Machine Minds

Humanoid robots are dancing, backflipping, and going viral. But are they ready to do real work? Theo Nash, founder and CEO of Mundane, joins Greg to challenge the hype cycle and refocus the conversation on what robots are actually for: eliminating dull, dirty, and dangerous work while amplifying human capability. From growing up around London auto garages to studying at Stanford and building teams across Palo Alto, Shenzhen, and Vancouver, Theo shares how his path shaped a mission centered on safety, embodiment, and human–robot collaboration. Mundane is not chasing flashy demos. Instead, the team is rebuilding the robotics stack from first principles, with a bold bet on telepresence, tactile sensing, and intuitive control systems that feel less like a video game and more like becoming the robot. This is a deep dive into embodiment, reliability, vertical integration, and why scaling too fast could be the biggest mistake in robotics today. In this conversation, Greg and Theo explore: If you are building physical AI, deploying robots in the field, or thinking about the future of human labor in an automated world, this episode is a thoughtful and ambitious look at what it will actually take to make robots useful at scale. Connect with Theo Nash: https://www.linkedin.com/in/theo-nash/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

What happens when a neuroscientist stops asking why the brain works the way it does and starts building his own version in silicon? Sam Fok, co-founder and CEO of femtoAI, joins Greg to explore the journey from studying neurons to designing ultra efficient AI chips for real world devices. Growing up in a household of scientists, Sam was drawn early to questions about intelligence and consciousness. That curiosity eventually led him from neuroscience labs to Stanford’s Brains in Silicon Lab and into the world of neuromorphic engineering. Today, femtoAI is building brain inspired hardware and software that brings AI out of massive data centers and into everyday products such as wearables, appliances, robotics, and consumer electronics. The goal is simple but ambitious: make AI run efficiently in the real world without straining power grids, supply chains, and balance sheets. Greg and Sam dive into the technical, commercial, and personal pivots required to turn deep research into a scalable company, including the hard decision to rebuild their core platform from the ground up. Highlights: If you are building AI powered hardware, deploying robots, or thinking about how to bring intelligence out of the cloud and into physical products, this conversation offers a grounded look at what it really takes to make AI usable, efficient, and scalable in the real world. Learn more about femtoAI: https://femto.ai/ Developer portal: https://developer.femto.ai/ Connect with Sam Fok: https://www.linkedin.com/in/sam-fok/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

From aerospace engineering to tactile sensing and physical AI, Jennifer Kwiatkowski’s path into robotics was driven by a simple but powerful motivation: taking math and physics off the whiteboard and making them work in the real world. Now an AI Specialist at Robotiq, Jennifer works at the intersection of hardware, software, and customer reality. In this conversation, she joins Greg to unpack what it actually takes to deploy robots that deliver ROI, why integration is often harder than the robot itself, and how the industry can avoid getting lost in hype cycles. Jennifer brings a research background in robotic manipulation and tactile sensing, along with firsthand experience navigating the fragile complexity of physical systems. Her perspective cuts through buzzwords and focuses on what matters: reliability, safety, usability, and long term value for customers. In this conversation, Greg and Jennifer explore: For founders, engineers, and operators building physical AI systems, this episode offers a grounded look at what it takes to move from prototype to production, and from hype to durable impact. Learn more about Robotiq: https://robotiq.com/ Connect with Jennifer Kwiatkowski on LinkedIn: https://www.linkedin.com/in/jenniferkwiatkowski/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

