continue be erratic?
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Grid Integration Challenges for AI Infrastructure Deployment
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You can’t always “just connect to the grid”
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USB Checkpoint Security: File Cleaning Between IT and OT
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Kiosk-based media scanning sits between IT and OT areas. Every USB drive passes through a checkpoint where files are cleaned and rebuilt.
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Karpathy’s Self-Improving AI Knowledge Base System
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Karpathy’s new set-up is the ultimate self-improving second brain, and it takes zero manual editing It acts as a living AI knowledge base that actually heals itself. Let me break it down. Instead of relying on complex RAG, the LLM pulls raw research directly into an
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Rethinking AI: Structure, Time, Ethics, Context Integration
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"The system no longer asks what the answer is. It asks what must be true for that answer to hold across structure, time, ethics, and context simultaneously," Will Burns writes here. Over the years I've had many conversations with Will. He is a deep thinker and here he argues
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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://
geni.us/Smart-Cities-A
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Gateway Architecture Design for Adversarial Agents
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A lot of it is not-understanding-architecture. For example, gateway is not designed for adversarial agents hosted in one process – if you want total isolation run gateway multiple times. Yet we get so many reports trying to refactor this into a much more complex architecture that
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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