Shaping the Future of Industrial Control.
Blogs
Explore how reinforcement learning enables adaptive real-time autonomous optimization (RTAO).
Why trust is the real barrier to AI adoption in critical infrastructure
AI adoption in critical infrastructure is often framed as a technical challenge. In practice, the larger barrier is trust.Operators and engineers are responsible for systems where ...
How Does Reinforcement Learning Make Predictions?
By Alex Trudeau
Reinforcement Learning (RL) is formulated as a loop between an agent and its environment. An agent is a computer program that makes decisions and learns from their observed effects...
Deployment Placement: The Most Critical Question in Industrial AI
By Andy Patterson
In industrial control, where your AI runs matters as much as what it does.Software defaulted to "cloud-first" a decade ago, and Industrial AI largely inherited that assumption with...
Reports & White Papers
Cut Opex on each process with the power of reinforcement learning (RL). Access the latest results by RL Core here.
Research Foundations Underlying RL Core’s Technology
RL Core’s team is composed of internationally-recognized leaders in reinforcement learning. The Reinforcement Learning and AI (RLAI) lab at the University of Alberta is one of the top reinforcement le...
Beyond the Chatbot: Defining Industrial Agency in the Water Sector
A fundamental architectural gap exists when LLMs are proposed for real-time industrial control....
Aeration Optimization in Wastewater Treatment
Aeration is the largest energy consumer in most activated-sludge wastewater treatment plants, often accounting for 40 to 60 percent of total electricity use. It is also one of the most operationally c...
Research Foundations Underlying RL Core’s Technology
RL Core’s team is composed of internationally-recognized leaders in reinforcement learning. The Reinforcement Learning and AI (RLAI) lab at the University of Alberta is one of the top reinforcement le...
Beyond the Chatbot: Defining Industrial Agency in the Water Sector
A fundamental architectural gap exists when LLMs are proposed for real-time industrial control....
Aeration Optimization in Wastewater Treatment
Aeration is the largest energy consumer in most activated-sludge wastewater treatment plants, often accounting for 40 to 60 percent of total electricity use. It is also one of the most operationally c...
Research Foundations Underlying RL Core’s Technology
RL Core’s team is composed of internationally-recognized leaders in reinforcement learning. The Reinforcement Learning and AI (RLAI) lab at the University of Alberta is one of the top reinforcement le...
Beyond the Chatbot: Defining Industrial Agency in the Water Sector
A fundamental architectural gap exists when LLMs are proposed for real-time industrial control....
Aeration Optimization in Wastewater Treatment
Aeration is the largest energy consumer in most activated-sludge wastewater treatment plants, often accounting for 40 to 60 percent of total electricity use. It is also one of the most operationally c...