AI is getting more powerful every day, and we witness its presence in our daily lives solving tougher and tougher business and consumer problems. If with great power comes great responsibility, then with great AI capabilities comes great complexity.…
You may have heard of Project Bonsai from Neal Analytics, Microsoft, or other partners for a while and are still a bit confused about what it is and what it…
Deep Reinforcement Learning (DRL) techniques have allowed deep neural networks (DNN) based AI to move from theoretical concepts in the research lab to real-life, business solutions. Although tools such as the Microsoft Project Bonsai toolchain have tremendously streamlined, accelerated, and simplified the design, training, and deployment of Autonomous Systems AI agents, it does not mean they suddenly became simple…
The traditional AI training method is rarely applicable in real-life business use cases simply because it requires an amount of data seldom available to businesses. Using the self-training mechanism of deep reinforcement learning,…
Before diving deep into the concept of using simulators to solve Reinforcement Learning (RL) real-world problems, let’s understand the basics of RL. What is Reinforcement Learning? Reinforcement Learning (RL) is an…
What is Reinforcement Learning? Deep Reinforcement Learning (DRL) or simply Reinforcement Learning (RL) is an area of machine learning that focuses on the training and decision-making abilities of AI agents.…
Autonomous Systems can solve many business problems by bringing AI from research labs to real-life use cases. Autonomous Systems leverage Deep Reinforcement Learning (DRL) techniques to train AI agents using…
What is Deep Reinforcement Learning? Deep Reinforcement Learning, or DRL, is a key technological foundation of Autonomous Systems. DRL leverages advanced process simulations and a trial-and-error approach to AI training.…
There are multiple paths to solving business challenges using data. As the saying goes “for a hammer every problem looks like a nail”. This is also true for applying advanced…
