Machine Minds

Greg Toroosian

Machine Minds - the minds behind the machines! This is the show where we dive deep into the intricate worlds of robotics, AI, and Hard Tech. In each episode, we bring you intimate conversations with the founders, investors, and trailblazers who are at the heart of these tech revolutions. We dig into their journeys, the challenges they've overcome, and the breakthroughs that are shaping our future. Join us as we explore how these machine minds are transforming the way we live, work, and understand our world. 

  1. 5 days ago

    Selling Airspace Awareness Before the Market Knows It Needs It with Melissa Swisher

    Having the best technology does not guarantee you win. Customers do not buy engineering. They buy outcomes. Melissa Swisher, Chief Revenue Officer at SkySafe, joins Greg to explore what it takes to turn sophisticated technology into a repeatable business, and why that challenge is becoming increasingly important as drones become a routine part of the world around us. Melissa brings decades of experience building and scaling go-to-market organizations across enterprise software, healthcare technology, AI, and now airspace intelligence. Her career has included high-growth companies, IPOs, founding and successfully exiting Socrates AI, and learning firsthand how culture, focus, and customer understanding can determine whether a technically impressive company actually succeeds. At SkySafe, Melissa has helped move the business from experimentation toward a focused, scalable go-to-market model. Since joining, the company has quadrupled revenue and grown from a handful of customers to roughly 50 by narrowing its focus, creating clearer buying motions, and building around federal, public safety, law enforcement, and critical infrastructure customers. The conversation also explores the rapidly changing world above us. As drones become cheaper, more capable, and more common, organizations increasingly need visibility beyond the traditional fence line. SkySafe is building an intelligence network designed not simply to detect a drone, but to understand where it came from, whether it has appeared before, how it behaves, and what patterns emerge across locations over time. Greg and Melissa get into: Why having the best technology is not enough to win, and why customers ultimately buy outcomes rather than engineeringMelissa’s journey from enterprise sales and leadership to founding Socrates AI and eventually joining SkySafeHow mentors shaped her career and why she now pushes people into bigger opportunities before they necessarily feel readyWhat dramatically different company cultures taught her about accountability, collaboration, customer focus, and why culture directly drives performanceWhy SkySafe needed to move from experimentation to scale by creating greater focus, clearer qualification, and repeatable buying motionsThe power of saying no, and why startups can die from having too many good ideasHow SkySafe detects drones and turns individual detections into a broader airspace intelligence networkWhy the company focuses on persistent detection and intelligence rather than treating every unidentified drone as a threatHow networked RF sensing can reveal patterns, history, and behavior that a standalone sensor cannotWhy drone forensics can turn airspace data from a monitoring tool into an investigative asset for law enforcementThe emerging opportunity around critical infrastructure, including energy, utilities, oil and gas, and data centersHow disciplined execution helped SkySafe quadruple revenue, and why growth often comes from doing the boring, repeatable things consistently wellWhat Melissa looks for when hiring go-to-market talent, including curiosity, hunger, adaptability, and comfort with ambiguityHer advice to technical founders whose go-to-market strategy is struggling: stop selling to everybody, identify who has an urgent problem they will pay to solve now, and build repeatability before expandingWhy a use case is not the same thing as a market, and why technical founders should bring commercial leadership into the business earlierWhat nationwide airspace awareness could eventually look like as cities, critical infrastructure, public safety, and federal organizations become part of a broader intelligence networkWhy Melissa believes meaningful career decisions often feel uncomfortable before they feel obviousFor robotics, hard tech, and AI founders trying to turn technical capability into a scalable business, this conversation is a practical look at focus, category creation, go-to-market discipline, and the importance of knowing which opportunities to pursue and which ones to leave behind. Learn more about SkySafe: https://www.skysafe.io/https://www.linkedin.com/company/skysafe/Connect with Melissa on LinkedIn: https://www.linkedin.com/in/melissa-swisher-00480a/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

