The industrial edge is getting significantly smarter. This came up at a plant visit last week. @IIoT_World @CRudinschi @agentic_factory @IotoneHQ @Softnet_Search @SmartIndustryUS
COMPUTING
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Reading data in place keeps production systems running smoothly
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Reading data in place means production systems keep running while analytics teams get the structured data they need.
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DataHub Intelligence: In-Place Data Integration Without Migration Risk
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Traditional data integration: rip out systems, migrate terabytes, pray nothing breaks.
— Lucian Fogoros (@fogoros) 11 avril 2026
DataHub Intelligence: read in place, contextualize on demand, deliver clean datasets.
Same result, zero migration risk. Partner content with @HighbyteInc. #highbyte_iiot pic.twitter.com/irPHcL5teWTraditional data integration: rip out systems, migrate terabytes, pray nothing breaks.
DataHub Intelligence: read in place, contextualize on demand, deliver clean datasets.
Same result, zero migration risk. Partner content with @HighbyteInc
. #highbyte_iiot -
Symbolic Code Refactoring: Beyond Neural Networks
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code is code; it’s not a neural network, it’s symbolic but yet it does sound like it needs a refactoring.
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Using Hetzner VPS with Tailscale, Termius, Claude Code, and Mosh
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I use @Hetzner_Online and just have VPS that are isolated via Tailscale (for safety) then I SSH into them with Termius and work on there with Claude Code and I often have Mosh running so it stays alive easier
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Meta Proposes Neural Computers: Unified Computation Memory I/O Architecture
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NEW paper from Meta What if the model wasn’t just using the computer… but actually became the computer? A new paper from Meta AI + KAUST makes a compelling case for Neural Computers (NCs) — a paradigm where computation, memory, and I/O are unified inside a single latent
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LLM Infrastructure Stuck in 1990s Like Linux
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And just like Linux, LLM infra will never get out of 90s.
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R Reference Card for Data Mining and Analytics
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R Reference Card for Data Mining! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/R-Ref-Card-DataMinin…
→ View original post on X — @gp_pulipaka, 2026-04-11 14:26 UTC
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Smartphones Process Locally While Cloud Handles Heavy Workloads
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Modern smartphones are powerful enough to handle many tasks locally, shifting more processing from the cloud to the device itself. The future is a hybrid model where everyday tasks run on-device while heavier workloads are handled in the cloud for scale. pic.twitter.com/KxZnTAthKV
— Satya Mallick (@LearnOpenCV) 11 avril 2026Modern smartphones are powerful enough to handle many tasks locally, shifting more processing from the cloud to the device itself. The future is a hybrid model where everyday tasks run on-device while heavier workloads are handled in the cloud for scale.
→ View original post on X — @learnopencv, 2026-04-11 13:32 UTC