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What Marketing Leaders Need To Know About The Next Generation Of Machine Learning

By News Creatives Authors , in Leadership , at December 6, 2021

Monolith AI is a leading artificial intelligence engineering software company that is building the next generation in machine learning software.

Founded by Imperial College London and NASA alum, Dr Richard Ahlfeld, Monolith is helping companies – and their marketing leaders – design products of the future. 

I recently met with Richard to learn more about one of the biggest trends brands are turning to to revolutionise their product design – digital twin technology

Ahlfeld: “Before, a business’ old data used to sit dormant in digital storage. Fast-forward to today and it’s seen as one of the most valuable resources, and a major part of the design and testing process of any new product.”

Most companies are still learning and understanding how to collect data in the right way, but already, existing data pools are potentially worth billions in industries such as automotive and cosmetics.

“Historic data has been hoarded on desktops for decades. What’s changed is the perception of this data – that the information belongs to the collective company as opposed to the individual. Collating this information across different individuals, across different silos, transforms it into a powerful resource for these companies.” says Ahlfeld. 

This insight changes the way new products are built, by incorporating learnings from previous designs to create better, more efficient products for the future. Fabio di Memmo of leading consumer packaging business APTAR highlighted to me how this intelligence “brings innovative solutions to market faster, while reducing the risk intrinsic in speed”. 

Knowing the impact of any product or service is essential to ensure business leaders and marketeers can truly focus their efforts in the right direction.

The benefits of creating a digital version of a product using real time data, simulation and machine learning, are significant, from mapping potential construction sites to healthcare and personalised medicines.

It allows companies to test new designs and improve old ones without risking technical faults or costing additional money, enabling them to make product decisions at high speed and low cost. This development and general democratisation of machine learning has meant that this technology can become more widely used, even outside of the traditional engineering space. Of this Ahlfeld told me: “Companies are particularly excited about AI technology because it’s helping to bridge the skills gap many of them are facing today. As data science becomes a bigger part of engineering design, engineering needs people who have a USP of experience with cloud technology and AI, but also who have years of engineering experience. Many of our client’s senior engineers are approaching retirement age. Currently, BAE systems estimates that roughly 40% of their senior engineers are over the age of 50.” 

By using AI to help store expertise in the form of data, new generations can access this knowledge base and instantly incorporate it into their work. As Ahlfeld notes of a recent conversation: “Honeywell’s Vincent Blake summed it up well when I spoke to him on this recently – he said to me ‘what usually makes the difference is AI + subject matter expertise’. It really is a marriage of data and expertise right down to the granular level.” 

Ahlfeld believes whilst AI is often viewed with some scepticism, useful data can come from any number of areas to help transform the creations of the future in all kinds of unexpected ways. Take motoracing. Jota Sports Endurance Racing team are not software engineers, but they have used Monolith’s platform to create a digital replica of their racing car, allowing the team to simulate and test every alteration to the car – from altering the wing mirrors to its performance with different materials – without the expense or time required of physical tests. Through utilising deep learning models, Jota can make informed decisions based on predictive technology to create real-world change.

By embracing AI and freeing up engineers time from admin heavy tasks, engineers can once again focus their energies on creating the most innovative and breakthrough products – something that every sector can benefit from, and something that every marketing and digital leader should know about.


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