Identifying the root cause of a turbine trip manually takes 6 to 10 hours. GenAI drops that to nearly instant response time.
ENTERPRISE AI
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GenAI and RAG Automate Industrial Diagnostics and Troubleshooting
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GenAI and RAG instantly search manuals, logs, and forums to provide probable cause and recommended action.
— Lucian Fogoros (@fogoros) 31 mars 2026
No more digging through 6,000-page turbine manuals. AI agents layer over ML tools to give context to anomalies.
From alert to answer in seconds. pic.twitter.com/eYiljr3nPuGenAI and RAG instantly search manuals, logs, and forums to provide probable cause and recommended action.
No more digging through 6,000-page turbine manuals. AI agents layer over ML tools to give context to anomalies.
From alert to answer in seconds. -
Create Production-Ready AI Agents in 5 Minutes with DataRobot
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Have an idea? Make it a production agent ready in 5 minutes through @DataRobot
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Designing and Running Successful AI Initiatives Simply
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Keep It Simple: How To Design And Run A Successful #AI Initiative
by @kedkorte @Forbes Learn more: https://
bit.ly/4rVzmbt #ArtificialIntelligence #MachineLearning #ML -
Paul Roetzer Joins Microsoft to Bring OpenClaw Personal Agents to Microsoft 365
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🦞 TL;DR: New Job at Microsoft. Bringing OpenClaw + personal agents to Microsoft 365! My goal is to help usher in a new generation of workplace proactive assistants, ones that lighten your load by taking on tasks end-to-end, and that can also step in proactively when they can help. As part of this mission, I’ll be partnering with the @OpenClaw + M365 community to bring the energy of this work to our customers. We’ve already hit the ground running with a fully integrated Teams plugin for OpenClaw, and I can’t wait to help usher in the era of personal agents at work.
→ View original post on X — @paulroetzer, 2026-03-31 16:52 UTC
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Anthropic Launches Enterprise AI Services, Partners with Wall Street Firms
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The # of DMCAs Anthropic is about to send is going to be crazzzy I personally will spin up 3 Hermes agents to rewrite it in Rust, Zig, and C
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Economic Graph Enables World Model and Intelligence Reorganization
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The scale you have with the economic graph means the world model and intelligence layers have enough mass to make sense. Leaves me wondering if other types of orgs will struggle with this type of re-org as they don’t have one, both, or either.
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Industrial AI Competitive Advantage Through Contextualized Data Integration
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#Paid Partnership with Siemens
— Lucian Fogoros (@fogoros) 31 mars 2026
"Tailored, domain-specific insights often outperform generic AI strategies." Samuel Schuler, Reimann Investors. The competitive battle in Industrial AI will be won by the company with the best contextualized data and the deepest integration into… pic.twitter.com/aj2wrQcLu3#Paid Partnership with Siemens
"Tailored, domain-specific insights often outperform generic AI strategies." Samuel Schuler, Reimann Investors. The competitive battle in Industrial AI will be won by the company with the best contextualized data and the deepest integration into -
Semantic Collapse: Fixing AI Agent Production Issues at Root
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Semantic collapse is killing production agents and this team is actually fixing it at the root.
— AI Highlight (@AIHighlight) 31 mars 2026
Not patching it. Fixing it. https://t.co/4Vbq4v9q5YSemantic collapse is killing production agents and this team is actually fixing it at the root. Not patching it. Fixing it. Nishkarsh (@contextkingceo) AI agents are failing in production…not a surprise. As you scale your knowledge base, embeddings start creating noise. It’s called ‘semantic collapse’ – when conversations run too long, you have hundreds of PDFs, millions of data points to give to your AI. Your AI can’t flag it because it doesn’t know it’s hallucinating. Similarity gets passed off as relevance. Fix your context. Make your agents work. Build intelligent AI. If your AI is plateauing at 50% accuracy and hallucinations are still a problem, let's talk. Book a 20 minute demo with the link in the next thread. We'll dig into your setup and find out how we can help. — https://nitter.net/contextkingceo/status/2038979631144116613#m
→ View original post on X — @aihighlight, 2026-03-31 15:31 UTC
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Three Keys to AI Success: Internal Use, Industrialization, and Control
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My takeaway is simple: The next 2 to 3 years will reward companies that do 3 things well: → use AI internally, so leadership understands it firsthand
→ build with a clear path from pilot to industrialization
→ take control of their own models, data, and evaluation strategy