What is Cybernetic Horticulture?

At the Cybernetic Horticulture Lab, our mission is to gain a deeper grasp of the nuanced aspects of nature, technology, and the connection between the two. In so far as technology exists as an artifice to augment human influence in the natural environment, we aim to blur levels of abstraction in both physical form and evocative states with the goal of understanding the connective qualities in technology that yield the power to deepen the human experience.

What is the GRS?

In the modern era of robotics, as we break unimaginable new ground in mechanical capability, the ever present need to understand and harness the human-robotic connection has never been more pointed than it is today. With a combined total of 60+ years of real world reinforcement learning, the Gesture Recognition System (GRS) is a groundbreaking intelligence solution that aims to fill the gap between human expression and robotics control frameworks by redefining what it means to have a "human in the loop".

To begin with, the GRS incorporates highly evolved sensory systems capturing a myriad of data points with a latency more in line with human processing speeds than anything ever seen in modern electronics. The optical capture system implements a stereo vision technology known as Elevated Yield Encoding Sensors. With a concurrent auto-centering rotational lensing system and reflexive ingress protection, the GRS is ready for anything that it might see in the real world.

Additionally, the GRS is equipped with a cutting edge binaural sound processing solution known as the Enhanced Audio Retrieval System that enriches both spatial awareness and language comprehension with extremely low latency. The GRS also takes advantage of the most advanced data transmission hardware infrastructure known to mankind, the Network Execution & Retrieval Viability Expeditor System. By harnessing the full advantages of Myelenic data transfer, unparalleled data speeds become attainable.

And at its core, the Modern Interpreted Neural Disambiguator is a vastly powerful neural network that allows for robust comprehension, as well as real-time deep learning and adaptive decision methods that unlock a level of generalized task based efficacy that has never been achieved before in agentic systems.

Finally, last but certainly not least, the GRS incorporates something that until now has never been considered in the context of a robotics workflow. This revolutionary idea has the power to reach new levels of empathic synchronicity that were once nothing more than a poorly conceived pipe dream. All internal and external processing systems are tied together via the Virtual Interpersonal Balanced Equalization Synchronizer, a triumph of modern innovation and the keystone of the GRS. This system correlates all observable and inferred data about details large and small, informing interpersonal status evaluations and augmenting responsive actions.

We are now breaching new territory as we explore these interactions between robotic systems and the intelligent systems used to control them. Putting forward an entirely new approach to interfacing with robotically controlled systems, we hope to produce deeply embedded connective frameworks with the power to blur the line between human and robotic interactions, and to re-shape how we think about modern robotics.