    Selling Airspace Awareness Before the Market Knows It Needs It with Melissa Swisher

  2. 30 Sept

    The Lawyer Who Writes Robotics' Rulebook with Michael Bearman

    There’s a huge difference between making a robot work in a lab and making it reliable enough to survive the chaos of a real warehouse. For Michael Bearman, Chief Legal and Safety Officer at Vecna Robotics, closing that gap has been a 23-year journey spanning legal, operations, customer deployments, fundraising, safety, and industry standards. Michael joins Greg to share how he went from outside counsel to becoming one of Vecna’s longest-serving leaders, taking on everything from contracts and customer implementations to financial modeling and even an all-night soldering session before a robot demonstration at Congress. That willingness to jump into unfamiliar problems gave him a front-row seat as Vecna evolved from experimental robotics projects into industrial automation deployed across warehouses and manufacturing facilities. They explore why impressive robotics demos are very different from commercially viable products, how an early rescue robot helped Vecna learn that lesson firsthand, and why a major FedEx deployment pushed the company toward industrial mobile robots. Michael also breaks down Vecna’s approach to automated forklifts, tuggers, and CaseFlow, including how one customer doubled throughput with half the staff by rethinking the traditional case-picking workflow. In this conversation, Greg and Michael explore: Michael’s unconventional journey from outside legal counsel to Chief Legal and Safety Officer, and the many operational, financial, customer, and leadership roles he took on along the wayWhy there is such a large gap between a successful robotics demonstration and a system that customers can rely on in real-world industrial environmentsHow Vecna’s early Bear rescue robot helped build the technology, team, and relationships that eventually supported its pivot into industrial roboticsThe FedEx deployment that put more robots into a single site than Vecna’s entire existing fleet and helped reshape the company’s directionHow automated tuggers, forklifts, and CaseFlow tackle different material-handling workflows across manufacturing, automotive, and third-party logisticsWhy close collaboration with an early 3PL customer helped Vecna build CaseFlow around the realities of warehouse case picking, ultimately doubling throughput with half the staff at that customerHow flexible Robots as a Service models allow 3PL customers to scale fleets up and down around seasonal peaks instead of paying for idle robots year-roundWhat Michael looks for during on-site safety risk assessments, from pedestrian traffic and crosswalks to routes that may look good in CAD but fail in the real warehouseWhy interoperability matters as warehouses deploy robots from multiple vendors, and how Michael helped shape the MassRobotics AMR interoperability standard that has now progressed into an international ISO standardThe challenges of writing safety standards for everything from multi-ton industrial robots to dynamically balancing humanoid and legged systemsWhy spending time inside real customer facilities has made Michael a better lawyer, safety leader, and contributor to robotics standardsWhat Vecna looks for when hiring in a startup environment, including intelligence, flexibility, curiosity, and a willingness to figure things out rather than staying inside a narrowly defined roleWhy customer trust depends on transparency when something goes wrong, and why hiding information is one of the fastest ways for a robotics company to lose that trustMichael’s view that warehouses will continue to need people for edge cases, even as automation expands, with human workers increasingly supporting fleets rather than performing every task manuallyWhy robotics founders cannot afford to cut corners on safety, especially when a single serious incident can have enormous consequences for a young companyFor robotics founders, operators, engineers, and anyone trying to move automation from a controlled demo into messy real-world environments, this conversation offers a practical look at what reliability, safety, interoperability, and customer trust actually require. Learn more about Vecna Robotics: https://www.vecnarobotics.com/ Connect with Vecna Robotics: https://www.linkedin.com/company/vecna-robotics/posts/ Connect with Michael Bearman: https://www.linkedin.com/in/bearman/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

    The Lawyer Who Writes Robotics' Rulebook with Michael Bearman

  3. 23 Sept

    The Visual Cortex of Physical AI with Chris Matthieu

    What happens when AI agents stop living entirely on screens and start controlling cameras, wheels, motors, and eventually full robotic bodies? Chris Matthieu, VP of Developer Ecosystem at RealSense, joins Greg to explore the rapidly converging worlds of AI agents, computer vision, robotics, and physical intelligence. A lifelong hacker who started programming on a Commodore VIC-20 as a kid, Chris has spent more than four decades building technology, including five startup exits, before joining Intel as an entrepreneur in residence and eventually helping grow the RealSense developer ecosystem. Chris shares how his fascination with connected machines evolved from IoT platforms and decentralized computing into his latest project, AgenticROS, an experimental system that gives AI agents direct access to ROS and allows them to perceive and control physical robots. His robot Bob can already use camera data to identify where Chris is, calculate his position, control its wheels, and follow him through a room without Chris explicitly programming every behavior. Greg and Chris also dig into RealSense’s evolution from an Intel incubator project into an independent company, why depth perception is becoming foundational infrastructure for physical AI, and how open source software, cheaper hardware, and AI coding tools are dramatically lowering the barrier to building real robotic systems. Highlights: Chris’s journey from hacking on Commodore computers as a child to building and exiting five technology startups before moving into Intel and RealSense. - Why builders who avoid ROS can end up recreating infrastructure that already exists, and why the broader ROS ecosystem can dramatically accelerate robotics development.How AgenticROS connects tools such as Claude, Codex, Gemini, and other AI agents directly to ROS, giving them access to cameras, perception data, and robot controls.Why Chris believes increasingly capable AI models may eventually control robotic bodies without developers having to explicitly program every movement or create a predefined skill for every task.The startup lesson Chris learned at Intel: stop building technology in search of a market and instead start with painful customer problems people are willing to pay to solve.Why timing played such an important role in spinning RealSense out of Intel, especially as generative AI, physical AI, and robotics began accelerating simultaneously.How RealSense depth cameras give robots an RGBD view of the world by calculating depth at every pixel, while increasingly moving AI and perception processing directly onto the camera itself.How open source SDKs and AI code generation are shrinking prototype timelines from weeks or months to hours, allowing developers to validate ideas far more quickly.Why side projects, GitHub activity, curiosity, and building in public can be some of the strongest signals for engineers looking to break into robotics and physical AI.How one experimental LinkedIn post about Chris’s robot generated roughly 180,000 impressions and led to NVIDIA webinars, conference talks, and unexpected opportunities.Why individual developers can sometimes validate ideas faster than large companies, especially when AI coding tools, inexpensive cameras, Raspberry Pis, and NVIDIA Jetsons make functional robotics prototypes accessible for hundreds rather than tens of thousands of dollars.Chris’s philosophy of failing fast, testing the market early, and recognizing when either the technology or the customer demand is not ready yet.Why he believes the enormous funding rounds flowing into physical AI may reflect the scale of the potential market, even while competing approaches such as VLAs, world models, and skill-based systems are still evolving.His advice for anyone entering robotics: start with an inexpensive desktop robot, experiment with it, and remember that complex robots are ultimately systems of smaller components working together.Where Chris hopes physical AI ultimately leads: robots that understand the people around them, safely operate in human environments, and perhaps finally bring him coffee in the morning and a beer in the evening.For developers, founders, students, and anyone curious about where AI goes after the chatbot, this conversation offers a hands-on look at how rapidly robotics is becoming easier to prototype, program, and experiment with, and why the next wave of AI may increasingly have cameras, wheels, arms, and a physical presence. Learn more about RealSense: https://www.realsenseai.com/ Learn more about AgenticROS: https://agenticros.com/ Connect with Chris Matthieu on LinkedIn: https://www.linkedin.com/in/chrismatthieu/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

    The Visual Cortex of Physical AI with Chris Matthieu

  4. 16 Sept

    The Factory Is the Innovation with Eric Hostetler

    What if the biggest bottleneck in defense technology is not designing better systems, but actually figuring out how to manufacture them at the speed, cost, quality, and scale modern warfare demands? Eric Hostetler, CEO and co-founder of Volund Manufacturing, joins Greg to unpack why America’s defense industrial base needs more than individual manufacturing breakthroughs. Drawing on a career that spans Vans, Oakley, Fox Racing, Apple, Anduril, and high-end defense manufacturing, Eric brings a consumer goods mindset to one of the country’s most urgent industrial challenges: producing reliable defense hardware at scale. At Volund, that philosophy is being applied to air-breathing propulsion systems for low-cost, attritable drones and other unmanned systems. Rather than treating the engine as the only innovation, Eric and his team are building a vertically integrated factory where manufacturing, quality control, software, automation, and production planning are designed as one system from the beginning. In this conversation, Greg and Eric explore: Eric’s unconventional path from BMX bikes and learning to weld to nearly 100 trips to China while building consumer products for companies including Vans, Oakley, Fox Racing, and AppleHow working on rifles for U.S. special operations helped push Eric from consumer products into defense, eventually leading him to join Anduril as one of its earliest employeesWhy consumer goods taught him that cost, quality, production volume, and speed cannot be treated as problems to solve after a product has already been designedThe problem with designing defense hardware for the demo first and planning to “optimize for manufacturing” laterWhy Eric believes manufacturers need to optimize the whole cost and complexity equation instead of focusing too heavily on individual technologies like AI, robotics, or automationHow Volund is building vertically integrated propulsion manufacturing for low-cost, medium-to-long-range unmanned systemsWhy the factory itself is part of the product, with CNC machining, sheet metal processing, welding, heat treatment, balancing, quality systems, and other capabilities brought under one roofHow self-contained manufacturing cells can handle production tracking, metrology, quality control, and scrap decisions without creating downstream bottlenecksWhy factory software, IoT, MES integration, and automated quality systems may deliver greater gains than simply replacing human labor with robotsThe propulsion supply chain challenges hiding behind bearings, investment castings, rare earth materials, chemical precursors, and other critical componentsWhy Eric believes parts of the existing defense industrial base may need to be replaced rather than simply funded to produce moreHow aging machine shops, fragmented suppliers, cybersecurity requirements, and limited scaling expertise make rapid expansion especially difficultWhy vertically integrated, product-focused factories could become a stronger model for rebuilding domestic manufacturing capacityWhat Volund’s $12 million seed round unlocks as the company works toward low-rate initial production of its first two engine sizesWhy COVID exposed the fragility of global supply chains and helped reignite investor interest in factories and domestic industrial capacityVolund ’s approach to hiring experienced operators and engineers who understand legacy systems but are motivated to build faster, less bureaucratic alternativesThe Apple principle of “brief by exception,” and what defense companies can learn from eliminating meetings about things that are already going according to planWhy investment casting deserves far more attention as a critical, skilled-labor-intensive foundation for propulsion and turbomachineryFor anyone building in defense tech, hard tech, robotics, or advanced manufacturing, this conversation offers a systems-level look at what it will actually take to rebuild American production capacity. The future of defense manufacturing may depend less on finding a single breakthrough technology and more on redesigning the entire factory around speed, scale, reliability, and manufacturability from day one. Learn more about Volund Manufacturing: https://www.volundmfg.com/ Connect with Eric Hostetler on LinkedIn: https://www.linkedin.com/in/eric-hostetler-4421964/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

