Machine Minds

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 integration Why approximately 40% of traditional automation costs can come from engineering and integration, and how a platform-based approach can dramatically reduce that burden The technological breakthrough that made Vention possible: bringing engineering-grade 3D design into the web browser and connecting design directly with purchasing and deployment Etienne’s simple mental model for Vention: combining 3D design software, industrial Lego, and Amazon Prime into one automation ecosystem How Vention connects machine specification, 3D design, programming, simulation, ordering, deployment, monitoring, and support within a single digital workflow Why reducing integration complexity can make automation accessible to mid-market manufacturers that historically could not justify the economics How Vention customers are achieving automation payback periods averaging around 1.3 years, while cutting deployment timelines by three to six times in some cases Why 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 floor What software-defined automation really means, and how separating hardware installation from programming could fundamentally change the role of system integrators Why Etienne believes the industry is already moving beyond software-defined automation toward AI-defined automation How Vention’s MachineMotion AI controller, built with NVIDIA technology, is becoming the bridge between cloud-based digital twins and physical machines on the factory floor A real-world example of a complex 300-motor conveyor system that was largely vibe-coded and programmed in roughly three weeks instead of several months Where 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 short Why application-specific field data and teleoperation data may matter more than the underlying foundation model when bringing physical AI into industrial environments Vention’s practical approach to AI validation, including letting manufacturers send in their own parts and proving cycle time and reliability before deeper commercial discussions The hidden challenge of industrial robotics: no matter how sophisticated the simulation becomes, real-world physics will always introduce edge cases engineers did not anticipate Why 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 them How Vention is gradually opening its ecosystem through developer tools while maintaining enough control to preserve a fast, seamless user experience Why manufacturing is becoming attractive again to top software, robotics, and AI talent as technology makes the industry increasingly scalable The performance culture inside Vention, and how transparency, meaningful work, and professional development help the company grow engineers into future business leaders Etienne 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/

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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 collaboration Why construction became an early proving ground for Spot, from reality capture and laser scanning to safety monitoring and project progress tracking The 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 enables Why 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 sites The enormous HRI challenge behind Atlas: designing an interaction model for a robot whose potential capabilities are effectively unbounded How reinforcement learning, behavior cloning, vision-language-action models, reasoning systems, and traditional software tools can work together across the Atlas autonomy stack Why 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 application Why general-purpose hardware also demands generalizable software interfaces, rather than building a completely new application every time the robot learns a new task How 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 imitation Why 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 uptime What the Google DeepMind partnership brings to Atlas, and why frontier reasoning models and high-quality robotic hardware can accelerate each other Brian’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 them Why 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 people Brian 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/brianringley Linkedin: https://www.linkedin.com/in/bringley/ Twitter/X: https://x.com/brianringley Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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From Egyptian Ruins to First Responders: The VOTIX Story with Edwin Sanchez

From remote drone operations and public safety to hardware-agnostic robotics platforms, VOTIX is building the software layer designed to help organizations coordinate increasingly complex autonomous systems. Edwin Sanchez, founder and CEO of VOTIX, joins Greg to unpack the journey from a simple idea inspired by archaeology and remote tourism to an enterprise platform now supporting drone operations across 16 countries. Drawing on more than two decades in IT, digital transformation, and enterprise software, Edwin shares why great technology alone is never enough, and why timing, resilience, regulation, service, and market fit are just as critical to building a lasting hard tech company. The conversation explores how VOTIX acts as a kind of operating system for drone ecosystems, connecting different hardware, workflows, data sources, and third-party systems through one unified platform. Edwin also explains why public safety has become such an important use case, including how drone-first response programs can dramatically reduce emergency response times without requiring agencies to add more personnel. In this conversation, Greg and Edwin explore: How Edwin’s childhood in Colombia shaped his resilience, entrepreneurial mindset, and willingness to challenge difficult circumstances The early fascination with computer viruses and self-replicating software that sparked his interest in how software interacts with machines Lessons from more than 20 years in enterprise IT and digital transformation, including time working with companies like Microsoft, Oracle, and Adobe Why strong engineering needs to be paired with service, market timing, sales, marketing, and a founder willing to adapt The unlikely origin of VOTIX, from watching a live camera pointed at the pyramids to imagining remotely operated FPV drones anywhere in the world Why the original remote tourism concept was ahead of the market, and how customer feedback pushed VOTIX toward industrial, commercial, and public safety applications How VOTIX became hardware agnostic, allowing organizations to operate different drones and robotic systems through a common software layer Edwin’s analogy of VOTIX as a symphony conductor, coordinating every component of a complex drone workflow so the system performs as one The common operational building blocks across construction, mining, oil and gas, security, military, and public safety drone programs Why public safety agencies are turning to drones as staffing challenges, shrinking budgets, and growing cities make traditional response models harder to sustain How one police department reduced response visibility for priority emergencies from roughly 15 minutes to about 90 seconds using drone-based response The launch of VOTIX Situational Rooms, which brings drones, body cameras, mapping, audio, chat, and other data sources into a single source of truth for faster decision making Why the VOTIX vision extends beyond aerial drones to ground robots, robotic dogs, rovers, boats, submarines, and eventually humanoids How integrations with airspace, weather, and traffic management systems help organizations safely execute more complex drone operations The tension between public safety and privacy, and how software controls, audit logs, restricted camera movements, transparent feeds, and community education can help build public trust Edwin’s approach to hiring senior technical talent, maintaining a culture comfortable with constant change, and making difficult personnel decisions quickly Why VOTIX is increasingly looking for leaders with a global mindset as the company expands across enterprise and government markets Why Edwin believes “autonomous” is one of the most overhyped terms in the drone industry today The hardest lesson from building VOTIX: regulation, public perception, and forces outside a founder’s control can shape commercialization timelines far more than expected For anyone building robotics infrastructure, deploying drone fleets, working in public safety, or trying to understand what it takes to turn emerging hardware into scalable enterprise systems, this conversation offers a practical look at the software, people, and operating models behind the next generation of autonomous operations. Connect with Edwin on Linkedin: https://www.linkedin.com/in/edwinysanchez/ Learn more about VOTIX: Linkedin: https://www.linkedin.com/company/votix/ VOTIX Website: www.votix.com Instagram: @votixgobeyond Facebook: @Votix Additional Resources: Understanding the Role of Software Under Part 108 and Part 146 The Importance of Technological Diversity in DFR Operations Unlocking Drone Autonomy Exploring the Challenges of Transitioning from Legacy to Autonomy in Drone Operations Connect with Greg on Linkedin: https://www.linkedin.com/in/gregtoroosian/

