Machine Minds

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 ageThe founding story of Andromeda Robotics and how strict COVID lockdowns in Australia exposed the real-world impact of lonelinessWhy Abby was designed as a character, not a tool, and how Pixar-inspired design principles drive trust and adoptionThe overlooked challenge of social acceptance in robotics and why capability alone is not enough to succeed in human environmentsReal-world deployments of Abby in aged care facilities and what the team has learned from observing how people actually interact with robotsThe importance of personalization in human-robot interaction, from voice tuning to behavioral adaptation for individual usersWhy emotional intelligence and “social awareness” will be critical for all robots working alongside humans, even outside consumer settingsThe interdisciplinary nature of building social robots, combining engineering, animation, healthcare insight, and operationsHow Grace thinks about hiring, from early generalists to later specialists, and why mission alignment is the most important filterThe concept of “anti-selling” during hiring to attract people who truly want ownership and responsibility in a startup environmentUsing AI agents internally to accelerate iteration speed and rethink how teams build and operate in modern startupsThe broader responsibility of shaping the future of robotics and why who builds this technology will determine its impact on societyLearn more about Andromeda Robotics:Youtube: https://www.youtube.com/@AndromedaRoboticsWebsite: https://andromedarobotics.ai/LinkedIn: https://www.linkedin.com/company/andromedarobotics/posts/?feedView=allConnect 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/

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 RoboticsWhy quality inspection is still one of the most manual, inconsistent, and frustrating parts of manufacturingThe core insight behind Bucket: applying self-driving car vision systems to factory environmentsHow CAD-based simulation replaces months of data collection with minutes of synthetic training dataThe “sim-to-real” challenge and why perception in changing lighting and environments is harder than it looksWhy most vision systems fail in production and how Bucket is designed for real-world robustness from day oneLessons from early market assumptions, including why medical device manufacturing was not the right starting pointThe economics of inspection: balancing cost, speed, and accuracy across high-mix and high-volume environmentsWhat makes a strong customer fit, from ambiguous defect definitions to expensive rework caught too lateCommon objections from manufacturers burned by legacy vision systems and how simulation changes the equationWhy labor shortages and supply chain reshoring are accelerating demand for automated quality solutionsHiring for empathy in robotics and why understanding the end operator matters more than credentialsThe importance of engineers who ship, not just prototype, and why early adopters beat bleeding edge thinkersHard-earned hiring lessons, especially the need for teams willing to travel and work onsite with customersWhere robotics is overhyped today, especially around deployment at scale versus polished demosWhy lightweight, lower-cost robotic systems are unlocking a new wave of practical automationMatt’s view on the future of manufacturing: a hybrid human and robotic workforce rather than full autonomyFounder reality: why building a company can feel easier than operating autonomous vehicles, but far more isolatingThe long-term vision for Bucket Robotics as the “cloud computing moment” for manufacturing quality systemsMatt's LinkedIn: https://www.linkedin.com/in/matt-puchalski/Bucket's LinkedIn: https://www.linkedin.com/company/bucketrobotics/Matt's email: [email protected]'s Youtube: https://www.youtube.com/@Bucket_RoboticsConnect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/

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 machinesThe hidden reality of manufacturing, with nearly 90% of production still manual despite decades of automationThe core problem GrayMatter is solving, enabling robots to adapt to high variability in materials, environments, and processesWhy physical AI requires more than vision alone, and how multimodal sensing unlocks real world autonomyStarting with sanding as a strategic wedge, then expanding into grinding, painting, blasting, and inspection through transferable learningThe power of data, building one of the largest manufacturing datasets to train foundation models for materials and processesRobot scientists and domain specific AI agents that compress process optimization timelines from months to daysHow optimizing human, robot, and AI workflows can drive massive gains, including tripling throughput without adding robotsLessons from early deployment challenges, from consumables to real world variability, and how they shaped more intelligent systemsThe importance of an adoption playbook, and why deploying robotics successfully depends on process and people as much as technologyAriyan’s perspective on talent, why high agency and system level thinkers are the most valuable builders in the age of AIWhat is still missing in robotics today, and why domain specific intelligence layers are the next frontierA vision for the future, rapidly reconfigurable, fully autonomous factories that can adapt in real time to new products and global needsFor 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=allhttps://x.com/GrayMatterRobotConnect with Ariyan Kabir:https://x.com/ariyankabirhttps://www.linkedin.com/in/ariyankabir/Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/