As robots move out of cages and into shared human environments, safety is no longer just about stopping motion. It is about enabling systems to keep moving productively without increasing risk. 3Laws Robotics is tackling one of the hardest problems in autonomy: how to guarantee safety while machines remain in motion. Andrew Singletary, co-founder and CEO, and Amir Sharif, COO of 3Laws Robotics, join Greg to unpack how a decade of academic research in safety critical control evolved into a commercial platform for dynamic safety across robotics, vehicles, and autonomous systems. From warehouse robots and mobile manipulators to aircraft and automobiles, their work aims to make autonomy scalable, certifiable, and trusted in the real world. Andrew traces his path from high school robotics competitions to nuclear engineering at Georgia Tech, a PhD at Caltech, and ultimately founding 3Laws to productize safety technology that companies repeatedly asked him to integrate. Amir brings the operator’s lens shaped by multiple startups and exits, focusing on product discipline, execution, and building an organization that values getting it right over being right. Together, they explore what it actually takes to move beyond academic proofs into functional safety that survives broken sensors, real world uncertainty, and regulatory scrutiny. Highlights: For founders, operators, and engineers building robots that must operate alongside people, this conversation offers a grounded look at how safety, productivity, and autonomy intersect and why the future of robotics depends on systems that can move intelligently, not just stop. Learn more about 3Laws Robotics: https://3laws.io Connect with Andrew Singletary on Linkedin: https://www.linkedin.com/in/andrewsingletary/ Connect with Amir Sharif on Linkedin: https://www.linkedin.com/in/asharif/ Connect with Greg Toroosian on Linkedin: https://www.linkedin.com/in/gregtoroosian

From academic breakthroughs in legged locomotion to building a horizontal AI platform for millions of robots, Flexion Robotics is taking on one of the hardest problems in the field: how to make robots learn, adapt, and scale in the real world. Nikita Rudin, co-founder and CEO of Flexion Robotics, joins Greg to share his journey from growing up in Switzerland with dreams of space exploration, to pioneering reinforcement learning for robots during his PhD, to helping shape NVIDIA’s simulation tools, and ultimately to founding a company aimed at becoming the “brain” behind general purpose robots. Nikita brings a rare perspective that spans deep research, real-world demos, and early-stage company building. He explains why hand-engineered behaviors and teleoperation do not scale, how reinforcement learning and simulation unlock robustness, and what it really takes to move robotics from impressive demos to economically viable deployments. In this conversation, Greg and Nikita explore: If you are building robots, investing in them, or trying to understand what it will take to move from research breakthroughs to real-world impact, this episode offers a grounded, deeply technical, and forward-looking view of where robotics is headed. Learn more about Flexion Robotics: https://flexion.ai Follow Flexion Robotics on LinkedIn and X for updates and technical insights Connect with Nikita Rudin on LinkedIn: https://www.linkedin.com/in/nikita-rudin Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian

From gigabytes of robot telemetry per minute to natural language search across multimodal data, Alloy is tackling one of the most underappreciated bottlenecks in robotics: making sense of what robots are actually doing in the real world. Joe Harris, founder of Alloy, joins Greg to unpack how his background in electrical engineering, machine learning, and growth teams shaped a product that helps robotics companies move faster, ship more reliably, and avoid rebuilding the same internal tooling over and over again. What started as frustration with inaccessible data and slow feedback loops has become a platform designed to turn robot data into a shared, searchable source of truth across engineering, validation, and commercial teams. The conversation dives deep into why replay tools break down at scale, how modern LLMs are changing what’s possible with robotics telemetry, and why deciding what not to build is one of the most important skills for early-stage founders. Highlights: If you are building robots, deploying them at scale, or thinking about the unseen infrastructure required to make robotics reliable in the real world, this episode offers a candid and deeply technical look at what it takes to turn raw robot data into real-world progress. Learn more about Alloy: www.usealloy.ai Connect with Joe Harris: https://x.com/_joe_harris_ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian

Manufacturing has long been the bottleneck between imagination and reality. From aerospace to automotive, complex physical products still take years to tool, validate, and produce. Machina Labs is working to change that equation by turning factories into flexible, software-driven systems that can build almost anything, anywhere. Edward Mehr, co-founder and CEO of Machina Labs, joins Greg to unpack his journey from early software obsessions to SpaceX, and ultimately to founding a company focused on rethinking how the world makes metal parts. Drawing from hands-on experience across software, robotics, and aerospace manufacturing, Edward shares why factories themselves are the real product, and how breaking the link between tooling and design unlocks speed, resilience, and creativity. The conversation explores how Machina Labs’ robotic “Robocraftsman” systems combine dexterity, AI-driven learning, and modular deployment to form metal without molds or dies. The result is manufacturing that adapts as fast as software, enabling rapid iteration, distributed production, and entirely new business models. Highlights from the conversation include: If you are building hardware, scaling robotics, or rethinking how physical products get made, this episode offers a deep look at what it takes to bring software-speed thinking into the world of atoms. Learn more about Machina Labs: https://machinalabs.ai/ Machina Labs Advances Custom Automotive Manufacturing with AI and Robotics: https://machinalabs.ai/resources/machina-labs-advances-custom-automotive-manufacturing-with-ai-and-robotics Strategic Development Fund Announces Investment and Initial Agreement with Machina Labs: https://machinalabs.ai/resources/uae-strategic-development-fund-announces-investment-and-initial-partnership-with-machina-labs Connect with Edward Mehr on LinkedIn: https://www.linkedin.com/in/edward-mehr/

