From Specialized Tools to Generalist Partners

By Dave Evans, CEO & Co-Founder, and Steve Ricketts, VP Business Development Robotics, Fictiv

Introduction: Robotics at an Inflection Point

For decades, robotics have been defined by specialization. Take industrial arms in automotive plants: massive, precise, and tireless, but programmed for a single task. Or the pick-and-place systems in electronics factories, moving circuit boards down the line with incredible speed but little adaptability.

But in 2025, we are seeing a tectonic shift. The convergence of AI foundation models, humanoid hardware, distributed supply chains, and advanced manufacturing platforms is transforming robots from specialized tools into generalist partners. This new era brings machines that can adapt, learn, and collaborate across tasks and industries.
The implications are profound. We are no longer asking, “What can robots replace?” We are instead exploring, “How can robots augment, adapt, and partner with humans to solve our toughest problems?”

From Narrow to Generalist Intelligence

The linchpin of this shift is artificial intelligence. Historically, each robotic application required task-specific programming. A robot that could weld could not assemble. A robot trained to sort fruit could not suddenly switch to packaging.

Now, thanks to breakthroughs in AI foundation models, robots can learn new skills without being reprogrammed from scratch. Nvidia’s Isaac GR00T N1 foundation model launched earlier this year and marked a watershed moment. This system gives robots a kind of “general intelligence” combining reflex-like responses for real-time tasks with more deliberate, strategic planning.

Companies like Boston Dynamics and Agility Robotics are already testing this model on humanoid platforms. What’s striking is not just the performance, but the adaptability. These robots don’t need bespoke coding for every movement; they learn patterns that can be transferred across contexts.

Consider Boston Dynamics’ Atlas robot. Once famous for its backflips, it has now achieved walking, grasping, and object manipulation through a single AI model, rather than multiple task-specific ones. This is a glimpse of a future where robots, like humans, can take lessons from one task and apply them to another.

The transition from narrow AI to generalist AI in robotics mirrors the evolution we’ve seen in large language models for communication. Where ChatGPT showed how AI could handle not one but thousands of conversational tasks, Isaac and Atlas are showing us how robots can transcend their niches to become multi-purpose partners.

The Robot Ballet: Orchestrating Coordination

Of course, individual adaptability is only one part of the equation. In real-world environments, productivity often depends on teams—whether teams of people or teams of machines.

That’s why the unveiling of RoboBallet, a system developed by University College London in partnership with Google DeepMind and Intrinsic, is so exciting. This AI-driven platform enables multiple robots to work together fluidly, choreographing movements to avoid collisions while maximizing throughput.

In controlled tests, eight robotic arms executed 40 distinct tasks with unprecedented efficiency. What once required sequential, step-by-step execution could now be handled in parallel. The gains are not just incremental—they’re exponential.

Imagine a manufacturing floor where robots assemble, inspect, and package simultaneously, adapting in real time to disruptions. Or a logistics hub where fleets of mobile robots coordinate like dancers, avoiding bottlenecks while accelerating fulfillment.

This speaks to a future where robotic collaboration mirrors human teamwork—dynamic, responsive, and far more than the sum of its parts.

Humanoids Enter the Mainstream

Source: https://www.forbes.com/sites/daveevans/2025/09/29/the-new-era-of-robotics-from-specialized-tools-to-generalist-partners/