    The Factory Is the Innovation with Eric Hostetler

  5. 9 Sept

    The Temp Agency for Robots with Matt Bush

    For decades, manufacturers have struggled with the same fundamental problem: there simply are not enough people to fill the jobs that need to be done. Matt Bush believes solving that problem requires changing the way manufacturers think about robotics entirely. Matt joins Greg to share how nearly two decades running manufacturing plants shaped his approach to automation, from deploying some of the earliest collaborative robots on production lines to building robotic systems designed to feel less like engineering projects and more like everyday tools. His goal is simple: make automation easy enough that the people already working on the shop floor can deploy and use it themselves. That philosophy led to Beacon, a unified software platform that gives manufacturers the same interface across robotic welding, plasma cutting, painting, and other applications, regardless of the underlying robot hardware. By combining standardized systems, cloud connectivity, fleet-wide software updates, and highly responsive support, Matt and his team are working to remove the friction that has historically kept robotics out of smaller and more flexible manufacturing environments. Greg and Matt explore: How nearly two decades running manufacturing plants taught Matt the importance of producing closer to the point of consumption, and why global supply chain fragility has reinforced that lessonThe story of "Waldo," an early collaborative robot that moved between jobs throughout a Tennessee factory and showed employees how flexible automation could becomeWhy employee attitudes toward robots changed once workers realized automation was taking over repetitive, uncomfortable, and undesirable tasks rather than eliminating their jobsHow labor shortages pushed Matt toward robotics as a service, including no upfront capital, limited commitment, and a model designed to reduce the financial and operational risk of adopting automationWhy decades of efforts to solve manufacturing labor shortages through education and recruiting have not been enough, and how demographic changes are making automation increasingly unavoidableMatt's belief that robots should be viewed as tools, no differently than drills, grinders, computers, or other technologies that allow people to work more effectivelyHow the Beacon platform creates one consistent interface across welding, cutting, painting, and multiple robot brands while allowing manufacturers to manage entire fleets from a single systemWhat it takes to make industrial robotics feel "iPhone-esque," from shipping systems largely assembled to continuously removing friction from setup, programming, and operationHow customer demand has shaped the company's expansion from welding into plasma cutting, liquid painting, and powder coatingThe engineering challenges of deploying robots inside potentially explosive paint environments, including intrinsically safe electronics, air-purged robot arms, and specialized operator controlsWhy standardization allows robotic systems to ship in days rather than the weeks or months traditionally associated with custom automation projectsHow cloud-connected robots enable fleet-wide software updates, production analytics, remote support, and fixes that can be deployed across every connected system at onceHow an AI-powered support system now resolves roughly half of customer inquiries before a human needs to step in, while keeping engineers directly involved when more complex support is requiredWhy Matt believes robotics companies should be careful about becoming an "everything platform" and instead build deep expertise around a clearly defined set of customer problemsWhat Matt looks for when hiring, including attitude, curiosity, adaptability, and the willingness to ask questions rather than simply following instructionsWhy engineers at the company work trade shows, interact directly with operators, and observe customers using the product so that real-world behavior can shape future software and hardwareMatt's concern that engineering education has become too theoretical, and why the next generation of robotics engineers needs far more hands-on experienceWhy the biggest misconception about collaborative robots remains the idea that they are coming for people's jobs when, in Matt's view, they are increasingly filling the jobs manufacturers cannot fill at allFor manufacturers still thinking of robotics as a complicated capital project reserved for high-volume production, this conversation offers a different vision: automation that arrives in a box, works alongside the existing workforce, and eventually becomes just another tool on the shop floor. Beacon platform: https://www.hirebotics.com/solutions/beacon-platform/ Cobot Welder: https://www.hirebotics.com/solutions/cobot-welder/ NEW Cobot Painter: https://www.hirebotics.com/solutions/cobot-painter/ New Tate case study: https://www.hirebotics.com/case-studies/tate-inc/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

    The Temp Agency for Robots with Matt Bush

  6. 2 Sept

    Why Your Sales Pipeline Deserves the Same Rigor as Your Factory Floor with Ed Marsh

