Mathematical power drives future technology

Mathematics underpins every technical disciplines logical advance and mathematics education is vital to the future, according to Jim Cooper, president and CEO of Maplesoft

Since their creation, computers have been used to solve complex problems in engineering, science, and medicine. Twenty years ago, Microsoft released Windows 3.11; IBM released the first Thinkpad with an integrated CD-Rom; Al Gore coined the term ‘Information Superhighway’; and the first Zip drive and Zip disks able to store an amazing 100MB were introduced. It was also at that time that the first volume of Scientific Computing World was published, giving the information-hungry scientific community a window into developments around the world.

At that time, Maple, the symbolic computation program from Maplesoft, was six years old. Even in its infancy, Maple turned computers from very fast number-crunchers into actual mathematical assistants: solving equations; providing proofs; checking calculations; and supporting mathematicians in numerous fields. Over the last 20 years, we have seen such tools dramatically change the way engineering organisations and research institutions advance their knowledge. And we have watched them turn that knowledge into commercially-profitable innovations for consumers demanding better solutions to their problems. Today, technology has catapulted even further as we see the rise of 3D printing, no-touch interfaces such as Google’s Glass, and the invasion of computational power into every facet of our lives, beyond desktops and smartphones, and into our cars and TVs.

The evolution of Maple technology and the addition of high performance tools, such as MapleSim, have meant that our focus is on providing the expertise and tools that help engineering and scientific organisations keep pace with their customers. With increasing global competition, organisations are looking for ways to reduce costs and development times, increase efficiency, performance, and safety. Maplesoft enables organisations to achieve this, and become competitive in ways not possible 20 years ago, all based on a foundation of symbolic maths.  

Mathematics is at the core of all technical disciplines, no matter the size or complexity of the problems they solve. A wide range of organisations are using mathematics to solve problems critical to their business. With increasing competition, environmental concerns, shorter development cycles, and price pressures, the problems facing these organisations are becoming increasingly complicated. And as engineers, scientists, and mathematicians look to the future, they are seeking solutions and tools that help them find better, more efficient ways to work. Our vision is to enable our customers to meet engineering and scientific challenges efficiently.

Educating future generation of engineers and scientists is another key goal for us. With increasing class sizes and reduced funding, heavy demands are being placed on instructors’ time. However, we see trends in education that are encouraging: the advent of online courses aimed at large-scale participation and open web access; the use of mobile devices; eContent such as iTunes U, eBooks, and Flexbooks; virtualisation; distance education; and cloud computing. Mathematics education is where Maplesoft began, and we still consider it an important part of our mission. Technology continues to play a strong role in not only how we teach, but what we teach and when. Our goal is to bring theory to life, to create an engaging and interactive classroom environment, and to increase student comprehension.

When I think about the rate of progress from 20 years ago to today, I can only imagine what such an article may look like in another 20 years. It is interesting to watch the evolution of drive-by-wire, green power, and mechatronics. Likely, 2D displays will be replaced by holograms, self-driving vehicles will be widespread, and the first manned lunar bases will be established. And, each of these will be thanks, in part, to greater computational and mathematical power.


Building a Smart Laboratory 2018 highlights the importance of adopting smart laboratory technology, as well as pointing out the challenges and pitfalls of the process


Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory


This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.


This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value


This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment