Remotely.Local

Remotely.Local
  • 5.0 (1)
  • Technology

Remotely.Local — the podcast where the physical world meets the connected world. Every machine, sensor, robot, vehicle, and smart device is becoming part of a much larger, intelligent network. Remotely.Local explores the technologies making that future possible: Physical AI, edge computing, industrial IoT, networking, secure connectivity, and remote device management. Each episode features conversations with the founders, engineers, researchers, operators, and industry leaders building the infrastructure behind connected products and autonomous systems. We dig into the architectures, protocols, platforms, and real-world lessons that power everything from factory floors and critical infrastructure to consumer devices and AI at the edge. Topics include: Physical AI and embodied intelligence Industrial IoT (IIoT) and IoT Edge AI and edge computing Secure networking and connectivity Remote access and remote device management Robotics and autonomous systems Network infrastructure and distributed computing Cybersecurity for connected systems Remote support, operations, and observability Because the future isn’t just in the cloud — it’s Remotely.Local.

Episodes

  1. Sep 29

    Fighting AI Scams with Patrick Coughlin of Savi Security

    The scariest scam calls don’t sound like strangers anymore. They sound like family. Ryo Koyama and Mike Johnson talk to Patrick Coughlin, CEO of Savi Security and author of Dark Side of the Boom, about how AI has turned scamming into the fastest growing crime in the country, from an AI-cloned kidnapping call aimed at his own mother to a voice-cloned scam that fooled one of Remote.it’s own employees. Patrick talks about why scams go underreported, why every family should have a safe word, and why he thinks the real danger isn’t a rogue AI model, but the quiet flood of AI-powered scams already hitting everyday people’s phones. Chapters 0:04 — Intro 0:21 — Who is Patrick Coughlin, and how did Savi Security start? 1:07 — The AI-powered kidnapping scam that targeted Patrick’s mother 2:43 — The AI voice clone scam that hit Remote.it’s team 5:48 — What is Dark Side of the Boom, and why did Patrick write it? 8:09 — The four types of imposter scams driving digital fraud 11:47 — Why so few victims ever report being scammed 14:08 — Rogue AI models, autonomous cyberattacks, and what could go catastrophically wrong 18:38 — Family safe words and practical ways to protect your family 22:25 — Scamwise, a free tool to check if something is a scam 23:13 — Who pays when AI fraud reaches a breaking point? 25:56 — Is regulation the answer, or is it already too late? 31:55 — AI hot take Links Watch the video version Savi Security Scamwise — free scam checker Dark Side of the Boom The voice clone scam that hit our team — full story Remotely Local Remote.it Make sure you check out remotelylocal.com Learn more about remote.it

    Fighting AI Scams with Patrick Coughlin of Savi Security

  2. Sep 17

    Bringing AI to Burning Man Art with Kevin Clark of Reared In Steel

    Some of the most striking art on the playa is wired as much as it’s welded. On this episode of Remotely Local, Ryo Koyama and Mike Johnson sit down with Kevin Clark, founder of Reared In Steel, whose fire sculptures have been lighting up Burning Man for more than a decade. His pieces range from the 26-snake Medusa to the 80-foot Flower Tower and the 110-effect, MIDI-controlled Fire Cathedral. Kevin tells how he got hooked on Burning Man in the early days of the temple movement, helping Jack Haye and David Best. He explains why scale matters when you’re building in the middle of the desert. Mike, who built the control systems behind the pieces, walks through how the tech grew from push buttons to Raspberry Pis, relay banks, MIDI, and remote access from the playa. That includes the night a stranger plugged in a homemade keytar and played the Fire Cathedral. They also get into Guma, the climbable Burning Man 2025 piece Kevin built with his daughter, including the story behind the viral bike crash. Kevin talks about teaching teenagers to weld, why he sees AI as a tool for getting ideas out faster rather than as the finished art, and why he’d happily put a few robot welders on the crew. Chapters 00:00 Intro 00:33 Mike and Kevin’s friendship and the naming of Reared In Steel 02:08 What Reared In Steel does and the early Burning Man builds 02:51 Burning Man temples and getting involved early on 05:23 How big these sculptures are and why scale matters 07:04 How the technology behind the art has evolved 08:23 Building the Fire Cathedral and its most unforgettable moments 12:51 AI as a tool for artists 17:58 Guma and how it became one of Burning Man’s most talked-about builds 23:16 What’s next for Reared In Steel’s technology 25:48 Why physical AI still needs hands-on skills like welding 31:24 What “physical AI” really means and the social media challenge 34:45 The AI hot take Links Watch the video version of this podcast (includes the crash clip): https://www.youtube.com/watch?v=QsIO-rHsD8o Reared In Steel on Facebook: https://www.facebook.com/rearedinsteel/ Guma dino crash video: https://www.youtube.com/watch?v=5HHFIPKMISc Remotely Local: https://remotelylocal.com Make sure you check out remotelylocal.com Learn more about remote.it

