Cognitive Machines

As an AI company, we transfer intelligence into machines – whether it’s hardware or another form of software. These AI applications are aimed at serving cognitive machines (machines that communicate, perceive, and act as human minds do) to enhance:

Learning Ability: to act automatically and receive signals from the assigned environment, make another action; update rewards and revise algorithms.
Robotics: simulation of dexterous robots utilizing foundational models with smarter and faster control algorithms.
Industrial Automation (IA): Vertical approach to empower industries by 5 layers of intelligence: Field Layer, Instrumentation and Sensors Layer, Control Layer, AI Layer and Management Layer.

At Cognera, our approach to full-stack industrial projects is comprehensive, covering various aspects across multiple layers. The foundational layer houses machinery and utilities. Next, the Instrumentation Layer equips these machines with essential instruments and sensors, ensuring cross-layer functionality. The third layer focuses on Industrial Automation, where we design and simulate the necessary control systems, system identification, and signal processing. The fourth layer, the AI Layer, is dedicated to fulfilling all AI-related needs, implementing decision-making processes under uncertainty, and training machines in learning and adaptation. At the pinnacle, the Management Layer provides oversight, monitoring the system’s effectiveness and reliability across all underlying layers.

Physics Info System

As an AI company, we provide machine learning models for physics information systems: Physics Informed Neural Networks (PINN). These customized models help:

Physical Understanding: Enhancing interpretation of physical phenomena deploying sophisticated models to potentially provide some level of explainability; data analysis and pattern recognition to discover inherent data in physical systems.

Predictive Modeling: Predictive modeling based on data to provide expectation without the need of further experiments or calculations.

Quantum AI

Empowering Symbiotic Relation Between Quantum Computing and AI

AI enhances Quantum Computing, and in turn, Quantum Computing amplifies AI.

At this pillar of our company, we are committed to maintaining and optimizing this mutually beneficial relationship focusing on:

Quantum Computing (QC) making faster and efficient AI
AI helping advancement of QC.

Our research endeavors in this section of company comprise:

Developing novel QC algorithms, addressing error pattern recognition and automatic noise reduction.
Quantum inspired optimization; annealing and variational algorithms.
Dimensionality reduction; harnessing the power of QC for a better features engineering.
Quantum Neural Networks (QNN).
Quantum Control and feedback systems, addressing quantum adaptive and optimal control.
Quantum Data Analyses.
Quantum Reinforcement Learning (QRL)