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Wildlife Whisperer: Inside the AI Built to Talk to Animals with Sára Nožková

What if AI could help humans and wildlife coexist by understanding how animals communicate instead of simply trying to scare them away? In this episode of Machine Minds, Greg sits down with Sára Nožková, CEO and co-founder of Flox Intelligence, to explore how artificial intelligence, edge computing, and wildlife science are coming together to reduce collisions between animals and critical infrastructure. From airports and railways to farms and highways, Flox is building technology that listens to, learns from, and responds to wildlife in ways that improve safety for both humans and animals. Sára shares her journey from transportation research at KTH Royal Institute of Technology in Stockholm to founding a company that is pioneering what she calls "wildlife intelligence." She explains how years of AI research evolved into a platform capable of identifying animal behavior, interpreting species-specific communication, and guiding wildlife away from danger without relying on harmful or outdated deterrent methods. In this conversation, Greg and Sára explore: How a background in transportation and infrastructure led Sára to build one of the world's first AI platforms focused on wildlife communication Why traditional wildlife deterrents like pyrotechnics, fences, and gunshots often fail, and what a more intelligent approach looks like How Flox Edge devices combine computer vision, bioacoustics, and generative AI to detect, identify, and respond to more than 27 wildlife species The concept of the "Wildlife Brain" and how AI learns regional behaviors, dialects, and species-specific responses over time The engineering challenges of deploying autonomous AI hardware in some of the harshest environments on Earth, from Arctic winters to Texas summers Real-world deployments protecting airports, railways, farms, livestock, and transportation networks across Europe and North America Why partnerships with organizations like WWF, Alstom, and transportation authorities are helping validate an entirely new category of wildlife technology Lessons from scaling a deep tech startup across two continents, raising capital, expanding into the U.S., and building a mission-driven team Why understanding animal communication could fundamentally change how humans coexist with wildlife in an increasingly developed world Whether you're building AI at the edge, deploying robotics in challenging environments, or simply fascinated by how technology can solve problems beyond the factory floor, this episode offers a fascinating look at one of the most unexpected applications of artificial intelligence today. Learn more about Flox Intelligence: https://floxintelligence.com/ Connect with Sára Nožková on LinkedIn: https://www.linkedin.com/in/sára-nožková-91339685/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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The Robots Hospitals Urgently Need with Steve Pinto

Hospitals are among the most complex logistics environments in the world. Thousands of medications, meals, linens, supplies, and pieces of equipment must move through crowded buildings every day, often using manual processes, walkie-talkies, spreadsheets, and staff pushing carts between departments. Steve Pinto, CEO of CTRL Robotics, joins Greg to explore how purpose-built robots can improve the internal movement of hospital supplies while giving healthcare workers more time to focus on patients. Steve’s path into robotics began with entrepreneurship, augmented reality, virtual reality, and enterprise software. A project deploying service robots at South Africa’s Hotel Sky exposed him to the enormous gap between impressive robotics demonstrations and systems that can operate reliably in real environments. That experience led him and his co-founder to launch CTRL Robotics. Today, the company is focused on building the hardware, software, digital twins, and infrastructure required to automate hospital logistics from the ground up. In this conversation, Greg and Steve explore: Steve’s journey from growing up around tools and family businesses in South Africa to building AR, VR, software, and robotics companies How a hotel robotics deployment revealed the limitations of existing robots, integrations, APIs, and elevator control systems Why CTRL Robotics narrowed its focus to healthcare after working across multiple industries and global markets The hidden scale of hospital logistics, including the meals, medications, linens, waste, equipment, and supplies required to support hundreds or thousands of patients Why Steve compares a hospital to an Amazon fulfillment center with significantly more people, greater complexity, and no ability to stop operations The bottom-up approach to healthcare automation, focused on moving everyday items rather than developing surgical or diagnostic systems Why hospital corridors are well suited to mobile robots, even though most carts and equipment still need to be pushed manually How robots can support hospital employees rather than replace them by removing repetitive, physically demanding, and low-value tasks Why CTRL Robotics describes its machines as “time machines” that give skilled employees more time for meaningful work The “full bucket” problem that can leave patients waiting hours for medication that has already been prepared How robotic deliveries have reduced medication transport times from several hours to as little as seven to nine minutes Why restaurant and warehouse robots cannot simply be repurposed for hospitals without major changes to safety, navigation, security, and payload handling The challenge of navigating crowded, constantly changing hospital corridors filled with patients, beds, wheelchairs, spills, carts, and emergency activity How CTRL Robotics uses digital twins and elevator integrations to coordinate deliveries across multiple hospital floors Why dedicating certain elevators to robots could reduce waiting times and dramatically improve the movement of both people and supplies How private and public healthcare systems differ in their ability to evaluate and adopt new technologies Why labor shortages drive hospital automation in the United States, while efficiency, skills gaps, and concerns about job displacement shape adoption elsewhere CTRL Robotics’ effort to make deployments economically accessible, with robots operating at an estimated cost of roughly four dollars per hour How the company’s seed funding is supporting localized manufacturing, additive manufacturing, and a small-scale production facility in Florida Why Steve believes robotics companies should locate themselves close to customers, manufacturing talent, suppliers, and affordable operating infrastructure The advantages of Florida’s Space Coast for building physical products, extending runway, and supporting healthcare customers CTRL Robotics’ long-term goal of completing one million hospital deliveries every day Why Steve believes humanoids are currently overhyped, while narrow machines that perform one task reliably remain underappreciated The importance of empathy and patient-centered design when introducing robotics into healthcare environments Why culture fit, adaptability, commitment, and independence often matter more than credentials when hiring an early-stage robotics team Steve’s hardest-earned founder lesson: stop protecting the idea, accept failure quickly, and move forward with confidence For robotics founders, healthcare leaders, and anyone interested in the infrastructure behind patient care, this conversation offers a detailed look at how reliable mobile robots could help hospitals move faster, support overstretched teams, and deliver better care. Learn more about CTRL Robotics: https://ctrlrobotics.com/ Connect with Steve Pinto on LinkedIn: https://www.linkedin.com/in/stevenpinto7/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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No Cab, No Driver, New Rules for Freight with Eyal Cohen