    Bringing AI to Burning Man Art with Kevin Clark of Reared In Steel

  3. Aug 4

    Bringing AI to Energy Management with Sam Cox of Mountain Vector Energy

    Somebody has to build the road before you can drive on it. Sam Cox, CTO of Mountain Vector, joins Ryo Koyama to talk energy data, legacy utilities, and the unglamorous infrastructure behind Physical AI — from dot-matrix-era utility bills to running hundreds of remote devices with a 12-person team. Bringing AI to an industry stuck in the past Mountain Vector does energy management: utility bill analysis, solar and battery evaluations, and analytics that show customers where their consumption and spend actually go. The hard part isn’t the AI. It’s the data. Utilities are among the most conservative industries in existence, and many municipalities still issue bills in formats that look like dot matrix printouts — poor-quality account numbers, inconsistent layouts, barely legible to a human. Before any insight is possible, someone has to make that readable to a machine. Operating at national scale Mountain Vector serves customers coast to coast: School districts Industrial facilities Utility providers Public sector organizations One industrial customer tracks locational marginal pricing on 15-minute and five-minute intervals, deciding in near-real-time whether to curtail operations when costs spike. Mountain Vector is building predictive capability on top of that, so customers can plan ahead instead of reacting. Physical AI needs infrastructure first The models get the attention. The roads don’t. Factories, sensors, meters, and edge devices have to be connected and reliably reporting before AI can do anything useful with them. With hundreds of devices deployed nationwide and a small team in New Mexico, Mountain Vector can’t send a technician every time something breaks. Remote access is what makes the model work: Configure deployed devices Troubleshoot and diagnose failures Push software updates Collect operational data into central analytics Sam had scoped building this himself — reverse SSH tunnels, custom infrastructure — before finding Remote.It and concluding it was cheaper and faster not to. He also recounts a support case where the root cause turned out to be an MTU issue on his own end, and Remote.It tracked it down anyway. Declarative, not imperative Sam’s sharpest observation: software has always required you to specify how. AI shifts that to what. Describe the outcome — pull these fields from ten thousand inconsistent utility bills — and let the system work out the method. AI won’t take your job, it’ll fill your queue Sam’s experience runs against the prevailing anxiety. AI hasn’t reduced his workload; it’s multiplied his throughput. Where he shipped one feature a week, he now ships six. The queue empties faster and refills faster. His analogy: Excel didn’t eliminate accountants. It let them serve far more clients and do far more sophisticated work. The catch Language models are very good at producing exactly what you asked for — which is not always what you needed. In production energy systems, that gap matters. Human expertise becomes more valuable as the tools improve, because someone has to judge whether the output actually survives contact with reality. Video version: https://www.youtube.com/watch?v=1zMs9TFK5v4 Make sure you check out remotelylocal.com Learn more about remote.it

  • 3 Episodes

About

Remotely.Local — the podcast where the physical world meets the connected world. Every machine, sensor, robot, vehicle, and smart device is becoming part of a much larger, intelligent network. Remotely.Local explores the technologies making that future possible: Physical AI, edge computing, industrial IoT, networking, secure connectivity, and remote device management. Each episode features conversations with the founders, engineers, researchers, operators, and industry leaders building the infrastructure behind connected products and autonomous systems. We dig into the architectures, protocols, platforms, and real-world lessons that power everything from factory floors and critical infrastructure to consumer devices and AI at the edge. Topics include: Physical AI and embodied intelligence Industrial IoT (IIoT) and IoT Edge AI and edge computing Secure networking and connectivity Remote access and remote device management Robotics and autonomous systems Network infrastructure and distributed computing Cybersecurity for connected systems Remote support, operations, and observability Because the future isn’t just in the cloud — it’s Remotely.Local.

Information

  • Creator
    Remotely.Local
  • Years Active
    2026
  • Episodes
    3
  • Rating
    Clean
  • Show Website
    Remotely.Local