Podcast Summary: Reimagining Robotics and Manufacturing—Gokul NA on Vision Intelligence and Universal Micro Factories

The Digital Executive Podcast | Ep 1104—August 26, 2025
Host: Brian (Coruzant Technologies)
Guest: Gokul NA, Co-founder of Syndler

Main Theme and Purpose

This episode explores the cutting-edge intersection of robotics, machine vision, and the future of manufacturing. Gokul NA shares his journey from National Instruments to founding Syndler, where his team is redefining “universal factories”—adaptive, intelligent manufacturing units drawing inspiration from neuroscience and human perception. The conversation centers on overcoming classic machine vision challenges, Syndler’s approach to robotics that mimic infant learning, and the promise of sustainable, decentralized production via microfactories.

Key Discussion Points & Insights

How Early Experience Shaped Vision for Syndler

[01:20–03:45]

• Exposure to Limitations in Machine Vision: Gokul worked on vision, RF, and embedded systems at National Instruments, tackling complex, unsolved customer problems across the globe.
  • “For every 10 problems that we attempt, only three problems we could commercially succeed with all the platforms that we had.” —Gokul [01:53]
• Critical Industry Insight: Industry-wide, even major players (Cognex, National Instruments) could only solve ~30% of machine vision problems, especially in automation requiring object manipulation.
• Learning from Failure: Rather than focusing on what did work, Gokul asked: Why was the failure rate so high, especially in tasks needing robot manipulation and object handling?
• Human vs. Machine Limitations: Cameras provide just visual input, but for high manipulation tasks, humans use a blend of vision, touch, and context—an approach Gokul’s team sought to emulate.

Solving “Unsolvable” Vision Challenges: Case Studies

[04:28–07:06]

• Consulting on Unsolved Problems: Gokul and his partner tackled over 30 persistent vision challenges after leaving National Instruments.
  • “We had to build [the camera] from scratch with the FPGA system.” —Gokul [05:56]
• Example Scenarios:
  • Bearing inspection: Counting and orienting pins obscured by grease—easy for a human, hard for machines.
  • Medical device assembly: Assembling intricate X-ray system components.
  • High-speed grain sorting: Identifying good/bad grains (or stones, glass) in free-fall at 5m/s within 56 microseconds—no commercial camera existed, so they built their own.
• Core Discovery: Across these use-cases, success required dynamic object manipulation—adapting to unknown variables rather than rigid pre-programming.
• Productization Thesis: “...there is a standard underlying principle which is solving all these problems, which means we could productize them.” —Gokul [06:42]
  • This formed the foundation for Syndler’s funding and technology stack.

Emulating Human Infants: The Breakthrough in Object Intelligence

[07:46–10:44]

• Beyond Conventional Vision Systems:
  • Traditional vision depends on object recognition and color analysis, then feeds this to a manipulator—a process prone to failure on unknown or variable objects.
  • “We don’t treat motion as an independent sensing capability for a vision system.” —Gokul [07:59]
• Human-Inspired Robotics:
  • Infants can interact with and manipulate unknown objects by touch, motion detection, and adaptive learning—without needing to know what an object is beforehand.
  • Key insight: “We don’t have to know the object prior to acting on that object.” —Gokul [08:44]
• Technical Breakthroughs:
  • Syndler’s system leverages real-time motion and contour detection—mirroring the way human neural networks process visual and tactile data, specifically referencing the retina’s ganglion cells.
  • “Your eyes’ ability to highlight only the things that move together is what helps you stitch an object together.” —Gokul [09:29]
  • Force feedback is dynamically calculated, just as a human instinctively adjusts grip, optimizing handling for fragile, unknown, or complex objects.

The Universal Microfactory and Sustainable, Decentralized Manufacturing

[11:32–14:40]

• Automation’s Rigidity Is Limiting:
  • “The rigidity that automation enforces...limits customers from reacting very quickly to customer needs.” —Gokul [11:34]
  • Traditional factories, designed for mass production, struggle to adapt to shifting or highly customized demands.
• Microfactory Concept:
  • Syndler is advancing “universal microfactories”—compact, decentralized, and highly adaptable manufacturing units.
  • Enables “franchise-style” manufacturing; smaller, more responsive, and able to continuously customize output.
    • “What McDonald’s has learned from Ford, Ford has failed to learn from McDonald’s...” —Gokul [13:11]
• Recycling & Resource Circularity:
  • Moving from mining raw materials to extracting value from waste (the “dustbin”)—made possible when robots handle the nuanced work of sorting and reclaiming materials.
  • “When you are able to build a system which is capable of applying that nuanced skill as much as a human...then you have a free effort available to extract material from your wastages.” —Gokul [12:45]
• Economic Efficiency:
  • Flexible, universal automation lowers both startup costs and waste; production lines can rapidly switch between different products without costly retooling or redesign.
  • “If I could produce all cars in the same line...you don’t have to look for hyperproduction… or create artificial market demand for it.” —Gokul [13:37]
• Core Vision:
  • Universal microfactories could change the scale and accessibility of manufacturing, making production more local, responsive, and sustainable.

Notable Quotes & Memorable Moments

• On Failure as a Learning Tool:
  • “Where are we failing the most instead of seeing where are we succeeding the most.” —Gokul [02:28]
• On Human-Like Robotics:
  • “A human being is capable of isolating an object out of [clutter], even though he doesn’t know what he’s actually picking.” —Gokul [08:18]
• On Changing the Manufacturing Paradigm:
  • “The ability to franchise your manufacturing is missing.” —Gokul [13:05]
• On Materials and Recycling:
  • “Why do we always look to mine the earth...rather than trying to mine that out of the dustbin?” —Gokul [12:27]

Timestamps for Important Segments

• 00:00–01:15: Intro, background on Gokul NA and Syndler’s vision.
• 01:20–03:45: Challenges in machine vision; why previous approaches failed.
• 04:28–07:06: Consulting on “unsolvable” problems; real-world examples and key insights.
• 07:46–10:44: Breakthroughs in mimicking human infant learning for robotics; motion and force feedback intelligence.
• 11:32–14:40: Decentralized, sustainable manufacturing and universal microfactories.
• 14:40–15:38: Closing thoughts, highlighting the transformative potential of universal microfactories.

Conclusion

This fast-paced episode distills how a neuroscience-inspired vision system and adaptable microfactory platforms could transform manufacturing—making automation more human-like, versatile, and sustainable. Gokul NA’s approach blurs the line between human learning and machine intelligence, aiming to unlock local, decentralized factories that flexibly and efficiently serve the emerging needs of a dynamic market.