The Duos Difference on Methodology for Developing and Deploying AI Use Case
Our Approach: Managing the AI Process
Duos proprietary AI development and deployment methodology gives our clients complete control over the AI implementation within an organization or functional area. In addition to custom development, from acquisition to detection, we can work with an organization to ensure efficient and reliable operations which work with your current business processes rather than requiring the client to re-engineer those processes to use the technology. We provide our users with a single source of accountability and measurability against pre-defined performance criteria.
Deploy Expert AI with Experienced Railcar Mechanics
Duos in-house Railcar Mechanics serve the role of subject matter experts (SMEs) to our data scientists, labelers, developers, and engineers. While our technical teams are very proficient at building systems to automatically detect anomalies and conditions, it is the Railcar Mechanics that know the intricacies of railcars and, thereby, hold the keys to determining exactly what should be detected and why it’s important. This results in a much more efficient and accurate learning process for the algorithms whereby irrelevant or meaningless data is eliminated, resulting in a much higher level of accuracy. When new datasets are developed and new algorithms formulated, our Railcar Mechanics serve as educators to the development teams and provide insight and guidance regarding the specifics of a particular area of interest. In addition, the Railcar Mechanics closely supervise the labeling team to ensure high-quality training sets, which results in highly accurate models.
Human-in-the-Loop (HITL) is a branch of AI that brings together AI and human intelligence to create and strengthen machine learning models. In HITL, humans are involved with setting up, testing and tuning the systems and models with the goal of improving decision-making, and actioning those decisions, where appropriate. The combination of HITL and Machine Learning acts as a force multiplier by eliminating false positives and continuously improving detection capabilities. The combination combines the rapid analysis or machines with the judgement of humans.
Benefits of the Duos implementation of HITL
- Extending human-observed quality control into production runtime
- Ensures the highest possible accuracy in AI detections
- Increases learning speed for newly introduced models
- Facilitates the continuous improvement of models through the addition of human-verified and/or human-corrected cases to existing model training data
Request the latest copy of our growing AI detection catalog which showcases our deployment-ready AI detection models. Each of model is designed to target and identify specific defects and/or anomalies on railcars as they pass through the Railcar Inspection Portal (RIP®) at track speed.