Config Dynamics is proud to champion Self-Aware™ computing, a groundbreaking concept first envisioned and brought to life by our founder, Professor Henry Hoffmann.

Solving Complexity with Intelligence

Professor Hoffmann recognized a universal challenge in computing: how to navigate multiple, often conflicting, configuration choices without perfect knowledge of changing workloads. Even the most advanced systems were becoming increasingly complex, making it harder to optimize performance under all conditions.

He understood that complexity was ever increasing and that new approaches were needed that could dynamically reconcile the inevitable gap between imperfect hardware and software applications and the unpredictability of workloads in the instant. 

He wanted new techniques to be beyond classical feedback and be responsive to the growing capabilities of machine learning and AI, especially when being applied to diverse industrial processes and even AI itself. 

His vision? To empower systems—whether cutting-edge architectures or legacy setups—with the computational intelligence to:

• Understand and reason about their condition in real-time.
• Continually manage and optimize themselves dynamically.
• Use goals to manage actual complex conditions, not the otherwise impossible task of trying to build perfect systems or perfectly define every nuance of every workload at every moment.

A Transformative Leap 

Combining classical control theory with the emerging power of machine learning and AI, Professor Hoffmann developed a transformational approach. His seminal idea was to use design goals and the configuration space itself as First-Class Objects under software control, unlocking unprecedented performance from everything complex, from physical systems, like chips, to advanced applications in software. 

For the first time, it became possible to:

• Use machine learning to address complexity.
• Use control theory to manage dynamic processes.
• And have computational horsepower to have goals bridge the system and workload conditions.

A Recognized Breakthrough

In 2011, Scientific American named Self-Aware computing one of the “World-Changing Ideas: 10 New Technologies That Will Make A difference.”

Since then, Config’s underlying technology has been applied to dozens of applications across multiple hardware and software systems, from simple configuration conflict analysis and resolution to improving the performance/watt of supercomputers, with continual peer review by many of the most talented computer scientists and AI experts in the world. 

These innovations have flipped the script on configuration practices…from conventional static configuration practices that only anticipate expected outcomes, to now dynamic configuration to meet goals, responsive continually to each instant of the workload. 

One major Self-Aware™ application has spawned AdaptiveAI™, a new, never-before available generation of configurable AI training, inference and agents that can be manipulated with goals. 

Config Dynamics continues to innovate, pushing the boundaries of what’s possible in intelligent, self-optimizing systems. Join us as we redefine how the world thinks about managing complexity.

Future Directions

Here are just a few ideas we are pursuing for the near future:

• Self-Aware Digital Twin simulations for performance analysis of configuration spaces.
• Tools for building a Self-Aware system’s configuration space only using the original system design spec as a primary goal, AI to model many instances of the dynamic cycling of the workload and advanced AI code writing tools. 
• Collaboration to enable Self-Aware AI Chips that allow individual developers to use goals selection to better tailor chip configuration spaces for their specific application needs.
• Using AI to evolve best practices to meet goal selection needs, a new field of Goal Development Sciences, especially for complex, distributed system architectures and automated goal development.
• Security and privacy as quantifiable goals, managed alongside energy and latency, with special emphasis on financial transactions and industrial process control.
• Application of Self-Aware and AdaptiveAI computing technologies to the electrical grid to improve performance of transmission and distribution strategies for an energy-constrained generation system. Closer integration with AI data center control tools.