The database architecture that made sense in the 1980s doesn't hold up in a world where agents are the primary builders. The reason is that agentic development doesn't work like traditional development. AI agents now create roughly 4x more databases than human users on Lakebase.
DATA
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Modern Time Series Analysis with R for Practical Forecasting
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Modern Time Series Analysis with R: Practical Forecasting and Impact Estimation with Tidy, Reproducible Workflows! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless
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Energy Digital Twins Drive Manufacturing Competitive Advantage
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Energy digital twins aggregate distributed energy assets across multiple factory sites and optimize grid participation in real time. For manufacturers with significant energy costs, this is not just an efficiency tool. It is becoming a direct competitive advantage as energy… pic.twitter.com/lYUK3bPcq4
— Lucian Fogoros (@fogoros) 31 mars 2026Energy digital twins aggregate distributed energy assets across multiple factory sites and optimize grid participation in real time. For manufacturers with significant energy costs, this is not just an efficiency tool. It is becoming a direct competitive advantage as energy
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AI Agents Creating Publication-Ready Charts Using Tufte Principles
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AI agents make charts fast. The output is almost always fine. Correct data, readable axes, nothing you'd actually want to publish. We encoded Tufte's principles as an AI quality bar in Truesight and told an agent to keep revising until it passed. goodeyelabs.com/insights/the…
→ View original post on X — @randal_olson, 2026-03-31 13:00 UTC
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Tata SD-WAN Enables Enterprise AI Data Center Connectivity Solutions
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Tata SD-WAN for DC connectivity in the AI age https://
cloudcomputing-news.net/news/tata-sd-w
an-for-dc-connectivity-in-the-ai-age/?utm_source=dlvr.it&utm_medium=twitter
… #Cloud #Automation #Data #EnterpriseAI #DataEngineering #DigitalTransformation #AgenticAI #CTO -
Unbounded Indexing Challenges in High-Ingestion Systems
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Indexes aren’t the problem. Unbounded indexing in high-ingestion systems is. IoT, observability, AI telemetry, financial feeds all share the same pattern: → continuous ingestion
→ append-only data
→ time-based queries
→ massive retention Eventually the architecture -
Data Analytics Roadmap 2026: Key Developments and Strategies
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#DataAnalytics Roadmap 2026
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Enterprise AI ROI: Focus on Existing Systems and Measurable Outcomes
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They all know I LOVE opensource winning
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AetheroSpace Launches Phobos Satellite for Orbital Intelligence
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Congrats to our friends @AetheroSpace on their (literal) launch! 🚀🛰️ https://t.co/8vyM7te7is
— Gill Verdon (@GillVerd) 31 mars 2026Congrats to our friends @AetheroSpace on their (literal) launch! 🚀🛰️ Edward (@somefoundersalt) Proud to announce that Phobos, the second @AetheroSpace satellite, was successfully launched to orbit earlier this morning We’re partnered with @BoozAllen on this mission to demonstrate capabilities for adaptive event detection using high-fidelity Earth observation data collected on orbit This will enable satellites to achieve faster, smarter, decision-making on orbit, and is a major step towards building the orbital intelligence layer for defense needs! — https://nitter.net/somefoundersalt/status/2038788178002522343#m
→ View original post on X — @bobgourley, 2026-03-31 05:05 UTC
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Machine Learning for Algorithmic Trading with Python
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Machine Learning for Algorithmic Trading — Predictive models to extract signals from market and alternative data for systematic trading strategies with Python Useful for *other* Time Series prediction applications also! Get it at http://
amzn.to/47Vd6s8 by @ml4trading