Autonomous trucking has long focused on retrofitting yesterday's vehicles. Humble Robotics is taking a different path by reimagining freight from the ground up. Founder and CEO Eyal Cohen joins Greg to share why the future of logistics won't simply be autonomous trucks, but purpose-built electric freight platforms designed specifically for a world where vehicles move seamlessly from dock to dock without human intervention. With more than two decades building breakthrough technologies across electric vehicles, autonomy, and robotics, Eyal has witnessed multiple waves of innovation from inside companies ranging from startups to Apple and Uber. Drawing on those experiences, he explains why building transformative hard tech requires more than exceptional engineering. It demands patient capital, uncompromising hiring standards, rapid iteration, and a team united by trust. In this conversation, Greg and Eyal explore: Why Humble Robotics rejected traditional truck designs in favor of a purpose-built autonomous freight platform The vision for fully autonomous dock-to-dock freight movement and what it could mean for supply chains How simplicity in vehicle design unlocks improvements in cost, payload capacity, reliability, and operational efficiency Why freight's labor challenges are driven more by long-term workforce shortages than immediate job displacement, and how autonomy can help fill growing capacity gaps Lessons from two decades across electric vehicles, autonomous systems, startups, Apple, and Uber that shaped Eyal's approach to company building Why culture, trust, and hiring exceptional people across every function are more important than technology alone How Humble Robotics built its first vehicle at remarkable speed while maintaining an uncompromising commitment to safety and engineering quality The dangers of premature scaling in hard tech and why founders should prioritize customer feedback before optimizing for production volume Why patient investors like Eclipse understand the realities of commercializing hardware and supporting ambitious long-term technology bets Eyal's perspective on the return of "moonshot" innovation and why society should once again embrace bold, world-changing engineering challenges Whether you're building robots, autonomous vehicles, or the next generation of industrial technology, this episode offers a thoughtful look at what it takes to turn ambitious ideas into products that can reshape the physical world, one carefully engineered step at a time. Learn more about Humble Robotics: https://humblerobotics.ai/ Connect with Eyal Cohen on LinkedIn: https://www.linkedin.com/in/eyal-cohen-humble/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Investing in the Future of Physical Industry with Scott Walbrun

Scott Walbrun brings a unique perspective to venture capital. Having started his career inside the automotive industry before moving into investment banking and venture, he has spent years helping deep tech founders navigate one of the hardest challenges in robotics: turning impressive technology into repeatable, scalable businesses. As Principal at BMW i Ventures, Scott sits at the intersection of physical AI, robotics, manufacturing, industrial software, and advanced materials. In this conversation, he joins Greg to discuss what separates great robotics companies from great robotics demos, why commercial urgency often matters more than technical perfection, and how founders can build businesses that survive the long road from prototype to widespread deployment. Greg and Scott also explore how AI is reshaping the physical world, why venture investors are increasingly focused on real-world reliability over flashy demonstrations, and what founders should understand before raising institutional capital in today's deep tech landscape. Highlights: Scott's journey from automotive finance and investment banking to becoming a venture investor focused on robotics, mobility, and deep tech Why so much breakthrough technology never makes it from the lab into commercial markets, and what successful founders do differently How BMW i Ventures evaluates Series A and B companies across physical AI, robotics, industrial software, advanced materials, and manufacturing technologies Why commercial validation is just as important as technical validation when building a venture-scale company The hidden costs of deploying robotics at scale, including maintenance, field service, reliability, and total cost of ownership What investors really mean when they ask about repeatability, and why one successful pilot is rarely enough How physical AI is moving beyond hype into real applications across manufacturing, quality inspection, warehouse automation, and enterprise operations The biggest mistakes robotics founders make when trying to scale too quickly Why founders should personally own customer development before building large sales teams Scott's advice for raising venture capital, building durable businesses, and maintaining the sense of urgency that separates exceptional founders from everyone else Whether you're building robotics, industrial AI, or any capital-intensive technology company, this episode offers practical insight into what investors look for, what customers actually value, and how to bridge the gap between breakthrough innovation and lasting commercial success. Learn more about BMW i Ventures: https://www.bmwiventures.com/ Connect with Scott Walbrun on LinkedIn: https://www.linkedin.com/in/scottwalbrun/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Inside the Hidden Layer of Robotics with Simone Gianotti

From surgical robots and autonomous underwater vehicles to humanoids and space exploration, motion control is one of the invisible technologies making modern robotics possible. Yet despite its critical role, it's often overlooked until something goes wrong. Simone Gianotti, Application Engineer Manager at Elmo Motion Control, joins Greg to explore what it takes to deliver precision, reliability, and flexibility across some of the world's most demanding robotic applications. Drawing on a career that spans aerospace engineering, automation, sales, and technical leadership, Simone shares why successful robotics companies know when to build, when to buy, and why solving customer problems often matters more than finding the perfect engineering answer. In this conversation, Greg and Simone explore: Why motion control sits at the heart of high performance robotics, from medical devices and humanoids to subsea vehicles and planetary rovers The common engineering challenges that appear across radically different robotic platforms, including tuning, reliability, electrical noise, and thermal management Why many robotics startups lose valuable time trying to build every subsystem themselves instead of focusing on their core innovation How products that perform perfectly in the lab can encounter unexpected problems once they reach real world deployments The importance of designing for safety, scalability, and future product generations from the very beginning rather than retrofitting later What separates exceptional application engineers, combining deep technical expertise with customer empathy and collaborative problem solving The robotics markets seeing the strongest momentum today, including medical robotics, subsea systems, and humanoid platforms How AI is changing robotics development and why many companies are shifting their focus toward building intelligent software rather than complete robotic systems The ongoing debate around humanoid robots versus more task specific designs, and why the industry is still discovering which approaches will ultimately win Simone's perspective on the future of AI powered motion control and what truly intelligent servo drives could eventually make possible Whether you're developing next generation robotic systems, selecting components for demanding applications, or simply curious about the technology enabling modern automation, this conversation offers an insightful look inside one of robotics' most important building blocks. Learn more about Elmo Motion Control: https://www.elmomc.com/ https://www.elmomc.com/media/elmo-in-action/ https://www.elmomc.com/media/case-studies/ https://www.roboticstomorrow.com/article/2026/05/elmo-motion-control-talks-about-their-newest-servos/26508#new_tab https://www.elmomc.com/products/industrial-environment/titanium-family-industrial/ https://www.elmomc.com/products/industrial-environment/servo-drive-platinum-family/ Connect with Simone Gianotti on LinkedIn: https://www.linkedin.com/in/simone-gianotti-889ba427 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Why the Future of Robotics Runs on Orchestration with Saurabh Gupta