Venture capital looks glamorous from the outside, but the reality is far more nuanced. From surviving market cycles to backing founders through years of uncertainty, long-term success in venture comes down to judgment, grit, and pattern recognition earned the hard way. Peter Harris, Partner at University Growth Fund, brings a rare perspective shaped by nearly two decades in venture investing, student-led fund models, and firsthand experience navigating both booms and downturns in technology markets . Peter’s path into venture capital started early, influenced by entrepreneurship, real estate investing, and a shift from wanting to be an engineer to seeing business itself as a tool for solving problems at scale. After helping rebuild and operate one of the largest student-run venture funds in the country, he went on to co-found University Growth Fund, a diversified Series A and beyond firm with a mission that blends strong returns, student development, and economic impact. The conversation spans what makes founders investable beyond pitch decks, why fundraising ability is often underestimated as a CEO skill, and how venture dynamics change when markets tighten. Peter also shares how AI is rapidly reshaping creation, distribution, and labor, and why ownership of assets may matter more than ever in the decade ahead. Topics covered include: For founders, operators, and anyone trying to understand how venture capital is evolving in an AI-driven world, this episode offers a grounded and experience-backed look at what really matters when building companies that last. Connect with Peter Harris on LinkedIn: https://www.linkedin.com/in/vcpete/ Learn more about University Growth Fund: https://www.ugrowthfund.com/ Listen to Peter’s podcast, VC.fm: https://vc.fm/ Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/

Robotics does not stall because the ideas are bad. It stalls because the underlying infrastructure is missing. Adrian Macneil, co founder and CEO of Foxglove, has spent his career inside the systems that power some of the most ambitious autonomous technologies in the world, and he believes the next leap in robotics will not come from a single breakthrough robot, but from making robotics development radically easier for everyone. Adrian’s path spans early work in payments and crypto, a formative chapter at Coinbase, and several pivotal years at Cruise during the early rise of self driving cars. At Cruise, he saw firsthand how much bespoke infrastructure was required to build, debug, and scale autonomy and how every leading AV company was quietly reinventing the same internal tooling. That realization became the foundation for Foxglove: a data and visualization platform designed to give robotics teams the same off the shelf leverage that software startups take for granted. In this conversation, Greg and Adrian unpack: If you care about the future of robotics, autonomy, and physical AI, and want to understand what actually needs to change for the industry to scale, this episode is a grounded and deeply informed look at the infrastructure beneath the hype. Learn more about Foxglove: https://foxglove.dev Connect with Adrian Macneil on LinkedIn: https://www.linkedin.com/in/adrianmacneil Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian

Robotics doesn’t fail in the field because of hardware alone—it fails when humans can’t understand, trust, or effectively work with the systems they’re given. Shakir Dzheyranov, founder and CEO of HelloRobo, has built his company around that reality. With a background spanning visual arts, motion design, and product leadership at brands like Nike, Shakir brings a rare design-first lens to robotics and automation. After years in traditional design and marketing, he made a deliberate pivot into product design—drawn by the ability to tie design decisions directly to real user problems, business outcomes, and measurable impact. That shift ultimately led him to robotics, where he saw a massive gap between technical capability and human usability. HelloRobo now operates as a specialized product design partner for robotics and automation companies, helping them build market-ready interfaces for robot operations, fleet management, and human–machine collaboration. Rather than chasing flashy MVPs or over-designed “vision concepts,” Shakir and his team focus on interfaces that can actually ship, scale, and be adopted by operators in the real world. In this conversation, Greg and Shakir dive into: Open RoboticsBedrock Roboticsembrace chaosmarket-ready softwareFor founders building robotic systems, leaders scaling hardware companies, or anyone thinking about how humans actually interact with autonomous machines, this episode is a reminder that great robotics isn’t just engineered—it’s designed. Learn more about HelloRobo: https://hellorobo.co Connect with Shakir Dzheyranov on LinkedIn: https://www.linkedin.com/in/shakir-works Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian

In this episode of Machine Minds, we step beyond today’s transformer-dominated AI landscape and into a deeper conversation about what’s missing on the path to truly autonomous, long-horizon intelligence. Jacob Buckman, co-founder and CEO of Manifest AI, joins Greg to explore why current AI systems struggle with long-term reasoning, persistent memory, and extended task execution—and what it will take to unlock the next paradigm. Jacob’s journey into AI began early, fueled by science fiction, programming, and a fascination with building systems that could do meaningful work autonomously. From studying and conducting research at Carnegie Mellon to working at Google Brain, he watched deep learning unify once-fragmented AI subfields—vision, language, speech—under a single scalable framework. That unification shaped his conviction that the next breakthrough wouldn’t come from incremental tuning, but from rethinking a fundamental architectural bottleneck. At Manifest AI, Jacob and his team are tackling what they believe is the missing piece: scalable long-context intelligence. Their work centers on replacing transformer attention with a new family of architectures called retention models, designed to compress and retain relevant information over time—rather than repeatedly replaying massive histories. The goal: AI systems that can reason, learn, and work continuously over hours, days, or longer. In this conversation, Greg and Jacob explore: retention architecturescompressIf you’re building AI systems, researching foundations of intelligence, or trying to understand what comes after today’s models, this episode offers a rare, deeply reasoned look at where the field may be heading—and why architectural simplicity could unlock far more than brute force scale. Learn more about Manifest AI: https://manifestai.com Explore the open-source retention models: pip install retention Connect with Jacob Buckman on LinkedIn: https://www.linkedin.com/in/jacobbuckman Connect with Greg Toroosian on Linkedin: https://www.linkedin.com/in/gregtoroosian

In this episode of Machine Minds, we dive into one of the most overlooked choke points in logistics: the loading dock. Chris Smith, founder and CEO of Slip Robotics, joins Greg to unpack why loading and unloading trucks remains one of the most manual, time-consuming processes in modern supply chains—and how Slip is transforming it with autonomous, high-payload mobile robots. Chris brings a rare blend of firsthand operator insight and deep robotics experience. From continuous improvement roles at Cummins, to factory-scale automation at Tesla, to building heavy-payload robots at a previous startup, his career repeatedly exposed the same inefficiency: trucks spending hours being loaded and unloaded for trips that last minutes. Slip Robotics was born from the realization that this problem wasn’t unsolved because it was hard—it was unsolved because no one had redesigned the workflow end-to-end. Slip’s solution is deceptively simple: a large, flat autonomous robot that becomes the staging lane, drives directly into trailers, stays with the freight during transport, and unloads autonomously on the other side. The result is five-minute loads, five-minute unloads, reduced labor, faster throughput, and dramatically improved dock utilization—without modifying trailers or docks. In this conversation, Greg and Chris explore: 12,000-pound payloadsRobotics-as-a-Service (RaaS)“rapidly deploying elegantly simple solutions”If you’re building robots, deploying automation, or thinking about how physical systems actually scale in real-world environments, this episode offers a clear-eyed look at how simplicity, speed, and workflow-first thinking can unlock massive value. Learn more about Slip Robotics: https://sliprobotics.com Connect with Chris Smith on LinkedIn: https://www.linkedin.com/in/christopher-r-smith Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian

In this episode of Machine Minds, we look at how physical intelligence—the fusion of robotics, automation, and software—can reshape one of society’s most strained systems: healthcare. Director of Software Engineering Nicholas Kirsch joins Greg to break down why hospital pharmacies are essentially “mini warehouses,” how automation is already quietly at work behind the scenes, and what it will take to reach the vision of a fully autonomous pharmacy. Nicholas brings a rare dual perspective: a mechanical engineer turned software leader who spent years in Pittsburgh’s startup ecosystem building mobile manipulation systems, AMRs, and government-funded robotics programs before shifting into healthcare tech. His experience—from garage-stage startups to acquisitions and rebrands—gives him a clear lens on what it takes to scale robots from impressive demos to mission-critical reliability. At Omnicell, he now helps drive software for medication-picking systems, IV-compounding robots, and the next wave of automation designed to return pharmacists and clinicians to the work they trained for: caring for patients. In this conversation, Greg and Nicholas explore: autonomous pharmacyFor anyone building automation in regulated environments—or simply trying to understand how robotics can meaningfully improve patient care—this episode offers a grounded, insightful look at the future of healthcare efficiency. Connect with Nicholas on Linkedin: https://www.linkedin.com/in/nicholaskirsch Connect with Greg on Linkedin: https://www.linkedin.com/in/gregtoroosian

In this episode of Machine Minds, we explore what it really takes to build the human infrastructure behind the coming wave of robots. CEO and co-founder Richard Petrazzini joins Greg to unpack how “robotic workforce enablement” can make or break uptime, customer trust, and the long-term success of robotics deployments—especially as robots leave cages, connect to the cloud, and move into human environments. Richard brings an unusually layered background to robotics: he’s a third-generation biochemist who grew up watching labs evolve from manual rabbit and frog testing to fully automated, 10,000-test-per-day facilities. That firsthand view of how healthcare automated over decades now informs how he thinks about robotics support, standards, and scale. After building one of Argentina’s largest labs and co-founding a successful software company, he spent two years doing nothing but researching robotics before launching Robotic Crew, a nearshore “human in the loop” partner for robot fleets. In this conversation, Greg and Richard get into: Robotic CrewIf you’re deploying robots, building them, or thinking about how to support a growing fleet without burning out your core team, this episode is a deep dive into the future of robotic workforce enablement—and the humans who will keep that future running. Connect with Richard on Linkedin: https://www.linkedin.com/in/rpetrazzini Connect with Greg on Linkedin: https://www.linkedin.com/in/gregtoroosian/

In this episode of Machine Minds, we look at what really happens when hardware innovation meets business strategy in robotics. Director of Business Development Milt Walker joins Greg to unpack how manufacturers, startups, and ecosystem players can scale robotics responsibly—without getting stuck in proof-of-concept purgatory or pretending they’re “just” software companies. From functional safety to workforce gaps and reshoring, Milt explores the forces reshaping how robots get built, deployed, and trusted in the real world. Milt brings a rare blend of hands-on engineering, ecosystem building, and strategic thinking. From early days fixing XT and 386 machines in a small-town computer shop, through field roles and leadership at Intel and Sick, to helping seed the Atlanta robotics community with RoboGeorgia, he’s consistently sat at the intersection of technology and partnerships. Now at Next Cobot, he focuses on giving robot builders the safety-critical and control platforms they need so they can innovate faster on what makes their systems unique. In this conversation, Greg and Milt explore: configurationIf you’re building robots, selling them, or betting your operations on them, this episode will sharpen how you think about partners, platforms, and the long game of automation. Connect with Milt Walker on Linkedin: https://www.linkedin.com/in/mwalkeriii/ Connect with Greg Toroosian on Linkedin: https://www.linkedin.com/in/gregtoroosian/ Chapters: 2:34 Essential Technology 3:31 Early Career Insights 4:42 Robotics Passion 7:38 Business Development Path 9:58 Atlanta's Robotics Ecosystem 12:37 Joining NexCobot 15:19 Partnership Strategies 16:14 Market Opportunities 18:33 Barriers to Adoption 21:35 Finding the Right Partners 24:15 Successful Collaborations 27:07 Customization vs. Scalability 30:44 Technological Trends 37:07 Standards and Regulations 45:41 Moonshot Ideas 47:06 Advice for Aspiring Professionals 49:21 Reflections on Career Growth

