Adrian Macneil

Happy Friday! 🖼️ A picture is worth a thousand words! ☺️ This is the latest data from our Central Plant AI optimization solution running at California State University-Dominguez Hills Kenny Seeton. Pretty exciting that we've confirmed that it takes our AI/ML/RL platform a total of TEN (10) days, from “scratch, to completely RE-discover the data points needed, classify them, "map" them, build its OWN model, train itself, and INCREASE the Central Plant efficiency by FORTY-EIGHT PERECNT! From 0.81 kW/ton down to 0.39 kW/ton! 🚷 NO human intervention! Below is a snapshot of the CP. Restart 5/5/25. We deleted ALL of the learnings from the last 2 1/2 years. About 2GB. 1 week baseline. 10 days RL. Notable observations: 1. Even though the Plant Efficiency increased by 48%, the Chiller is STILL "holding" the CHW-S temp set-point of 47 DEG F (46.5 DEG F Actual). 2. The one-thousand TON (rated) JCI/York YMC2 Chiller is "putting out" 668 TONS of cooling (67% of its RATED capacity), YET the Chiller itself is only "loaded up" 39.4%! This means the Chillers CAPACITY (output) INCREASED significantly. 3. The original BMS algorithm was programmed to set the CW Temp to Outside Air Wet-Bulb (OA-WB) PLUS five (5) degrees. Which is standard practice, and has been, for decades. However, our AI trained itself and controlled the CW Temp everywhere from +4 degrees above OA-WB to TWENTY-FOUR (+24) degrees above OA-WB. And everywhere in between. Every five (5) minutes. 288 cycles (solutions) per day. The new set-point is computed and sent from the cloud. Takes 4-5 secs. Let's talk about "guardrails". 😉 YES! 😁 They're there. Low: 60.0 DEG F to a High: 90.0 DEG F. In fact, these same "guardrails" are typically already IN PLACE, with your existing BMS logic. AND there's mechanical safeties, ON the Chiller(s) and equipment. We take the safety and security of your organization VERY seriously. But here's the thing about facil.ai: How can you TRUST our AI? Because you can TRUST the people who built it! And install it. Our partners are the same BMS service providers, consultants, mechanical contractors, ESCOs, Property Managers, Peers and friends: Who are serving you right now! Ready to learn more? Contact us: https://lnkd.in/gVutYEiX Want to explore being a partner? https://lnkd.in/gigtx2vx Want to invest in the future of AI Digital Technology? We're putting together a crowdfunding growth round with StartEngine https://lnkd.in/gwcSRR3b Please sign up on the list if interested: https://lnkd.in/gJ_2yCr3 Let's start a conversation! I'm always ready to "talk shop" 🤗 Shoot me a note on LinkedIn or e-mail: keith@facil-ai.com 🦄 We’re thrilled to be in conversations with several large infrastructure companies as partners or acquirers. Inquiries to our interim CTO John Majeski BUILD🛠️GROW📈FUND💰EXIT🦄 ❤️ Our customers love us! 🚀 facil.ai is proud to be a Portola Valley Partners portfolio company. #innovation #technology #management #creativity #future

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Too many robotics & AI programs stall at the pilot stage — never reaching the potential to actually transforms operations. After years helping end users and robotics and AI companies navigate that exact challenge, I’m excited to share a new chapter: the launch of Nascent Scale 🤖 Together with Tim Dykstra we founded Nascent Scale to help technology providers, industrial leaders, and investors bridge the gap between innovation and enterprise scale. We’ve seen firsthand how much time and capital can be lost chasing the wrong applications, misaligned changed management, or hype-driven deployments. Nascent Scale exists to break this cycle — combining deep domain expertise, real experience, and ecosystem insights to help turn breakthrough robotics and AI into operational reality. Our mission is simple: ➡️ Help innovators scale beyond pilots and become relied-on technology. ➡️ Help industries unlock measurable ROI & integrate technology. ➡️ Help investors find, back, and grow technologies that truly scale. We’re just getting started, and I couldn’t be more energized by the opportunity ahead. 🚀 #Robotics #ArtificialIntelligence #EmbodiedAI #IndustrialAutomation #GoToMarket #VentureCapital #TechnologyCommercialization #DigitalTransformation #AIinIndustry #StartupEcosystem #InnovationStrategy #FutureOfWork

