OPTIMIZE PERFORMANCE: START YOUR ALGORITHM WITH THE SENSING SYSTEM

AI systems understand the world through sensors and algorithms. Over the past few years, we’ve seen the capabilities and performance of sensors and algorithms rapidly increasing. Combine this with the introduction of open source development tools, and today, deploying an AI system is easier than ever, allowing for rapid adoption and application. 

One thing that hasn’t changed, is the difficulty in optimizing the performance of these systems in certain scenarios. To leverage the full potential of AI and overcome this difficulty, it’s important to understand the sensing system’s signal quality and how it drives algorithm requirements and capabilities. Whether improving the performance involves tuning sensor parameters or adding capability to the algorithm, it is the designer’s responsibility to navigate these relationships and trade-offs.

Download the Twisthink sampling sheet or presentation that uses computer vision as an example to unpack the best practice of starting your algorithm development with the sensing system. Learn about why having a system level perspective is important and these 3 techniques to enable the best practice: 

• An iterative design approach
• The data driven development framework
• Designer tools to nail down the highest impact sensor parameters first