What does it take to guide a robotics startup from a napkin sketch to a $775 million exit? Oliver Mitchell, a venture capital partner at FF Venture Capital and author of "A Startup Field Guide in the Age of Robotics and AI" returns to Machine Minds to share hard-won lessons from the trenches of deep tech investing. From the dramatic rise and fall of Webvan to the triumph of Kiva Systems (now Amazon Robotics), Oliver reveals why product-market fit isn't found in the lab - it's discovered in relentless customer conversations. We explore the pivotal mistakes founders make, why pivoting isn't failure but strategy, and how the right cap table can be the difference between scaling and stalling out. Highlights: Oliver's book "A Startup Field Guide in the Age of Robotics and AI" is available on Amazon or at routledge.com (20% off with discount code 25ESA3 - valid 1 July 2025 - 31 December 2025) Connect with Oliver Mitchell on Linkedin: https://www.linkedin.com/in/oliverbmitchell/ Connect with Greg on Linkedin: https://www.linkedin.com/in/gregtoroosian/

Construction is one of the world’s most complex, risk-filled, and operationally fragmented industries — and also one of the last to benefit from automation. At Raise Robotics, CTO Rishabh Aggarwal is helping change that. From capturing diesel soot to turn into ink, to designing CubeSats at NASA, to building autonomous harvesting robots in ag-tech, Rishabh’s journey has always been about one thing: building real technology that solves real problems.  In this episode, he breaks down how Raise Robotics is building a multi-use, autonomous construction robot capable of performing high-precision tasks on the edge of skyscrapers — layout marking, drilling, inspection, and more — all with 1/16-inch accuracy on chaotic, unpredictable job sites.  We explore the technical challenges, the industry dynamics, the hiring realities of early-stage robotics, and the future of “physical AI” as robotics collides with deep learning at industrial scale. ⸻ Highlights •From building off-road race cars to capturing diesel pollution: Rishabh’s early startup experience involved inventing a device that trapped generator soot and converted it into ink — a hands-on lesson in iterative engineering and impact-driven design.  •Learning hard lessons in hardware: While building agricultural robots, a battery fire caused a full site evacuation — shaping Rishabh’s philosophy that startups should buy first, innovate later until product-market fit is clear.  •Why construction needed robotics yesterday: Multi-million-dollar rework, misaligned facades, and error-prone layout marking inspired Raise Robotics to automate tasks that require extreme accuracy — tasks humans aren’t well-suited for on 2,000-foot floors.  •Inside Raise’s autonomous platform: A robot on wheels equipped with long-reach arms, tool-changing capabilities, and precise localization — delivering layout marking, drilling, inspection, and more, while generating detailed QC reports for contractors.  •The toughest technical challenge: Designing a robotic arm that remains rock-solid on the literal edge of a building while working with sub-inch tolerance — in rain, dust, debris, and unpredictable environments.  •Building a high-performing robotics team: Rishabh emphasizes hiring for intent, attitude, and intrinsic motivation, not just technical skill — and why people from big tech increasingly seek startup impact.  •Where robotics is headed next: The rise of “physical AI,” the explosion of better sensors and compute, and the coming wave of human-robot collaboration that replaces cages with perception-driven safety.  •Long-term vision: A multi-industry platform that moves beyond construction into manufacturing, oil & gas, and high-risk industrial environments — wherever a precise, ruggedized robotic teammate is needed.  ⸻ Learn more about Raise Robotics: https://raiserobotics.ai/ Connect with Rishabh Aggarwal: https://www.linkedin.com/in/rish-creator/ Follow the Raise Robotics team on LinkedIn (they post regular updates): https://www.linkedin.com/company/raise-robotics/ Connect with Greg: https://www.linkedin.com/in/gregtoroosian/

