Artificial Intelligence

Many clients have historically integrated Programmable Logic Controllers into their inventive systems. Software developments now enable PLCs to interface with Machine Learning modules, increasing the functionality of the systems and introducing decision-making and creating more automated systems.

Keep in mind that the federal courts are reluctant to uphold patents for “improved software,” including software that otherwise includes groundbreaking machine learning or model training methods. For example, machine learning for fraud detection, financial forecasting, AI-based risk scoring, compliance analysis, and credit systems, or privacy-preserving machine learning should all be considered purely software-driven applications. These may be rejected by the courts as being “merely” abstract ideas.

The best course of action is to “integrate the abstract idea” into a “practical application” and/or include “significantly more” in the claims of a utility patent application. A practical application, for instance, might be an improvement to the functioning of a computer or to another technology showing how a specific technical problem is solved. The “significantly more” approach might incorporate a controller having machine learning into a system. Here are examples:

– AI-based diagnostic imaging, such as radiology
– Navigation and control systems for autonomous drones, maritime vessels, and vehicles
– AI in industrial automation and robotic perception
– Real-time transcription systems
– AI-enhanced workflows for manufacturing

Thrive IP® attorneys are able to incorporate machine learning, large language models, and cloud computing into electro-mechanical systems.