Liquid State Machines (LSMs) are a type of recurrent neural network (RNN) that are particularly powerful for handling temporal data and dynamically evolving information. They are designed to leverage the rich dynamics of complex, nonlinear systems to process time-series data in a way that more closely mimics how the human brain processes sensory inputs…

Morphogenesis refers to the process by which organisms develop their shape and structure through self-organizing mechanisms. In biology, this concept explains how complex forms arise from relatively simple rules and interactions at the cellular level, often without the need for a central controller. The idea of applying morphogenesis to robotics is a transformative approach…

Spiking Neural Networks (SNNs) represent a significant leap forward in the development of neuromorphic computing, a paradigm that attempts to mimic the structure and function of the human brain. Unlike traditional artificial neural networks (ANNs), which process information in a continuous manner, SNNs process data in the form of discrete spikes, much like how…

Predictive coding is a computational theory of brain function that has gained significant attention in neuroscience, artificial intelligence (AI), and robotics. It posits that the brain (and similarly, AI systems) continuously makes predictions about incoming sensory data and updates its models based on discrepancies, or prediction errors, between expected and actual inputs. This mechanism…

Event-based vision systems are a breakthrough in sensory technology that mimic the way biological vision works, offering unique advantages over traditional frame-based cameras. Unlike conventional cameras, which capture entire frames at fixed time intervals, event-based cameras only capture changes in the scene, providing high temporal resolution and low latency. This makes them particularly well-suited…

The field of neuromorphic computing is inspired by the brain’s architecture and the way biological neural systems process and respond to sensory input. Neuromorphic sensors are designed to mimic the sensory systems found in nature—such as the human sense of sight, touch, and hearing—by leveraging bio-inspired circuits and algorithms. These sensors go beyond traditional…

Morphological computation refers to the idea that the physical structure (or morphology) of a system—such as a robot—can be used to offload some of the computational processes typically handled by its brain (central processor). This approach emphasizes the role of a robot’s body and its interaction with the environment in performing tasks. Instead of…

Capsule endoscopy is a revolutionary medical procedure that allows doctors to visualize the inside of a patient’s gastrointestinal tract without the need for traditional, invasive procedures like colonoscopies or upper endoscopies. This technology utilizes a small, pill-sized capsule equipped with a camera and other sensors that the patient swallows, allowing it to capture images…

Hyperdimensional Computing (HDC) is an emerging paradigm in computation that leverages the power of high-dimensional spaces (often with dimensions in the thousands or millions) to perform tasks like pattern recognition, associative memory, and data classification in a fundamentally new way. It’s inspired by how the human brain processes information using vast interconnected networks of…

Brain-Computer Interfaces (BCIs) are at the cutting edge of neuroscience and robotics, enabling direct communication between the human brain and external devices like computers, robotic limbs, and prosthetics. The integration of Artificial Intelligence (AI) into BCIs, particularly in robotics, promises to create a new era of interaction, where human intentions can be seamlessly translated…