Warehouse automation is entering a new phase. The challenge is no longer building individual robots. It's coordinating fleets of robots, software systems, and human workers into a seamless, intelligent operation. Saurabh Gupta, Chief Technology Officer at GreyOrange, joins Greg to explore why orchestration is becoming the defining layer of modern warehouse automation. Drawing on a career that spans Apple, Amazon, educational robotics, healthcare, and autonomous systems, Saurabh shares lessons from helping scale technologies that bridge the gap between technical complexity and real-world usability. From working on the first iPhone production line to leading the evolution of GreyOrange from a robotics company into a warehouse orchestration platform, Saurabh offers a unique perspective on what it takes to move robotics from impressive demos to scalable, reliable systems that deliver business value. In this conversation, Greg and Saurabh explore: Lessons from Apple's product culture and why the best technology is often invisible to the user What working on the original iPhone taught Saurabh about vision, product design, and disruptive innovation How educational robotics revealed the importance of understanding human behavior before building technology Why the gap between a robotics demo and a real-world deployment remains one of the industry's biggest challenges The transition from viewing robotics as a hardware problem to understanding it as an orchestration problem GreyOrange's evolution from warehouse robot manufacturer to software platform coordinating robots, humans, conveyors, and automation systems Why vendor-agnostic orchestration is critical for the future of warehouse automation How AI creates practical value through exception handling, prediction, and real-time operational decision-making The role of data in building warehouse "world models" capable of anticipating disruptions before they happen Why fully autonomous warehouses may be the wrong goal and what highly orchestrated human-robot collaboration looks like instead Common mistakes robotics companies make when scaling products, manufacturing, and deployments What separates impressive engineering organizations from effective engineering organizations The importance of simulation-first development and testing before real-world deployment Why robotics founders must be crystal clear about the single problem their product solves Saurabh's vision for intelligent warehouse systems that can autonomously anticipate and resolve problems before humans even notice them For anyone building robots, deploying automation, or trying to understand where AI and physical systems are headed next, this episode offers a practical look at how orchestration, intelligence, and human-centered design are shaping the future of warehouse operations. Saurabh's LinkedIn: https://www.linkedin.com/in/saurabhgupta6/ GreyOrange LinkedIn: https://www.linkedin.com/company/gogreyorange/ GreyOrange website: https://www.greyorange.com/ GreyMatter - GreyOrange's warehouse solution: https://www.greyorange.com/greymatter/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Humanoids Beyond the Hype with Jide Akinyode

Humanoid robots are moving beyond flashy demos and into some of the hardest environments on Earth: shipyards, energy sites, manufacturing floors, construction projects, and other industrial settings where skilled labor is scarce and the work is often dangerous, physically demanding, and difficult to automate. Greg sits down with Jide Akinyode, co-founder and COO of Persona AI, to unpack what it really takes to build humanoids for heavy industry. Jide traces his path from NASA Johnson Space Center, where he started at 19 and spent a decade working on advanced dexterity, robotic astronauts, humanoids, and mobile manipulators, to Nauticus Robotics, where he helped bring robotic manipulation into harsh subsea environments. Now at Persona AI, Jide is focused on building industrial humanoids that can do real work in places where traditional automation struggles. The conversation explores why shipbuilding is such a compelling first market, why the humanoid form factor matters in cluttered human-built environments, and what robotics companies often underestimate about deployment, maintenance, workflow integration, and customer adoption. Highlights: Jide’s path from NASA Johnson Space Center to Nauticus Robotics, and how building robots for space and subsea environments shaped his view of commercial robotics. What changed in 2024 that shifted him from humanoid skeptic to founder, including stronger component supply chains, better simulation tools, reinforcement learning, behavior mimicry, and embodied AI. Why Persona AI is starting with heavy industries like shipbuilding, energy, construction, and manufacturing rather than homes, offices, or retail environments. The labor gap in skilled trades, including welders, grinders, painters, and fabricators, and why Persona sees humanoids as an alternative labor solution for industrial operators. Why humanoids do not need to look human, but do need the mobility, dexterity, and flexibility to work in spaces designed around human bodies and hands. What shipyards reveal about automation: tight spaces, massive structures, fragmented workflows, and the surprising reality that welders may spend only a small portion of their day actually welding. The challenge of moving from impressive demos to industrial deployments, including transparency with customers, realistic POCs, expectation management, and proving reliability over time. How Persona evaluates first deployments by looking at robot density, task value, customer readiness, cost of the current workflow, and the likelihood of real adoption. Why the challenge is not just hardware or autonomy, but the entire stack: mechanical design, embedded systems, controls, perception, autonomy, fleet management, manufacturing, operations, and customer workflow integration. What a successful early deployment could look like, from rugged robots surviving shipyard environments to reliably laying down welds in small and medium block assembly. The breadth of talent required to build humanoids, from actuation, structures, mechanisms, embedded software, controls, manipulation, locomotion, perception, autonomy, data collection, ML, manufacturing, supply chain, and operations. Why ML, autonomy, manipulation, and grasping talent are especially hard to find in today’s robotics market. How Jide thinks about culture, communication, and company building as COO, including why his “product” is now the team, the operating system, and the way Persona scales. The future Jide wants to see: humans moved away from dangerous physical work and upskilled into robot operators, fleet managers, and technical supervisors. Jide’s advice for anyone building robotics that changes the physical world: talk to customers, listen deeply, strip away assumptions, and get ready for hard work. For anyone building robots, hiring robotics teams, or trying to understand where humanoids will actually create economic value, this conversation offers a grounded look at the long road from demo videos to real industrial deployment. Learn more about Persona AI: LinkedIn: https://www.linkedin.com/company/persona-humanoids-at-work/posts/?feedView=all X / Twitter: https://x.com/personaaiinc Instagram: https://www.instagram.com/persona_ai_official/ YouTube: https://www.youtube.com/@persona_ai_inc Connect with Jide Akinyode on LinkedIn: https://www.linkedin.com/in/jideakinyode/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Making Material Movement Autonomous with Michael Lawrence