From satellite missions and drone startups to international development work in Haiti, Peter Haas has carved one of the most unconventional and globally minded paths in robotics. Today, he’s combining decades of experience across academia, entrepreneurship, government, and humanitarian work to answer a pivotal question: How can robotics and AI help the half of the world living on less than $5.50 a day? In this episode, Peter shares his journey - from working on NASA’s Gravity Probe B, to co-founding a drone company, to running robotics research at Brown University, to helping grow the Massachusetts robotics ecosystem. Now, as he embarks on a new chapter consulting from a sailboat in the Caribbean, Peter reveals what’s next for robotics, where the biggest opportunities lie, and why building for real-world problems matters more than ever. Highlights: - A career shaped by exploration: Peter’s early days ranged from being a park ranger and attempting a novel in Paris to working on Gravity Probe B, where robot-made gyroscopes sparked his fascination with precision hardware.  - International development meets robotics: A decade in Haiti showed Peter the limitations of traditional manufacturing models — inspiring his mission to use robotics to uplift underserved populations globally.  - The spark moment: Riding in an early Google self-driving car at TED convinced Peter to fully transition back into tech, eventually co-founding a drone company and entering the robotics ecosystem.  - From research to ecosystem building: Peter shares insights from leading Brown University’s Humanities-Centric Robotics Initiative and helping scale Massachusetts’ 500-company robotics cluster.  What’s exciting him now: - Lightweight, non-transformer models (Liquid AI, etc.) enabling powerful AI on resource-constrained robots. - Better teleoperation interfaces and the rise of “robot call centers” that decouple physical labor from geography.  - Ethical & technical challenges: Why cybersecurity is a looming crisis in robotics, and how insecure firmware and exposed ROS systems create real-world risk.  Lessons from the field: - Failure: building a $50K LiDAR drone just before DJI commoditized photogrammetry — and how that mirrors today’s AI landscape. - Success: why startups like SIMPL Automation win by partnering early and commercializing quickly. - Advice for builders & graduates: - Solve real problems for real customers — not abstract robotics challenges. - The integrator gap is massive: new grads with hands-on skills can build careers serving manufacturers who desperately need automation.  Connect with Greg: https://www.linkedin.com/in/gregtoroosian/ Connect with Peter: https://www.linkedin.com/in/peterhaas-robotics/

From retrofitting automation into existing warehouses to redefining how fast robotics can be deployed, SIMPL Automation is pioneering a more flexible, less disruptive path toward warehouse transformation. In this episode, Ayman Labib, co-founder and CEO of SIMPL Automation, shares how his 25+ years in manufacturing and integration led him to build a company that’s challenging the traditional timelines, costs, and risks of warehouse automation. We explore how adaptive ASRS (Automated Storage and Retrieval Systems) can bolt onto existing racking, why simplicity and speed are key to driving adoption, and how his team is bringing “Lego-like” modularity and 4G-enabled plug-and-play design into the world of logistics technology. Highlights: adaptive ASRSde-risk automationextend the life of their facilitiesfocus, speed, and incremental improvementfuture of warehouse automationcommercial viability before perfectionLearn more about Simpl Automation: https://simplautomation.com (Simpl without the “e”) More about Ayman Labib: https://www.linkedin.com/in/ayman-l-45a3ba4/ Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

Florian shares his journey from cryptography researcher to big tech product leader — at companies like Microsoft, Adobe, and Facebook — and how that experience inspired him to tackle one of robotics’ biggest challenges: making robots work together seamlessly across diverse fleets and environments. From interoperability and observability to performance and safety, this episode explores how InOrbit.AI is building the connective tissue of the robotics world — a “Google Translate for robots” that enables smarter, safer, and more efficient automation at scale. Highlights: - Florian’s journey from research in cryptography to leadership roles in major tech companies, and what inspired him to build something from the ground up. - Explaining robot orchestration — helping organizations connect, monitor, and manage fleets of diverse robots across the world. - Florian breaks down InOrbit’s approach Observability – Know what’s happening Operation – Manage and act on it Orchestration – Coordinate across systems Optimization – Continuously improve performance - Letting robots “speak” any language rather than forcing one universal standard. - Florian’s philosophy of continuous improvement — for both humans and machines — and how AI powers real-time insights in robotics. Learn more about InOrbit.AI: https://www.inorbit.ai/ Connect with Florian Pestoni: https://www.linkedin.com/in/florianpestoni/ Connect with me: https://www.linkedin.com/in/gregtoroosian/