    Industrial companies apply extraordinary rigor to manufacturing, quality, and operations, yet their approach to revenue growth is often far less disciplined. Founder and principal Ed Marsh joins Greg to explore what changes when manufacturers start treating marketing and sales like an integrated system that can be measured, optimized, and continuously improved. Ed brings decades of experience across engineering, the Army, industrial sales and marketing, international business, capital equipment, and consulting. Today, through Ed Marsh Consulting, he works primarily with middle-market industrial companies and private equity-backed manufacturers on organic revenue growth, spanning strategy, marketing, sales, technology, talent, and executive leadership. A central idea behind Ed’s work is Overall Revenue Effectiveness, a framework inspired by Overall Equipment Effectiveness in manufacturing. Instead of accepting leakage throughout the customer journey as inevitable, Ed argues that companies should examine every stage of the revenue engine, from understanding the buyer and generating demand to qualifying opportunities, coaching salespeople, and closing business. In this conversation, Greg and Ed explore: Why industrial buyers care far more about operational outcomes than product features, and why sellers need to understand how a solution affects KPIs, staffing, downtime, shipments, capacity, and the buyer’s day-to-day realityWhy identifying customer pain is only the beginning of a sales conversation, and why the real focus should be the business outcome a customer is trying to achieveHow Ed developed the Overall Revenue Effectiveness framework by treating organic revenue growth as an integrated system similar to a manufacturing operationWhy small inefficiencies across marketing and sales compound into extremely low overall revenue effectiveness, even when individual parts of the system appear to be performing reasonably wellWhy manufacturers would never tolerate the level of yield loss in production that they routinely accept in salesThe mindset shift required for leadership teams to bring the same accountability, rigor, process, and measurement to go-to-market functions that they already apply to operationsWhy private equity-backed industrial companies often provide a fertile environment for transformation, while family-owned businesses may have completely valid reasons to prioritize margins, stability, or lifestyle over aggressive growthWhat changes when Ed advises startups building AI-enabled software for manufacturers, and what remains constant about focusing on customer outcomes rather than product capabilitiesWhy a startup’s first salesperson can shape the company’s entire perception of sales, either reinforcing negative assumptions or establishing a powerful go-to-market cultureWhat founders should look for in an early sales hire, including business acumen, creativity, consultative selling skills, entrepreneurial instincts, and the ability to build systems while actively sellingWhy hiring based primarily on resumes and interviews creates problems, and how a more carefully engineered and empirically informed hiring process can improve sales talent decisionsHow founders should navigate the difficult transition when the person who helped build the early sales motion is no longer the right person to lead the next stage of growthWhy honesty, clear expectations, coaching, and a distinction between being "nice" and being "kind" matter when making difficult leadership decisionsHow AI-first CRM platforms are transforming CRM from a manually maintained database into a memory, context, and orchestration layer that can automatically capture emails, meetings, messages, buying signals, and opportunity informationHow AI can help sales managers identify coaching opportunities, prepare targeted role-playing exercises, improve forecasts, and spend more meaningful time developing their teamsWhy sales coaching and role playing have declined despite their importance, and why companies often expect salespeople to perform without the structured onboarding and training provided to other functionsHow manufacturers can begin experimenting with AI by building Claude skills, connecting tools through MCPs, and automating research and preparation rather than simply producing larger volumes of generic outreachEd’s own experiment building an AI-powered prospecting workflow that identifies ideal accounts, finds relevant contacts, enriches data, conducts research, populates CRM, and prepares prospecting blocks automaticallyWhy Ed believes sales is currently the bigger bottleneck than marketing, driven by fundamental changes in how buyers research, assess risk, and make purchasing decisionsThe danger of vague claims around "value" in industrial marketing, and why companies need to communicate specific, differentiated outcomesWhy ethical guardrails such as the Foreign Corrupt Practices Act matter even when commercial pressure is intense, and the responsibility leadership teams have to reinforce the reasoning behind those standardsFor industrial leaders, founders, sales teams, and investors trying to improve organic growth, this conversation offers a practical look at what happens when go-to-market performance is treated with the same seriousness as the factory floor, and how AI could make that revenue engine dramatically more intelligent. Ed Marsh Consulting Website: https://www.edmarshconsulting.com/ Ed Marsh’s Youtube Channel: www.youtube.com/@EdMarsh Connect with Ed on LinkedIn: https://www.linkedin.com/in/edwardbmarsh/ Connect with Ed on Twitter/X: https://www.linkedin.com/in/edwardbmarsh/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