Autonomous forklifts and pallet jacks may generate plenty of headlines, but the real challenge isn't building robots that can move. It's building solutions that fit seamlessly into existing operations, deliver measurable ROI, and earn customer trust over years of deployment. Michael Lawrence, Director of Sales and Business Development at Anantak Robotics, joins Greg to discuss what it actually takes to bring autonomous material handling systems into warehouses and manufacturing environments. Drawing on a career that spans electrical engineering, entrepreneurship, robotics, and commercial strategy, Michael shares why successful automation is as much about partnerships, process design, and customer education as it is about technology. At Anantak Robotics, Michael helps bridge the gap between technical capability and operational reality, helping customers deploy autonomous tuggers, pallet jacks, and forklifts that solve real-world material movement challenges without forcing facilities to redesign how they work. In this conversation, Greg and Michael explore: Why many robotics companies underestimate the importance of business ecosystems, service networks, and partnerships when bringing automation to market The lessons Michael learned building his first autonomous construction equipment company and how they shaped his view of commercialization Why warehouse automation sales cycles often take years, not months, and what separates successful deployments from stalled pilot projects How Anantak approaches autonomous material handling with tuggers, pallet jacks, and forklifts designed for existing warehouse and manufacturing environments The importance of fitting into customer workflows rather than forcing facilities to adapt to the technology Where autonomous material movement delivers the fastest ROI and why clearly defined operating procedures accelerate adoption What "practical autonomy" looks like in messy, real-world environments filled with variability, edge cases, and imperfect conditions Why customer champions, change management, and operator feedback are critical ingredients for long-term deployment success The role of humans in the loop and why robots are best viewed as tools that eliminate repetitive tasks rather than replace people Common misconceptions customers have about warehouse automation and how education helps close the expectation gap Why Michael believes many robotics companies focus on building technically impressive products instead of solving the problems customers actually care about His perspective on humanoid robots, material handling automation, and where the industry is headed over the next decade How consolidation, improved capabilities, and growing customer familiarity could drive the next major wave of warehouse automation adoption For anyone building robotics companies, deploying automation, or trying to understand what separates hype from real-world value creation, this episode offers a grounded look at how practical autonomy is reshaping material handling operations one deployment at a time. Learn more about Anantak Robotics: Website: anantak.com Email: sales@anantak.com LinkedIn: linkedin.com/company/anantak-robotics Connect with Michael Lawrence on LinkedIn: https://www.linkedin.com/in/mglaw/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Building the Foundation Model for Construction with Francesco Iorio

Construction is one of the world’s largest industries, yet much of the design process still depends on manual coordination, long hours, and workflows that struggle to keep pace with growing project complexity. Francesco “Frio” Iorio, co-founder and CEO of Augmenta, joins Greg to explore how AI-native design tools could fundamentally reshape the future of construction, engineering, and collaboration across the built environment. Before founding Augmenta, Frio spent years working in computational science, generative design, and advanced AI systems at Autodesk Research. His experience applying artificial intelligence to manufacturing, aerospace, and simulation eventually led him toward one of the hardest design problems imaginable: construction. At Augmenta, he and his team are building AI systems capable of generating detailed construction blueprints for electrical systems and eventually entire buildings, helping contractors and engineers dramatically compress timelines while reducing burnout and coordination overhead. In this conversation, Greg and Frio explore: Why construction presents a fundamentally different AI challenge than software or manufacturing, and why design in the built environment has “no amortization” How Augmenta’s AI generates construction-ready electrical blueprints from scratch, similar to how AI coding agents generate software Why building design is ultimately a geometry, constructability, and real-world reasoning problem rather than a language problem The hidden complexity of “unwritten rules” in construction, and how AI must learn the field knowledge that experienced foremen and electricians develop over decades How AI-driven design can reduce weeks of coordination work into days or even hours on hospitals, data centers, and other mission-critical infrastructure projects Why contractor burnout, labor shortages, and compressed schedules are accelerating demand for AI-powered workflows The challenge of building trust with contractors and field teams, and why deep customer collaboration became essential to Augmenta’s product development What Augmenta’s five-year strategic partnership with EJ Electric signals about the broader construction industry’s readiness for advanced AI adoption How AI could reshape collaboration between engineers, contractors, owners, and specialty trades by compressing pre-construction timelines and improving coordination Why Frio believes the biggest impact of AI in construction will not just be automation, but a fundamental restructuring of how projects are delivered and how companies operate For anyone interested in AI for physical industries, construction technology, or the future of engineering workflows, this episode offers a deep look into how intelligent systems could transform the way buildings are designed and delivered. Learn more about Augmenta: https://www.augmenta.ai/ https://www.linkedin.com/company/augmenta-ai/posts/?feedView=all Connect with Francesco Iorio on LinkedIn: https://www.linkedin.com/in/francescoiorio/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Robots Don’t Replace Work. They Redesign It. — with Michelle Lo

