Plants generating thousands of data points per second need message throughput that MQTT cannot provide. The protocol was designed for low-bandwidth IoT devices, not high-frequency industrial sensors.
ENTERPRISE AI
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MQTT QoS 2 latency bottleneck in industrial sensor networks
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MQTT protocol overhead becomes the bottleneck at industrial scale. Each QoS 2 message requires four network round-trips to confirm delivery, creating latency walls that sensor networks cannot break through.
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IP dispute over Uber demand prediction algorithms clarified
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This is brazenly false, @vkhosla
. 1. To clarify my understanding, I followed up with someone who stayed at Uber longer than I was. The core intellectual property that we developed at Geometric (I was a co-developer thereof) was embedded in supply and demand prediction of pricing -
MQTT QoS Latency Limits Industrial IoT Sensor Networks
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MQTT QoS 2 with 125ms latency caps at 4 messages per second. QoS 1 caps at 8. For a plant with thousands of sensors updating every second, that math breaks fast. Partner content with @skkynetinc. #HM26 #skkynet_ai pic.twitter.com/20zoDHb79w
— Lucian Fogoros (@fogoros) 11 avril 2026MQTT QoS 2 with 125ms latency caps at 4 messages per second. QoS 1 caps at 8. For a plant with thousands of sensors updating every second, that math breaks fast. Partner content with @skkynetinc
. #HM26 #skkynet_ai -
Teaching AI to recognize normal voltage patterns across time
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How do you explain to an AI model what 'normal' voltage looks like at 3pm versus 3am? @IIoT_World @CRudinschi @agentic_factory @JoeSpeeds @RichRogers_ @andreacreativo
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Denmark’s pharma and tech sectors driving AI innovation
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its danemark so i'd guess pharma and tech
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MIT Sloan Review: Latest Developments in Artificial Intelligence Applications
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Putting #AI to work: The latest from MIT Sloan Management Review by Brian Eastwood @MITSloan Learn more: bit.ly/41gLQzI #MachineLearning #ArtificialIntelligence #ML
→ View original post on X — @ronald_vanloon, 2026-04-11 19:49 UTC
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Context Over Volume: Data Intelligence in Energy Operations
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The gap between data-rich and insight-poor is almost always a context problem, not a volume problem in energy operations.
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Claude Code Quality Decline: AMD Director Reports Rising Laziness Issues
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AMD’s AI director Stella Laurenzo claims Anthropic’s Claude Code has significantly declined in quality since early March, citing analysis of 6,800+ sessions and 234k tool calls showing rising “laziness” behaviors like shallow reasoning, skipping code review, and incomplete tasks. Honestly, this is more impactful than expected, engineers report the model now favors quick, incorrect fixes over deep problem-solving, raising trust issues for complex workflows.
→ View original post on X — @kimmonismus, 2026-04-11 19:42 UTC
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Semantic Tagging Enables AI Understanding of Industrial Sensor Data
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Semantic tagging provides the context AI models need to understand what a voltage reading actually means. Without knowing the asset, operating context, and grid topology position, models are processing numbers without meaning. Partner content with @IOTechSystems. #iotechsys_iiot pic.twitter.com/kr94pAhnAc
— Lucian Fogoros (@fogoros) 11 avril 2026Semantic tagging provides the context AI models need to understand what a voltage reading actually means. Without knowing the asset, operating context, and grid topology position, models are processing numbers without meaning. Partner content with @IOTechSystems
. #iotechsys_iiot