    Why Your Sales Pipeline Deserves the Same Rigor as Your Factory Floor with Ed Marsh

  7. 26 Aug

    The Future of Software-Defined Automation with Etienne Lacroix

    Factory automation has traditionally been expensive, fragmented, and heavily dependent on specialized system integrators. Vention is challenging that model by turning automation into something closer to a software platform, where manufacturers can design, simulate, program, order, deploy, and operate industrial equipment within a connected digital ecosystem. Etienne Lacroix, founder and CEO of Vention, joins Greg to share how his early experience as a teenage system integrator exposed him to the inefficiencies of traditional automation and ultimately inspired a different approach. From modular hardware and browser-based 3D design to software-defined controls and physical AI, Etienne has spent the last decade building a platform designed to dramatically reduce the time, cost, and engineering complexity required to automate a factory. In this conversation, Greg and Etienne explore: How Etienne went from designing machines and selling automation cells at 19 to identifying the fundamental problems behind traditional system integrationWhy approximately 40% of traditional automation costs can come from engineering and integration, and how a platform-based approach can dramatically reduce that burdenThe technological breakthrough that made Vention possible: bringing engineering-grade 3D design into the web browser and connecting design directly with purchasing and deploymentEtienne’s simple mental model for Vention: combining 3D design software, industrial Lego, and Amazon Prime into one automation ecosystemHow Vention connects machine specification, 3D design, programming, simulation, ordering, deployment, monitoring, and support within a single digital workflowWhy reducing integration complexity can make automation accessible to mid-market manufacturers that historically could not justify the economicsHow Vention customers are achieving automation payback periods averaging around 1.3 years, while cutting deployment timelines by three to six times in some casesWhy a new generation of manufacturers, particularly in defense, could be a leading indicator for the future factory, with engineers bringing Python, AI, and modern software practices directly onto the shop floorWhat software-defined automation really means, and how separating hardware installation from programming could fundamentally change the role of system integratorsWhy Etienne believes the industry is already moving beyond software-defined automation toward AI-defined automationHow Vention’s MachineMotion AI controller, built with NVIDIA technology, is becoming the bridge between cloud-based digital twins and physical machines on the factory floorA real-world example of a complex 300-motor conveyor system that was largely vibe-coded and programmed in roughly three weeks instead of several monthsWhere physical AI is genuinely production-ready today, including perception, pose estimation, segmentation, and collision-free path planning, and where generalized vision-language-action models still fall shortWhy application-specific field data and teleoperation data may matter more than the underlying foundation model when bringing physical AI into industrial environmentsVention’s practical approach to AI validation, including letting manufacturers send in their own parts and proving cycle time and reliability before deeper commercial discussionsThe hidden challenge of industrial robotics: no matter how sophisticated the simulation becomes, real-world physics will always introduce edge cases engineers did not anticipateWhy Vention partners with established robot manufacturers such as Universal Robots and FANUC rather than building robot arms itself, choosing instead to focus on the deployment platform surrounding themHow Vention is gradually opening its ecosystem through developer tools while maintaining enough control to preserve a fast, seamless user experienceWhy manufacturing is becoming attractive again to top software, robotics, and AI talent as technology makes the industry increasingly scalableThe performance culture inside Vention, and how transparency, meaningful work, and professional development help the company grow engineers into future business leadersEtienne also shares his long-term ambition for Vention: having already helped shift automation from a system integrator-led model toward a platform-based one, the next challenge is building a company that permanently changes how factories around the world automate. Learn more about Vention: https://vention.com/ Connect with Etienne on LinkedIn: https://www.linkedin.com/in/etiennelacroix/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

