@mvollmer1 @iotjuice @jamesvgingerich @IIoT_World @CRudinschi @agentic_factory This covers critical ground on predictive maintenance and asset reliability.
AUTOMATION
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LaserWeeder G2 Revolutionizing Farming Technology Across Seven Countries
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LaserWeeder G2 Is Transforming Farming Across 7 Countries
— Ronald van Loon (@Ronald_vanLoon) 7 avril 2026
by @carbon_robotics#AgriTech #TechForGood #Innovation #Tech #Technology pic.twitter.com/wcpugvBsjYLaserWeeder G2 Is Transforming Farming Across 7 Countries by @carbon_robotics #AgriTech #TechForGood #Innovation #Tech #Technology
→ View original post on X — @ronald_vanloon, 2026-04-07 21:50 UTC
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Mutiny launches AI agent for GTM teams creating customer content minutes
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Imagine having a prospect call.
— Charly Wargnier (@DataChaz) 7 avril 2026
5 mins later, you send them a custom microsite, perfectly branded with their exact pain points and CRM data.
That’s what @mutinycorp just unlocked today.
oh… and they hit 8-figures ARR + raised $72M from Sequoia/YC along the way 👀 https://t.co/xKqnlHf4GpImagine having a prospect call. 5 mins later, you send them a custom microsite, perfectly branded with their exact pain points and CRM data. That’s what @mutinycorp just unlocked today. oh… and they hit 8-figures ARR + raised $72M from Sequoia/YC along the way 👀 Jaleh Rezaei (@jalehr) We raised $72M from Sequoia/YC and hit 8-figures in ARR. Then we shut it all down & rebuilt the company from scratch. Today we’re launching the new Mutiny: the first AI agent for GTM teams to create anything customer-facing, in minutes. Comment "Mutiny" to get 3X free credits. — https://nitter.net/jalehr/status/2041546131709292586#m
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Abacus AI: Integrating AI into Your Real Infrastructure
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"AI agents will replace teams" is the narrative right now. At Abacus AI, it's less about hype, more about wiring AI into your actual stack – Slack, Drive, CRM, warehouses – all in real time. That's when it stops being a demo and starts working like infrastructure. [Translated from EN to English]
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Karpathy’s Self-Improving AI Knowledge Base with Obsidian
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ICYMI here's more info about Andrej’s new method nitter.net/DataChaz/status/203996… Charly Wargnier (@DataChaz) 🚨 Karpathy’s new set-up is the ultimate self-improving second brain, and it takes zero manual editing 🤯 It acts as a living AI knowledge base that actually heals itself. Let me break it down. Instead of relying on complex RAG, the LLM pulls raw research directly into an @Obsidian Markdown wiki. It completely takes over: ✦ Index creation ✦ System linting ✦ Native Q&A routing The core process is beautifully simple: → You dump raw sources into a folder → The LLM auto-compiles an indexed .md wiki → You ask complex questions → It generates outputs (Marp slides, matplotlib plots) and files them back in The big-picture implication of this is just wild. When agents maintain their own memory layer, they don’t need massive, expensive context limits. They really just need two things: → Clean file organization → The ability to query their own indexes Forget stuffing everything into one giant prompt. This approach is way cheaper, highly scalable… and 100% inspectable! — https://nitter.net/DataChaz/status/2039963758790156555#m
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Karpathy’s Autonomous Obsidian Wiki System Replaces Traditional RAG
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🚨 @karpathy literally ditched traditional RAG for an autonomous Obsidian file system. Instead of writing code, he dumps raw AI research into a local folder and lets an LLM convert it into an interconnected markdown wiki. He rarely edits the text manually. By relying purely on dynamically updated index files, the system navigates the exact context it needs natively without relying on flawed vector embeddings. Because the LLM fully understands the file structure, it executes advanced autonomous workflows: → Operates a custom vibe-coded local search engine → Renders complex charts and formatted markdown slides → Continuously compounds a 400,000-word knowledge base The most fascinating mechanic is the self-healing loop. He triggers background health checks where the LLM natively spots structural gaps, scrapes the internet for missing data, and cleans the articles perfectly. This feels the absolute blueprint for managing complex technical data 🔥 btw, he also plans to fine-tune a local model directly on the wiki so the research is baked into the neural weights rather than relying on limited context windows 👀
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AI-Powered Ransomware Defense for Manufacturing Security
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Manufacturing is the number one target for ransomware. Production downtime costs more per minute than office downtime. 30,000 installations, zero inbound ports. Ask how at Stand A12, Hall 27. Partner content with @skkynetinc. #HM26 #skkynet_ai pic.twitter.com/UgAjWCCrd8
— Lucian Fogoros (@fogoros) 7 avril 2026Manufacturing is the number one target for ransomware. Production downtime costs more per minute than office downtime. 30,000 installations, zero inbound ports. Ask how at Stand A12, Hall 27. Partner content with @skkynetinc
. #HM26 #skkynet_ai -
Anthropic Uses Claude to Automate Growth Strategy
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How Anthropic is using Claude to automate its own growth with Amol Avasare (Head of Growth)
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Salesforce Leverages Slackbot AI to Address SaaSpocalypse Challenge
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Salesforce is looking to Slackbot to help it solve the SaaSpocalypse puzzle https://t.co/XZRx45t2A1 pic.twitter.com/PaR2hQHGcY
— Craig Brown, PhD (@craigbrownphd) 7 avril 2026Salesforce is looking to Slackbot to help it solve the SaaSpocalypse puzzle go.theregister.com/feed/www.…