I grab 40,000 posts a day. Costs about $400 a day right now. On Monday will see if it goes down to $40
DATA
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Collecting 40,000 Daily Tweets Through API Access
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It is for all tweets. I grab 40,000 a day via API
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AI Data Processing Infrastructure Costs: $30 Daily for 30K Posts
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It depends how big your list is. And how active it is. A football team list probably would cost a few cents per day. My app at https://
alignednews.com/ai costs about $30 a day to grab 30,000 posts a day -
Sensor Origin Impact on IoT Procurement Strategies in 2026
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Will sensor origin still matter to your procurement team in two years? @IIoT_World @CRudinschi @agentic_factory @paul_wertz @ThyGat @kai_at_ProSyst
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AI Data Collection Service Cuts Costs from $300 to $40
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Yes. Way cheaper. My agents at https://
alignednews.com/ai grab 40,000 posts a day. $40. Way better than the $300 I was paying. -
Infrastructure gaps for autonomous energy system optimization
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What's the biggest infrastructure gap preventing your energy systems from true autonomous optimization? @IIoT_World @CRudinschi @agentic_factory @vishalpanchal85 @OneLinders @APGuha
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Data Foundation and Orchestration: Keys to Real AI Progress
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Organizations making real progress started with the foundation: normalized data, semantic context, edge compute, and orchestration to manage it all over time.
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Distributed Energy Fleets Self-Optimize With AI Edge Orchestration
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The future everyone's working toward – distributed energy fleets that self-optimize with minimal human intervention – depends on getting data normalization, semantic context, and edge orchestration right first. Partner content with @IOTechSystems. #iotechsys_iiot pic.twitter.com/vV5TgDHzxJ
— Lucian Fogoros (@fogoros) 18 avril 2026The future everyone's working toward – distributed energy fleets that self-optimize with minimal human intervention – depends on getting data normalization, semantic context, and edge orchestration right first. Partner content with @IOTechSystems
. #iotechsys_iiot -
Industrial Analytics Projects Fail Due to Data Preparation Challenges
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Industrial analytics projects have a 70% failure rate, often because the data preparation phase takes longer than expected and delivers poor quality datasets.
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Manufacturing AI Needs Operational Context for Meaningful Results
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Most AI models trained on raw manufacturing data produce useless results because they lack operational context about normal vs abnormal conditions.