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In robotics, the real flex isn’t a backflip. It’s a purchase order! While much of the humanoid robotics category is still polishing demo reels, our portfolio company, Agility Robotics, just landed a production deployment with Toyota Motor Corporation — seven Digit robots are now operating at a Canadian RAV4 factory. This isn't a proof of concept. This is production. Robots-as-a-service. Real workflows. Real output. Agility is the only humanoid robotics company operating at this level — production-grade deployments with Amazon, GXO, Schaeffler, and now Toyota. Everyone else is still in pilot mode. Agility is in production. At MFV Partners, we've always believed that getting to 90% in robotics is the easy part. It's the last 10% — the outlier scenarios, the edge cases that make robots fail, the messy integration, the maintenance cycles — that separates cool videos from real deployments. Our portfolio reflects this philosophy. Chef Robotics is doing it in commercial kitchens. Ati Motors is doing it in factory logistics. Agility is doing it with humanoids. The gap between demo day and deployment day is where most robotics companies go to die. Agility keeps widening that gap against the competition. Congratulations to the Agility and Toyota teams. This is just the beginning. 🤖 https://lnkd.in/gUcWYJUw Peggy Johnson Jonathan Hurst Pras Velagapudi Daniel Diez Matt Ocko Bruce Leak

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Fast, Scalable, Real: OPC UA Machine Connectivity—Streaming Live to MQTT & InfluxDB Everyone talks about real-time shopfloor connectivity and “Industry 4.0”—but how many can actually show it in practice, at scale? We’ve pushed our OPC UA setups to the edge—and discovered something essential: ➡️ It’s almost never OPC UA (the protocol) that’s your bottleneck, but the performance of your OPC UA servers and—more often—the connected controllers and underlying protocols. Our results: ⭐Up to 28,500 OPC data points per second (28.5 kHz) from a single OPC UA server, sent live to MQTT and InfluxDB. ⭐In another scenario, monitoring 640,000 OPC tags on a single server, we consistently achieved over 21,000 data points per second (>20 kHz)—real, not just theory. The real-world insight: It’s not about protocol limits, but about: ➡️Batch reads for ultra-fast polling (using cron, timer, or data change triggers) ➡️The true limiters: OPC UA server performance, the connected controllers (PLCs, DCS), and the “old” protocols (S7, Modbus, Ethernet/IP…) beneath the surface Every week I see teams obsess over buzzwords and dashboards, yet basic machine connectivity is still a challenge. If you want actionable production data at scale, focus on: ▪️A clear trigger strategy (data change, timer, batch polling) ▪️OPC UA connections built for real load, not just “demo mode” ▪️Tight integration into your data pipeline (MQTT, DB, cloud) ▪️And most importantly: Measure the performance of your devices, controllers, and protocols—not just the protocol overhead! ▪️Also: Optimize how your controllers expose data—PLC tag design and protocol handling all play a crucial role. (More on that next week…) Don’t just talk about digital transformation—stress-test it. 👉 Ready to break the “demo barrier”? Connect your machines, push your OPC UA pipeline to the limit—and see where your actual bottlenecks are. The future belongs to those who turn machine data into business value, not just pretty slides. What about you? Where do you hit the wall—protocol, server, controllers, or the “old” field protocols? Let’s talk real-world bottlenecks in machine data acquisition. Next week: ⏭️I’ll share practical tips for spotting and overcoming device and protocol limitations—based on real projects and lessons learned. #OPCUA #IndustrialAutomation #MachineConnectivity #MQTT #InfluxDB

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We just wrapped up a huge week at Figure - here’s what we announced: 1/ Announced >$1B in Series C. This gives us the strongest balance sheet in humanoid robotics - critical to scaling Helix (our AI) and BotQ (robot manufacturing) 2/ Launched a partnership with Brookfield, who manages $1T in assets globally. Together we’re planning to scale AI infrastructure for Helix, already collecting real-world data for Helix pretraining, and working commercially to deploy robots 3/ Announced Project Go-Big - our push to build the world’s largest humanoid pretraining dataset. We are scaling out human video collection and our F.02 humanoid can now learn directly from human video. This project is accelerated by our partnership with Brookfield, who owns over 100,000 residential units As a founder, timing is everything. Too early or too late is fatal Right now, we’re in the sweet spot for humanoids: advanced hardware is maturing that can walk and do human-like tasks, production manufacturing is spinning up, and most importantly - neural networks are delivering. I believe we’re at the starting line of scaling synthetic humans to billions of units