As robotics and AI reshape manufacturing, the hardest challenge is often not the technology itself. It is helping people, processes, and entire organizations successfully adapt to it. GrayMatter Robotics is tackling that challenge head-on by building AI-powered automation systems designed for real-world manufacturing environments where variability, human expertise, and operational complexity are everywhere. Michelle Lo, Director of Customer Strategy and Success at GrayMatter Robotics, joins Greg to discuss what it actually takes to deploy automation in high-mix manufacturing environments. Drawing from her background in electric vehicles and industrial automation, Michelle shares why successful robotics adoption depends just as much on customer alignment, operator trust, and long-term partnership as it does on the robots themselves. Greg and Michelle explore the realities of manufacturing transformation, from backlog-driven demand and workforce shortages to the nuanced collaboration between humans and robots on the factory floor. They also unpack why configurable automation platforms are enabling faster deployment cycles, how manufacturers evaluate ROI beyond labor replacement, and why “perfect” automation is not always what customers actually want. Highlights: Michelle’s journey from EVs and automotive manufacturing into customer strategy and robotics at GrayMatter Robotics Why automation adoption is a long-term transformation journey rather than a one-time deployment The hidden labor shortages driving demand for automation across industries like aerospace, specialty vehicles, and industrial manufacturing How GrayMatter Robotics partners directly with operators during deployment to improve adoption and long-term success The difference between configurable automation platforms and fully custom systems and why deployment speed matters Why manufacturers evaluate robotics based on throughput, consistency, quality, and capacity rather than simple labor replacement Lessons from real-world production environments where no two parts, surfaces, or workflows are ever exactly the same How AI-powered automation systems adapt to high-mix manufacturing environments with constantly changing variables Michelle’s perspective on humanoid robots and why purpose-built industrial systems are often better suited for manufacturing tasks The surprising reality that some customers intentionally want “imperfect” robotic finishes to preserve the familiar look and feel of legacy products How AI and predictive factory intelligence could optimize everything from workflow orchestration to production efficiency in the near future What makes a successful automation partnership before, during, and after deployment If you are building automation for manufacturing, deploying robotics at scale, or navigating the human side of industrial transformation, this episode offers a grounded look at how AI-powered systems are changing the factory floor while keeping people at the center of the process. Learn more about GrayMatter Robotics: https://graymatter-robotics.com/ https://www.linkedin.com/company/graymatter-robotics/ https://x.com/GrayMatterRobot Connect with Michelle on LinkedIn: https://www.linkedin.com/in/michlo/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Conviction Before Consensus - Outlander VC with Paige Craig

From bootstrapping a defense intelligence startup with five credit cards to backing some of the most ambitious robotics and autonomy companies in the world, Paige Craig has built his career around one core belief: exceptional people matter more than polished ideas. In this conversation, Paige Craig, founder and managing partner of Outlander VC, joins Greg to unpack how his unconventional path through the Marine Corps, intelligence work, and entrepreneurship shaped his philosophy as an investor. Paige shares why he spends more time analyzing founders than products, how his team evaluates leadership under chaos, and why physical AI and robotics will define the next two decades of innovation. The discussion also dives deep into the realities of robotics deployment, the hidden complexity behind autonomy, and what separates founders who can survive the brutal transition from prototype to real-world scale. Highlights: Paige’s journey from a difficult childhood and military service to building and bootstrapping a multi-hundred-million-dollar intelligence company Why Outlander VC invests at the “pre-conception” stage, backing founders before products or customers exist The 38-point founder framework Outlander uses to evaluate vision, intelligence, character, and execution Why great founders often emerge from hardship, high agency, and an obsession with solving problems The loneliness of leadership and why Paige believes the best investors act as true problem-solving partners How Outlander structures conviction-driven investing, including single-partner authority to write early checks Why physical AI, robotics, and automation are entering a massive growth cycle driven by AI, manufacturing reshoring, and falling hardware costs The biggest differences between investing in robotics versus pure software startups Why cheap, rapidly deployable robots often outperform “exquisite” high-cost systems in the race toward autonomy Lessons from backing Coco Robotics and Havoc AI, including the realities of deploying robots into unpredictable real-world environments The overlooked operational challenges of robotics businesses: supply chains, government relations, field operations, and human oversight Why many robotics founders underestimate the difficulty of scaling hardware systems outside the lab Paige’s perspective on defense tech investing, the influx of “tourist VCs,” and what founders should look for in strategic investors The leadership gaps technical founders often face as companies scale, and how mentorship can help engineering leaders grow into organizational leadership roles Why AI may fundamentally reshape the future role of engineering leadership and startup team structures Connect with Paige Craig on LinkedIn: https://www.linkedin.com/in/paigecraig/ Learn more about Outlander VC: https://outlander.vc/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

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Building Robots People Trust: The Andromeda Vision with Grace Brown

From engineering-first robots to emotionally intelligent companions, Andromeda Robotics is redefining what human-robot interaction can look like in the real world. Grace Brown, founder and CEO of Andromeda Robotics, joins Greg to share her journey from a STEM-obsessed student in Australia to building one of the most distinctive companies in the humanoid robotics space. What started as a response to isolation during COVID has evolved into Abby, a social companion robot designed to bring meaningful connection into aged care environments. Rather than optimizing for flashy demos or industrial efficiency, Grace and her team are focused on something far more complex: building robots that people trust, relate to, and genuinely care about. In this conversation, she unpacks why emotional intelligence is the missing layer in robotics, how design and psychology shape adoption, and what it will take for humanoids to scale in human environments. Highlights: Grace’s early path into engineering and how a clear passion for math, physics, and problem-solving led her toward robotics from a young age The founding story of Andromeda Robotics and how strict COVID lockdowns in Australia exposed the real-world impact of loneliness Why Abby was designed as a character, not a tool, and how Pixar-inspired design principles drive trust and adoption The overlooked challenge of social acceptance in robotics and why capability alone is not enough to succeed in human environments Real-world deployments of Abby in aged care facilities and what the team has learned from observing how people actually interact with robots The importance of personalization in human-robot interaction, from voice tuning to behavioral adaptation for individual users Why emotional intelligence and “social awareness” will be critical for all robots working alongside humans, even outside consumer settings The interdisciplinary nature of building social robots, combining engineering, animation, healthcare insight, and operations How Grace thinks about hiring, from early generalists to later specialists, and why mission alignment is the most important filter The concept of “anti-selling” during hiring to attract people who truly want ownership and responsibility in a startup environment Using AI agents internally to accelerate iteration speed and rethink how teams build and operate in modern startups The broader responsibility of shaping the future of robotics and why who builds this technology will determine its impact on society Learn more about Andromeda Robotics: Youtube: https://www.youtube.com/@AndromedaRobotics Website: https://andromedarobotics.ai/ LinkedIn: https://www.linkedin.com/company/andromedarobotics/posts/?feedView=all Connect with Grace Brown: Instagram: https://www.instagram.com/grace.jbrown/ LinkedIn: https://www.linkedin.com/in/grace-brown-619b59161/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

