Hardware Podcasts

End-Of-Line Automation With Ai: Inside Rapid Robotics Revolution

Over the Air · 14 Nov 2024 · 32m

AI in practice: one real use of AI described

What this episode covers

Kim, CEO of Rapid Robotics, explains how the company pivoted from custom manufacturing automation to end-of-line boxing and palletizing using generative AI to solve labor shortages and handle high SKU variability. She details the development of Rapid ID, which allows robots to identify and handle diverse objects without extensive programming, contrasting this with the limitations of traditional robotics in brownfield environments. Kim also shares her background in the toy industry at Hasbro and how that experience informs her approach to scaling the company and supporting US manufacturing reshoring.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

Manufacturingwithin a minute or 2 minutes

The team implemented generative AI and machine learning to allow robots to self-identify objects and determine handling strategies within minutes, eliminating the need for traditional training or programming for new SKUs.

“we are using generative AI. We are using still some traditional machine learning training. Uh, so that the robot can begin to understand what is that object, how do I handle that object? Um, but then getting to a place where, you know, it can see the object and within a minute or 2 minutes, it just knows what is that object and what do I do with it? Um, so really no training. Required.”

Speaker 2 · Hear it at 6:57

Most relevant to

companies scaling up

Topics

Mentioned

Companies
Rapid Robotics, Hasbro, Autodesk
Products
Rapid ID, Aeropress, Transformers
Also
Modex

Related episodes from other shows

Other shows on the same ground, closest first.

  • The Manufacturing Executive · 30m

    Intelligent Robots and the Warehouse of the Future

    Michael Perry, Vice President of Marketing at Dexterity, discusses how AI-enabled robots are transforming warehouse operations by handling variability that traditional automation cannot. He details Dexterity's platform, which integrates vision and touch to allow robots to pick, pack, and palletize mixed-SKU goods in existing 'brownfield' facilities without extensive infrastructure changes. Perry highlights a specific success story involving a bread fulfillment center where one robot managed over 10,000 SKUs, including deformable items like tortillas and loaves of bread, while also explaining the future of collaborative robot teams.

    Robotics & autonomyScaling production
    7 chapters

  • The Manufacturing Executive · 25m

    Using Robots in High-Mix, Low-Volume Environments w/ Josh Gruenstein

    Josh Gruenstein, co-founder and CEO of Tutor Intelligence, explains how his MIT spinout uses AI and machine learning to automate high-mix, low-volume manufacturing environments, such as co-packers and 3PLs, which were previously considered too variable for robotics. He details how their robots eliminate the need for specialized programming by interpreting build sheets and specifications directly, allowing facilities with no automation engineers to adopt automation. Gruenstein also describes Tutor Intelligence's 'Robot as a Service' model, which converts capital expenditures to operating expenses, reduces risk, and aligns vendor incentives with customer productivity through continuous software updates.

    Robotics & autonomyAI & machine learning
    6 chapters

  • Manufacturing Happy Hour · 50m

    173: Leveraging Robotics in an Unstructured World with Dexterity's Michael Patrick Perry

    Michael Patrick Perry, Dexterity’s VP of Marketing, discusses how the company has scaled from a small team to nearly 260 employees, moving from bread packing to full warehouse automation. He explains Dexterity’s software-first approach, which allows robots to handle complex, unstructured tasks like truck loading and palletizing by combining vision, force control, and planning. Perry highlights the democratization of robotics, enabling smaller companies to deploy flexible solutions quickly without massive capital expenditure, while also detailing how AI is used to create customized marketing experiences for enterprise clients.

    Robotics & autonomyAI & machine learning
    9 chapters

  • Manufacturing Happy Hour · 38m

    172: How To Stay Focused on Your Mission and Deliver Robotic Solutions at Scale with Rapid Robotics CEO & Co-Founder Jordan Kretchmer

    Jordan Kretchmer, CEO and Co-Founder of Rapid Robotics, explains his transition from MarTech to robotics and how his company is scaling robotic solutions to address the US labor shortage. He details Rapid Robotics's strategic refocus from heavy deployment services to robust computer vision and AI software, enabling robots to self-learn and adapt without programming. Kretchmer discusses how this shift allows for scalable, affordable automation that maintains profitability while keeping investors and customers aligned through transparency.

    Scaling productionAI & machine learning
    6 chapters

  • The Manufacturing Executive · 27m

    Moving From Generative to Physical AI on the Manufacturing Floor w/ Etienne Lacroix

    Etienne Lacroix, Founder and CEO of Vention, discusses the transition from generative AI to 'physical AI' on the manufacturing floor, defining it as injecting AI code into embodied systems like robots to achieve autonomy. He identifies bin picking and vision-guided robotics as the only two task categories currently ready for industrial deployment, citing specific metrics like 99.9% first-pick success rates and sub-two-year payback periods for two-shift operations. Lacroix contrasts these mature applications with the current limitations of Vision-Language-Action (VLA) models, which require excessive post-training hours, and highlights the operational challenges of non-deterministic robot movements.

    AI & machine learningRobotics & autonomy
    6 chapters

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by Over the Air. The episode itself belongs to its publisher.