    The Future of Software-Defined Automation with Etienne Lacroix

  8. 19 Aug

    Designing the Robot That Can Do Anything with Brian Ringley

    What happens when a robot is no longer built for one fixed task, but can potentially be retasked through software to do thousands of different things? Brian Ringley, HRI Designer at Boston Dynamics, joins Greg for the 150th episode of Machine Minds to explore that question through the evolution of Spot, Atlas, and the software systems that connect increasingly capable robots to the people and environments around them. Brian’s path into robotics is anything but conventional. After starting in architecture, CNC machining, industrial robotic arms, computational design, and construction technology, he found himself working at the intersection of digital models and physical automation. That journey eventually brought him to Boston Dynamics, first to explore construction applications for Spot, then into product management and industrial inspection, and now into human-robot interaction design for Atlas. In this conversation, Greg and Brian explore: How Brian’s background in architecture, digital fabrication, CNC machining, and industrial robot programming shaped the way he thinks about human-machine collaborationWhy construction became an early proving ground for Spot, from reality capture and laser scanning to safety monitoring and project progress trackingThe critical shift from thinking of “the robot as the product” to treating the robot as an invisible physical layer that creates value through the work it enablesWhy collecting more data is not enough, and how vision-language models and generative interfaces could let operators effectively “have a conversation” with factories and construction sitesThe enormous HRI challenge behind Atlas: designing an interaction model for a robot whose potential capabilities are effectively unboundedHow reinforcement learning, behavior cloning, vision-language-action models, reasoning systems, and traditional software tools can work together across the Atlas autonomy stackWhy Brian sees the real promise of humanoids as an economic breakthrough: one hardware platform that can be retasked through software instead of requiring new machines for every applicationWhy general-purpose hardware also demands generalizable software interfaces, rather than building a completely new application every time the robot learns a new taskHow Boston Dynamics balances natural human-like movement with Atlas’s superhuman range of motion, while deliberately designing it as an industrial tool rather than a human imitationWhy great hardware still matters in the age of physical AI, from reliability and field serviceability to strength-to-weight ratios, range of motion, manufacturability, and uptimeWhat the Google DeepMind partnership brings to Atlas, and why frontier reasoning models and high-quality robotic hardware can accelerate each otherBrian’s vision for the software-defined factory, where humanoids work alongside AMRs, fixed automation, inspection robots, digital twins, and other specialized machines rather than replacing themWhy teleoperation will remain valuable even as autonomy improves, especially in nuclear facilities, underground mines, collapsed buildings, launch sites, and other environments that are unsafe for peopleBrian also shares why robotics consistently gets overestimated in the short term and underestimated in the long term. Building systems that can understand natural instructions, reason about unfamiliar situations, manipulate the physical world, and operate reliably at scale remains extraordinarily difficult. But that difficulty is also part of what makes the field so compelling. For anyone working in robotics, industrial automation, human-robot interaction, or physical AI, this conversation offers a grounded look at what it will really take to move humanoids from impressive demonstrations to flexible, useful tools embedded throughout the physical world. Learn more about Boston Dynamics: https://bostondynamics.com/ Boston Dynamics’ Youtube Channel: https://www.youtube.com/user/BostonDynamics Connect with Brian Ringley on LinkedIn: Linktree: https://linktr.ee/brianringleyLinkedin: https://www.linkedin.com/in/bringley/Twitter/X: https://x.com/brianringleyConnect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

    Designing the Robot That Can Do Anything with Brian Ringley
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About

Machine Minds - the minds behind the machines! This is the show where we dive deep into the intricate worlds of robotics, AI, and Hard Tech. In each episode, we bring you intimate conversations with the founders, investors, and trailblazers who are at the heart of these tech revolutions. We dig into their journeys, the challenges they've overcome, and the breakthroughs that are shaping our future. Join us as we explore how these machine minds are transforming the way we live, work, and understand our world. 

Information

  • Creator
    Greg Toroosian
  • Years Active
    2023 - 2026
  • Episodes
    158
  • Rating
    Explicit
  • Copyright
    © 2026 Machine Minds
  • Show Website
    Machine Minds

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