Rethinking Defect Detection in Modern Manufacturing with Matt Puchalski

From autonomous vehicles to factory floors, a new wave of vision technology is transforming how manufacturers think about quality. Bucket Robotics is at the center of that shift, bringing simulation-driven inspection systems to an industry long reliant on manual checks and outdated tooling. Matt Puchalski, founder and CEO of Bucket Robotics, joins Greg to share how his experience in self-driving cars shaped a fundamentally different approach to quality inspection. Instead of relying on expensive hardware or months of data collection, his team is using CAD-based simulation to generate training data instantly, unlocking faster deployment, lower costs, and more scalable automation. We explore why quality inspection remains one of the most painful bottlenecks in manufacturing, how legacy vision systems have failed to keep up, and what it takes to build robots that actually work outside of polished demos. Highlights: Matt’s journey from Georgia Tech and Michelin to autonomy startups and ultimately founding Bucket Robotics Why quality inspection is still one of the most manual, inconsistent, and frustrating parts of manufacturing The core insight behind Bucket: applying self-driving car vision systems to factory environments How CAD-based simulation replaces months of data collection with minutes of synthetic training data The “sim-to-real” challenge and why perception in changing lighting and environments is harder than it looks Why most vision systems fail in production and how Bucket is designed for real-world robustness from day one Lessons from early market assumptions, including why medical device manufacturing was not the right starting point The economics of inspection: balancing cost, speed, and accuracy across high-mix and high-volume environments What makes a strong customer fit, from ambiguous defect definitions to expensive rework caught too late Common objections from manufacturers burned by legacy vision systems and how simulation changes the equation Why labor shortages and supply chain reshoring are accelerating demand for automated quality solutions Hiring for empathy in robotics and why understanding the end operator matters more than credentials The importance of engineers who ship, not just prototype, and why early adopters beat bleeding edge thinkers Hard-earned hiring lessons, especially the need for teams willing to travel and work onsite with customers Where robotics is overhyped today, especially around deployment at scale versus polished demos Why lightweight, lower-cost robotic systems are unlocking a new wave of practical automation Matt’s view on the future of manufacturing: a hybrid human and robotic workforce rather than full autonomy Founder reality: why building a company can feel easier than operating autonomous vehicles, but far more isolating The long-term vision for Bucket Robotics as the “cloud computing moment” for manufacturing quality systems Matt's LinkedIn: https://www.linkedin.com/in/matt-puchalski/ Bucket's LinkedIn: https://www.linkedin.com/company/bucketrobotics/ Matt's email: matt@bucketrobotics.com Bucket's Youtube: https://www.youtube.com/@Bucket_Robotics Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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Building Factory SuperIntelligence with Ariyan Kabir

From disaster response inspiration to reimagining the backbone of global manufacturing, GrayMatter Robotics is tackling one of the largest untapped opportunities in automation: bringing true autonomy to the 90% of factory work still done by hand. Ariyan Kabir, co-founder and CEO of GrayMatter Robotics, joins Greg to share how a firsthand experience with an earthquake in Bangladesh sparked his mission to build intelligent machines that can take on dangerous, tedious work. What started as a question about why robots were not helping in high-risk environments has evolved into a company building “factory superintelligence,” a full stack physical AI platform designed to transform how goods are made. In this conversation, Ariyan breaks down why traditional robotics has struggled in high variability environments, how GrayMatter is bridging the gap with multimodal sensing and foundation models for manufacturing, and why solving these challenges is critical not just for productivity, but for economic resilience and national security. Highlights: Ariyan’s journey from aspiring astronaut to robotics founder, and how a real world disaster shaped his mission to build intelligent, helpful machines The hidden reality of manufacturing, with nearly 90% of production still manual despite decades of automation The core problem GrayMatter is solving, enabling robots to adapt to high variability in materials, environments, and processes Why physical AI requires more than vision alone, and how multimodal sensing unlocks real world autonomy Starting with sanding as a strategic wedge, then expanding into grinding, painting, blasting, and inspection through transferable learning The power of data, building one of the largest manufacturing datasets to train foundation models for materials and processes Robot scientists and domain specific AI agents that compress process optimization timelines from months to days How optimizing human, robot, and AI workflows can drive massive gains, including tripling throughput without adding robots Lessons from early deployment challenges, from consumables to real world variability, and how they shaped more intelligent systems The importance of an adoption playbook, and why deploying robotics successfully depends on process and people as much as technology Ariyan’s perspective on talent, why high agency and system level thinkers are the most valuable builders in the age of AI What is still missing in robotics today, and why domain specific intelligence layers are the next frontier A vision for the future, rapidly reconfigurable, fully autonomous factories that can adapt in real time to new products and global needs For founders, engineers, and operators thinking about the future of manufacturing, this episode offers a deep dive into how physical AI will reshape the industrial world and why the race to build intelligent factories is just getting started. Learn more about GrayMatter Robotics: https://graymatter-robotics.com/ https://www.linkedin.com/company/graymatter-robotics/posts/?feedView=all https://x.com/GrayMatterRobot Connect with Ariyan Kabir: https://x.com/ariyankabir https://www.linkedin.com/in/ariyankabir/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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From Robots to Revenue: Marketing That Actually Works in Automation with Kait Peterson

Warehouse automation is no longer a question of if, but when. As supply chains face growing pressure from labor shortages, unpredictable demand spikes, and rising customer expectations, robotics is becoming a critical lever for speed, accuracy, and resilience. Kait Peterson, VP and Head of Marketing at Locus Robotics, joins Greg to break down how modern warehouse automation is evolving from rigid, capital-intensive systems into flexible, scalable solutions that can adapt in real time. Drawing on 15 years in supply chain technology, Kait shares how robotics, data, and physical AI are reshaping fulfillment operations and why the next wave of adoption will look very different from the last. Kait brings a unique perspective at the intersection of marketing, robotics, and human-centered leadership. From making hundreds of cold calls selling warehouse software early in her career to helping scale one of the most recognized brands in warehouse automation, she has seen firsthand how the industry has shifted from skepticism to rapid acceleration. Now at Locus Robotics, she helps translate complex automation systems into clear business value while championing greater inclusion across the tech ecosystem. In this conversation, Greg and Kait explore: Kait’s journey from supply chain SaaS into robotics and how early exposure to warehouse operations shaped her approach to marketing and leadership Why flexibility is becoming the defining advantage in warehouse automation, especially for brownfield facilities that cannot afford disruption How Locus Robotics differentiates through its Robots as a Service model, combining deployment, maintenance, and continuous optimization into a single offering The role of physical AI and why data from billions of robot interactions is becoming a competitive moat in modern automation What success looks like for customers, from improved throughput and accuracy to better worker retention and operational scalability Why marketing in robotics is fundamentally different from traditional B2C and SaaS, and how understanding customer problems outweighs technical specifications The shift from early skepticism to ROI-driven adoption and why automation decisions are now tied to short-term financial performance How category creation is shaping the market, including Locus’s push toward a new “robots to goods” paradigm The importance of change management and why the most successful robotics deployments focus as much on people as they do on technology Why warehouse automation is still in its early innings, with the vast majority of facilities remaining unautomated The debate between humanoids and purpose-built robotics, and why solving specific problems may matter more than mimicking human form Kait’s leadership philosophy, from building teams rooted in curiosity and collaboration to avoiding common hiring pitfalls Her perspective on increasing representation in robotics and why creating inclusive environments is critical to the industry’s future For anyone building, deploying, or evaluating automation in supply chain operations, this episode offers a practical and forward-looking view of where warehouse robotics is headed and what it takes to succeed in a rapidly evolving market. Learn more about Locus Robotics: https://locusrobotics.com/ Learn more about The Feminist Exec: https://www.feministexec.com/ Connect with Kait Peterson: https://www.linkedin.com/in/kaitvinson/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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The First In-Person Machine Minds with Flyhound, Modovolo, Flox Intelligence, and Aerialoop