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Humanoid robotics in a nutshell 🤖✨ Just listened to this podcast with the CEO of Agility Robotics (Peggy Johnson – super insightful!). It breaks down really well the burning (and most misunderstood) topics in robotics, like: will they actually replace human workers? Why now? The key changes happening 🔥 🤖 Several breakthrough technologies are finally in place – especially AI teaching skills to robots 💪 Actuations in arms & legs – getting lighter, stronger, and way smarter 🔋 Batteries are becoming more dense and useful (longer runtime!) 📉 Huge demand for human labor – especially in tedious, repetitive, or risky jobs They're designed to be human-centric and help fill labor shortages, not take over. The next-gen ones will lift up to 50kg (sounds small at first, but imagine doing that daily or hourly – it's basically a full gym workout every shift! 💪😅) Safety? Trust is everything. People need to feel safe and confident around these humanoids. What it feels like to work with them? Will they take my job? 🙅‍♂️ Nope – they're here to help humans with the boring/dangerous stuff. Humans can offload the heavy lifting and free up time for more interesting, valuable work. Plus, new jobs are popping up: robot managers – basically digital-focused roles supervising the fleet! 📈 How HR sees it ✅ Keep injury numbers way down ✅ Help humans move up to better positions instead of just lifting boxes all day Most ready use cases right now? 📦 Logistics – moving products around warehouses 💊 Pharmaceuticals – handling stuff in facilities 🚗 Automotive – carrying parts 🛒 Retail – restocking inventory, unpacking, and moving to shelves Near future? Eldercare and healthcare – assisting with everyday tasks 🏥❤️ Fun fact: The robots can walk themselves back to the charging station and juice up autonomously ⚡😎 And when talking to CEOs in this space? It's all about product-market fit – finding what actually brings revenue today. But more importantly: culture – growth mindset everywhere, staying open to new ideas! 🌱 https://lnkd.in/ee6UEJut

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RobCo Raises $100 Mn to Scale Its Autonomous Industrial Robotics Platform Why this matters: The investment co-led by Lightspeed Venture Partners and Lingotto Innovation will accelerate RobCo’s enterprise deployments, deepen its U.S. market presence and support advanced autonomy for tasks such as machine tending, palletizing and welding, reducing manual programming needs and enhancing productivity. Our take: This funding underscores an opportunity for manufacturers to adopt adaptable, learning-enabled robotics that can lower operational friction and support labour-constrained environments. What do you think? With autonomous industrial robots gaining traction, could Physical AI become standard in future factory automation? Roman Hölzl Alexander Schmitt Morgan Samet Read More:- https://lnkd.in/d2t4xqR9 #Robco #AI #Automation #PhysicalAI #SeriesC #news #AITP #Manufacturing #TechFunding #Innovation #robotics

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🎙️ “AI isn’t a product — it’s a velocity enabler.” — Matt Siemens, NUSO At the #Crexendo User Group Meeting, I caught up with Matt Siemens of NUSO, where the company is taking a bold, practical approach to AI and expanding across Europe. 🌍 In his main-stage talk, Matt explained how NUSO has built a digital twin of its own network — a live, structured data model that keeps AI grounded in real-world conditions. The result: 🤖 Fewer hallucinations 🧠 Smarter transcription and sentiment analysis 🔁 Better context for every customer interaction Matt also highlighted how #vCons** act as “micro-mirrors”* — threading together the moments that define customer experience and helping AI focus on outcomes, not just outputs. Beyond AI, NUSO announced a global technology partnership with Crexendo** and continued European expansion — now with operator authority in 14 countries, and new momentum in 🇫🇷 France, 🇩🇪 Germany, 🇪🇸 Spain, and 🇮🇹 Italy. If you’re at **Crexendo UGM**, stop by the **NUSO Lounge on the 3rd floor** for a quiet conversation and a closer look at their next-generation UCaaS platform. Or learn more at 👉 [nuso.cloud](https://nuso.cloud) #NUSO #AI #DigitalTwin #vCon #UCaaS #TelecomInnovation #CrexendoUGM #TechnologyResellerNews #CloudCommunications #AIinTelecom #CrexendoUGM 2025 Snom Technology GmbH\ #SnomAtTheShow Doug Green TR Publications #Podcast Julie Smith Chad Collins Antoine Karachekhlian Vincent Gianfrancesco Outsourcing Services International | OSI TELCLOUD NUSO Yealink Nomadix, an ASSA ABLOY company Grandstream Networks Ozonetel | oneCXi 888VoIP Poly HP NTSDirect VOLA NETWORKS FaxSIPit Services Inc. CCT Solutions Adaptiv Networks Creo Solutions Ecosmob Technologies Sinch TransNexus Amanda Howard Jason Byrne

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All of a sudden, hardware startups have become hot with VC funds, especially where they intersect with AI, compute infrastructure, semiconductors, robotics, and advanced manufacturing. Software developer teams seem poised to be gradually replaced by AI agentic teams as the industry shifts toward open source -> with AI agents building apps while we sleep. Just a gentle example: Kelly Claude is now building 12+ products per day. Autonomously. Welcome to the future of software building. And by the way, you can find Kelly Claude on Moltbook. For those still living in the past, Moltbook is like a “Facebook” for AI agents.

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