The annual MATLAB EXPO U.K. event attracted 600 delegates this year, offering a platform for users to delve into the latest advancements. The focus of the event spanned networking, technical presentations, and shared experiences covering various technology and science domains, including AI, telecommunications, autonomous systems, robotics, and electrification.

Richard Rovner, VP of Marketing at MathWorks in Natick, Massachusetts, emphasized the significance of MATLAB EXPO in user communication. He pointed out the challenge users face in keeping up with over 130 software products and biannual releases. Despite the wealth of information available on MathWorks' website and through regular digital communications, Rovner highlighted the dedicated and focused nature of the event, providing users with the opportunity to stay abreast of new capabilities and learn from each other.

In a discussion about the increasing complexity of embedded systems, Rovner acknowledged the two-decade growth in complexity across various applications, such as aero, auto, and industrial automation. He emphasized the integration of software into the early stages of the design process, making software design an integral part of the entire workflow.

To illustrate the complexity of embedded systems, Rovner shared an example of an intelligent sensor application incorporating AI. He highlighted the need to select the correct algorithm, plan algorithm training and testing, consider embedded design, deployment to the network, and address trends like digital twins and autonomous operation. Rovner emphasized the relevance of adopting a model-based design perspective, offering a platform that accelerates the development of similar devices.

Jos Martin, Director of Engineering at MathWorks, contributed insights into the evolving nature of system complexity. He noted that what was considered simple two decades ago is now significantly more intricate. Martin emphasized the substantial increase in lines of code, from 30,000 to two million, in contemporary systems. He explained why startups opt for MathWorks products from the outset, citing the necessity for rapid, cost-effective development of complex systems to create valuable products.

Martin also discussed the changing approach to system design, driven partly by necessity. With the market pushing for innovative uses of embedded hardware, complexity has become intrinsic due to the abundance of computational resources available in modern hardware.

Highlighting the importance of productivity, Martin suggested that both large and small organizations should prioritize efficiency. He shared an example of a one-person development organization realizing increased productivity through the use of system-level design tools. Martin advocated for a system model approach, using toolchains to enhance effectiveness and focusing on higher-level design concepts to improve productivity and produce higher-quality designs.

Rovner concluded by advising engineers and developers to consider modeling and simulation tools when designing engineered products. He emphasized that this approach accelerates the transition from prototype to product, reduces costs, and minimizes errors by identifying bugs early in the design process.