A rare in-person episode brings together four founders building at the frontier of drones, autonomy, and physical AI. Recorded live from the Drones and Robotics AI Summit in New York, this conversation spans search and rescue, wildlife protection, aerial logistics, and next-generation drone platforms—offering a real-time snapshot of where the industry is heading. From detecting phones in disaster zones to decoding animal communication, deploying drone delivery networks at city scale, and rethinking the cost-performance curve of aerial systems, each founder shares how they are tackling hard, real-world problems—and what it takes to move from prototype to deployment. In this conversation, Greg speaks with Manny Cerniglia (Flyhound), Sara Nozkova (Flox Intelligence), Santiago Barrera (Aerialoop), and Justin Call (Modovolo) about: How Flyhound is turning everyday devices into life-saving signals by enabling drones to locate and identify phones, even without cell service, for search and rescue and disaster response Why radio frequency complexity remains one of the hardest challenges in real-world deployment, and how environmental factors shape system performance How Flox Intelligence is using AI to decode animal communication and prevent human-wildlife conflicts across airports, railways, and industrial sites The shift from drone-based systems to edge-deployed stationary units, and what it takes to move from research to validated, real-world impact Why physical AI startups face unique hurdles in funding, scaling hardware, and bridging the gap between prototype and production How Aerialoop built a “metro system in the sky,” operating high-frequency drone logistics networks and moving everything from food to medical samples in dense urban environments Lessons from scaling to hundreds of daily drone flights, including what breaks first in operations, manufacturing, and training The importance of regulatory collaboration—and how working alongside governments can accelerate deployment instead of slowing it down Why finding the right early customers is as critical as finding the right investors when building frontier technology How Modovolo is rethinking drone design to dramatically improve performance while reducing cost, unlocking new use cases across defense, public safety, and commercial sectors The growing demand for modular, payload-driven drone systems—and why enabling customer innovation is key to long-term adoption This episode is a fast-moving look at the builders pushing drones and robotics out of the lab and into the real world—one deployment, one partnership, and one hard-earned lesson at a time. Connect with Manny Cerniglia: https://www.linkedin.com/in/mannyce/ Learn more about Flyhound: https://www.flyhound.com/ Connect with Sara Nozkova: https://www.linkedin.com/in/sára-nožková-91339685/ Learn more about Flox Intelligence: https://floxintelligence.com/ Connect with Santiago Barrera: https://www.linkedin.com/in/santiagobarrerav/ Learn more about Aerialoop: https://www.aerialoop.com/ Connect with Justin Call: https://www.linkedin.com/in/justincall/ Learn more about Modovolo: https://modovolo.com/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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From Models to Machines: Building AI That Actually Delivers with Ash Saxena

From early experiments with dismantled electronics to building AI systems that power real-world machines, Ash Saxena has spent decades at the intersection of research, entrepreneurship, and applied intelligence. Now, as Founder & Chief AI Officer of TorqueAGI, he is focused on one of the most ambitious challenges in technology: enabling robots to perform meaningful work in the physical world. Ash brings a rare depth of experience, from his PhD work at Stanford alongside Andrew Ng to founding and scaling multiple AI-driven companies. His perspective cuts through the noise of today’s AI hype cycle, offering a grounded view on what is actually working, what is misunderstood, and where the real opportunities lie in robotics and embodied intelligence. We explore how the shift from data-driven AI to reasoning-based systems is reshaping robotics, why most companies are approaching the problem the wrong way, and what it takes to move from impressive demos to reliable deployment in the real world. Highlights: Ash’s journey from building robots as a child to leading AI innovation across academia and industry, including early work on deep learning for robotics Key inflection points that led him to found multiple companies, including applying AI to unlock access to credit through Catapult Why “technology-first” companies often fail and the importance of aligning AI with real customer demand and ROI The evolution of AI from statistical models to deep learning to today’s foundation models and reasoning-based systems Why the biggest shift in AI is not better models, but dramatically faster time to deployment from years to days or weeks What Torque AGI is actually building: end-to-end robotic “skills” that combine foundation models, agents, and real-time infrastructure Why data collection at massive scale may not be the answer and how useful systems can be built with far less data than expected The gap between AI demos and real-world deployment, and why most demonstrations fail outside controlled environments A pragmatic roadmap for robotics adoption, from simple tasks today to more complex industrial automation over the next decade Where Torque AGI fits in the stack as a modular layer that translates AI models into actionable robotic capabilities The importance of interpretability, safety, and measurable performance when deploying AI into physical systems The core technical bottleneck in robotics today: bridging deep learning with real-world physics and constraints Why industrial robotics will see massive value creation in the next 5 to 10 years, while humanoids remain further out A contrarian take on general-purpose systems: general AI will matter more than general-purpose robots Where the industry is overhyping progress, especially around humanoid demos, and what is actually working today Why AI-driven upgrades to existing robots could unlock 10x to 40x increases in productivity without new hardware How to stay disciplined as a founder in a hype-driven market by focusing on real customer outcomes instead of funding cycles What a successful deployment looks like, from quick demos to full operational integration in messy real-world environments Learn more about TorqueAGI: LinkedIn | Twitter | Website Connect with Ash Saxena: LinkedIn | Stanford Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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